At ICRA 2022, Benjamin Rosman delivered a keynote presentation on an organization he co-founded called “Deep learning Indaba”.

Deep Learning Indaba is based in South Africa and their mission is to strengthen Artificial Intelligence and Machine Learning communities across Africa. They host yearly meetups in varying countries on the continent, as well as promote grass roots communities in each of the countries to run their own local events.

What is Indaba?

An indaba is a Zulu word for a gathering or meeting. Such meetings are held throughout southern Africa, and serve several functions: to listen and share news of members of the community, to discuss common interests and issues facing the community, and to give advice and coach others.

Benjamin Rosman

Benjamin Rosman is an Associate Professor in the School of Computer Science and Applied Mathematics at the University of the Witwatersrand, South Africa, where he runs the Robotics, Autonomous Intelligence, and Learning (RAIL) Laboratory and is the Director of the National E-Science Postgraduate Teaching and Training Platform (NEPTTP).

He is a founder and organizer of the Deep Learning Indaba machine learning summer school, with a focus on strengthening African machine learning. He was a 2017 recipient of a Google Faculty Research Award in machine learning, and a 2021 recipient of a Google Africa Research Award. In 2020, he was made a Senior Member of the IEEE.

Links

• Deep Learning Indaba
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In this episode, Audrow Nash speaks with Janet Vertessi, Assistant Professor of Sociology at Princeton, on her book Seeing Like a Rover: How Robots, Teams, and Images Craft Knowledge of Mars. The book is written about her experience living and working with NASA’s Mars Rover team, and includes her observations about the team’s leadership and their relationship with their robot millions of miles away on Mars. She also gives some advice from her findings for teams.

Janet Vertessi

Janet Vertesi specializes in the sociology of science, knowledge, and technology. She has spent the past 7 years studying several NASA spacecraft teams as an ethnographer. Her book, Seeing like a Rover: Images and Interaction on the Mars Exploration Rover Mission (Chicago, 2014) draws on over two years of ethnographic immersion with the Mars Exploration Rover mission to show how scientists and engineers use digital images to conduct scientific research on another planet. She is currently working on followup study of the NASA-ESA Cassini mission to Saturn focusing on the role of sociotechnical organization in research, data-sharing, and decision-making on robotic spacecraft teams. Vertesi is also interested in the digital sociology: whether studying computational systems in social life, shifting sociological methods online, or applying sociological insights to build new technologies.  She holds a Master’s degree from Cambridge and a PhD from Cornell, has received several grants from the National Science Foundation, and was awarded the Hacker-Mullins prize for best graduate student paper from the American Sociological Association, Science, Knowledge and Technology section in 2007.

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with Guy Hoffman
Robotics Researcher, Cornell University

An Art, Technology, and Culture Colloquium, co-sponsored by the Center for New Music and Audio Technologies and CITRIS People and Robots (CPAR), presented with Berkeley Arts + Design as part of Arts + Design Mondays.

As we continue to develop social robots designed for connectedness, we struggle with paradoxes related to authenticity, transience, and replication. In this talk, I will attempt to link together 15 years of experience designing social robots with 100-year-old texts on transience, replication, and the fear of dying. Can there be meaningful relationships with robots who do not suffer natural decay? What would our families look like if we all choose to buy identical robotic family members? Could hand-crafted robotics offer a relief from the mass-replication of the robot’s physical body and thus also from the mass-customization of social experiences?

About Guy Hoffman

Dr. Guy Hoffman is an Assistant Professor and the Mills Family Faculty Fellow in the Sibley School of Mechanical and Aerospace Engineering at Cornell University. Prior to that he was an Assistant Professor at IDC Herzliya and co-director of the IDC Media Innovation Lab. Hoffman holds a Ph.D from MIT in the field of human-robot interaction. He heads the Human-Robot Collaboration and Companionship (HRC2) group, studying the algorithms, interaction schema, and designs enabling close interactions between people and personal robots in the workplace and at home. Among others, Hoffman developed the world’s first human-robot joint theater performance, and the first real-time improvising human-robot Jazz duet. His research papers won several top academic awards, including Best Paper awards at robotics conferences in 2004, 2006, 2008, 2010, 2013, 2015, 2018, and 2019. His TEDx talk is one of the most viewed online talks on robotics, watched more than 3 million times.

About the Art, Technology, and Culture Colloquium

Founded by Prof. Ken Goldberg in 1997, the ATC lecture series is an internationally respected forum for creative ideas. Always free of charge and open to the public, the series is coordinated by the Berkeley Center for New Media and has presented over 200 leading artists, writers, and critical thinkers who question assumptions and push boundaries at the forefront of art, technology, and culture including: Vito Acconci, Laurie Anderson, Sophie Calle, Bruno Latour, Maya Lin, Doug Aitken, Pierre Huyghe, Miranda July, Billy Kluver, David Byrne, Gary Hill, and Charles Ray.

Fall 2019 – Spring 2020 Series Theme: Robo-Exoticism

In 1920, Karl Capek coined the term “robot” in a play about mechanical workers organizing a rebellion to defeat their human overlords. A century later, increasing popularism, inequality, and xenophobia require us to reconsider our assumptions about labor, trade, political stability, and community. At the same time, advances in artificial intelligence and robotics, fueled by corporations and venture capital, challenge our assumptions about the distinctions between humans and machines. To explore potential linkages between these trends, “Robo-Exoticism” characterizes a range of human responses to AI and robots that exaggerate both their negative and positive attributes and reinforce fears, fantasies, and stereotypes.

Robo-Exoticism Calendar

09/09/19 Robots Are Creatures, Not Things
Madeline Gannon, Artist / Roboticist, Pittsburgh, PA
Co-sponsored by the Jacobs Institute for Design Innovation and CITRIS People and Robots (CPAR)

09/23/19 The Copper in my Cooch and Other Technologies
Marisa Morán Jahn, Artist, Cambridge, MA and New York, NY
Co-sponsored by the Wiesenfeld Visiting Artist Lecture Series and the Jacobs Institute for Design Innovation

10/21/19 Non-Human Art
Leonel Moura, Artist, Lisbon
Co-sponsored by the Department of Spanish & Portuguese and CITRIS People and Robots (CPAR)

11/4/19 Transience, Replication, and the Paradox of Social Robotics
Guy Hoffman, Robotics Researcher, Cornell University
Co-sponsored by the Center for New Music and Audio Technologies and CITRIS People and Robots (CPAR)

01/27/20 Dancing with Robots: Expressivity in Natural and Artificial Systems
Amy LaViers, Robotics, Automation, and Dance (RAD) Lab
Co-sponsored by the Department of Theater, Dance, and Performance Studies and CITRIS People and Robots (CPAR)

02/24/20 In Search for My Robot: Emergent Media, Racialized Gender, and Creativity
Margaret Rhee, Assistant Professor, SUNY Buffalo; Visiting Scholar, NYU
Co-sponsored by the Department of Ethnic Studies and the Department of Comparative Literature

03/30/20 The Right to Be Creative
Margarita Kuleva, National Research University Higher School of Economics, Moscow
Invisible Russia: Participatory Cultures, Their Practices and Values
Natalia Samutina, National Research University Higher School of Economics, Moscow
Co-sponsored by the Department of Slavic Languages and Literature and Department of the History of Art and the Arts Research Center

04/06/20 Artist Talk
William Pope.L, Artist
Presented by the Department of Art Practice

04/13/20 Teaching Machines to Draw
Tom White, New Zealand
Co-sponsored by Autolab and CITRIS People and Robots (CPAR)

For more information:

http://atc.berkeley.edu/

Contact: info.bcnm [​at​] berkeley.edu, 510-495-3505

ATC Director: Ken Goldberg
BCNM Director: Nicholas de Monchaux
Arts + Design Director: Shannon Jackson
BCNM Liaisons: Lara Wolfe, Laurie Macfee

ATC Highlight Video from F10-S11 Season (2 mins)
http://j.mp/atc-highlights-hd

ATC Audio-Video Archive on Brewster Kahle’s Internet Archive:
http://tinyurl.com/atc-internet-archive

ATC on Facebook:
https://www.facebook.com/cal-atc

ATC on Twitter:
https://www.twitter.com/cal_atc

In this episode, Audrow Nash interviews Bilge Mutlu, Associate Professor at the University of Wisconsin–Madison, about design-thinking in human-robot interaction. Professor Mutlu discusses design-thinking at a high-level, how design relates to science, and he speaks about the main areas of his work: the design space, the evaluation space, and how features are used within a context. He also gives advice on how to apply a design-oriented mindset.

Bilge Mutlu

Bilge Mutlu is an Associate Professor of Computer Science, Psychology, and Industrial Engineering at the University of Wisconsin–Madison. He directs the Wisconsin HCI Laboratory and organizes the WHCI+D Group. He received his PhD degree from Carnegie Mellon University‘s Human-Computer Interaction Institute.

Links

• Download mp3 (15.4 MB)
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• The HCI Lab’s website
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In this episode, Audrow Nash interview Magnus Egerstedt, Professor at the Georgia Institute of Technology, about a way for anyone interested in swarm robotics to test their ideas on hardware, called the Robotarium.  The Robotarium is a 725-square-foot lab at the the Georgia Institute of Technology that houses nearly 100 rolling and flying robots.  To test their ideas, people can write their own programs, upload them to the Robotarium, and then watch the machines carry out their commands.

In this interview, Egerstedt speaks about the kinds of robots used in the Robotarium, design decisions in making the Robotarium, the differences between doing research in simulation and on hardware, and about lessons learnt and the challenges of building the Robotarium.

Magnus Egerstedt

Dr. Magnus Egerstedt is the Steve W. Chaddick School Chair and Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He holds secondary appointments in the Woodruff School of Mechanical Engineering, the School of Interactive Computing, and the Guggenheim School of Aerospace Engineering, and has previously served as the Executive Director for the Institute for Robotics and Intelligent Machines at Georgia Tech. He received the M.S. degree in Engineering Physics and the Ph.D. degree in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden, the B.A. degree in Philosophy from Stockholm University, and was a Postdoctoral Scholar at Harvard University. Dr. Egerstedt conducts research in the areas of control theory and robotics, with particular focus on control and coordination of complex networks, such as multi-robot systems, mobile sensor networks, and cyber-physical systems. Magnus Egerstedt is a Fellow of the IEEE and has received a number of teaching and research awards, including the Ragazzini Award from the American Automatic Control Council, the Outstanding Doctoral Advisor Award and the HKN Outstanding Teacher Award from Georgia Tech, the Alumni of the Year Award from the Royal Institute of Technology, and the CAREER Award from the U.S. National Science Foundation.

Links

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• GRITS Lab
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In this episode, Audrow Nash interviews Shuo Yang about DJI’s RoboMaster first-person shooter (FPS) competition, a competition designed to get people excited about robotics. For the competition, university teams build and program a robot to go against DJI’s robots in a shooting battle. Each robot has a way of propelling marble-sized plastic balls and pressure sensors on their sides to register if they’ve been hit by an opponent’s projectile. Shuo speaks about the goals of the competition, the teams that are involved, what strategies the teams use, the difficulties the team had in making their robot’s good competitors, the future of the challenge, and how people can get involved.

Note that RoboMaster’s final tournament for the FPS competition starts on July 20, 2018 and goes until July 28, 2018.

Shuo Yang

Shuo Yang is the Director of Intelligent Navigation Technologies at DJI. He obtained B.Eng and M.Phil degrees from Hong Kong University of Science and Technology (HKUST). He is involved in developing flight control and navigation technologies for several DJI flagship products, such as the Inspire 1, Phantom 4 and Matrice 100 drones and the A3 flight controller. He has coauthored 4 academic papers and obtained near 10 US patents. Shuo is also leading an educational robotics competition project called RoboMaster at DJI.

Links

• Robomaster’s Official Website
• Robomaster’s Livestream Platform
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In this episode, Audrow Nash speaks with Maja Matarić, a professor at the University of Southern California and the Chief Science Officer of Embodied, about socially assistive robotics. Socially assistive robotics aims to endow robots with the ability to help people through individual non-contact assistance in convalescence, rehabilitation, training, and education. For example, a robot could help a child on the autism spectrum to connect to more neurotypical children and could help to motivate a stroke victim to follow their exercise routine for rehabilitation (see the videos below). In this interview, Matarić discusses the care gap in health care, how her work leverages research in psychology to make robots engaging, and opportunities in socially assistive robotics for entrepreneurship.

A short video about how personalized robots might act as a “social bridge” between a child on the autism spectrum and a more neurotypical child.

A short video about how a robot could assist stroke victims in their recovery.

Maja Matarić

Maja Matarić is professor and Chan Soon-Shiong chair in Computer Science Department, Neuroscience Program, and the Department of Pediatrics at the University of Southern California, founding director of the USC Robotics and Autonomous Systems Center (RASC), co-director of the USC Robotics Research Lab and Vice Dean for Research in the USC Viterbi School of Engineering. She received her PhD in Computer Science and Artificial Intelligence from MIT, MS in Computer Science from MIT, and BS in Computer Science from the University of Kansas. 

Links

• Interaction Lab
• Embodied
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• Download MP3 (13.7 MB)

By Jeff Morgan, Trinity College Dublin

Robots have been taking our jobs since the 1960s. So why are politicians and business leaders only now becoming so worried about robots causing mass unemployment?

It comes down to the question of what a robot really is. While science fiction has often portrayed robots as androids carrying out tasks in the much the same way as humans, the reality is that robots take much more specialised forms. Traditional 20th century robots were automated machines and robotic arms building cars in factories. Commercial 21st century robots are supermarket self-checkouts, automated guided warehouse vehicles, and even burger-flipping machines in fast-food restaurants.

Ultimately, humans haven’t become completely redundant because these robots may be very efficient but they’re also kind of dumb. They do not think, they just act, in very accurate but very limited ways. Humans are still needed to work around robots, doing the jobs the machines can’t and fixing them when they get stuck. But this is all set to change thanks to a new wave of smarter, better value machines that can adapt to multiple tasks. This change will be so significant that it will create a new industrial revolution.

Industry 4.0

This era of “Industry 4.0” is being driven by the same technological advances that enable the capabilities of the smartphones in our pockets. It is a mix of low-cost and high-power computers, high-speed communication and artificial intelligence. This will produce smarter robots with better sensing and communication abilities that can adapt to different tasks, and even coordinate their work to meet demand without the input of humans.

In the manufacturing industry, where robots have arguably made the most headway of any sector, this will mean a dramatic shift from centralised to decentralised collaborative production. Traditional robots focused on single, fixed, high-speed operations and required a highly skilled human workforce to operate and maintain them. Industry 4.0 machines are flexible, collaborative and can operate more independently, which ultimately removes the need for a highly skilled workforce.

For large-scale manufacturers, Industry 4.0 means their robots will be able to sense their environment and communicate in an industrial network that can be run and monitored remotely. Each machine will produce large amounts of data that can be collectively studied using what is known as “big data” analysis. This will help identify ways to improve operating performance and production quality across the whole plant, for example by better predicting when maintenance is needed and automatically scheduling it.

For small-to-medium manufacturing businesses, Industry 4.0 will make it cheaper and easier to use robots. It will create machines that can be reconfigured to perform multiple jobs and adjusted to work on a more diverse product range and different production volumes. This sector is already beginning to benefit from reconfigurable robots designed to collaborate with human workers and analyse their own work to look for improvements, such as BAXTER, SR-TEX and CareSelect.

While these machines are getting smarter, they are still not as smart as us. Today’s industrial artificial intelligence operates at a narrow level, which gives the appearance of human intelligence exhibited by machines, but designed by humans.

What’s coming next is known as “deep learning”. Similar to big data analysis, it involves processing large quantities of data in real time to make decisions about what is the best action to take. The difference is that the machine learns from the data so it can improve its decision making. A perfect example of deep learning was demonstrated by Google’s AlphaGo software, which taught itself to beat the world’s greatest Go players.

The turning point in applying artificial intelligence to manufacturing could come with the application of special microchips called graphical processing units (GPUs). These enable deep learning to be applied to extremely large data sets at extremely fast speeds. But there is still some way to go and big industrial companies are recruiting vast numbers of scientists to further develop the technology.

Impact on industry

As Industry 4.0 technology becomes smarter and more widely available, manufacturers of any size will be able to deploy cost-effective, multipurpose and collaborative machines as standard. This will lead to industrial growth and market competitiveness, with a greater understanding of production processes leading to new high-quality products and digital services.

Exactly what impact a smarter robotic workforce with the potential to operate on its own will have on the manufacturing industry, is still widely disputed. Artificial intelligence as we know it from science fiction is still in its infancy. It could well be the 22nd century before robots really have the potential to make human labour obsolete by developing not just deep learning but true artificial understanding that mimics human thinking.

Ideally, Industry 4.0 will enable human workers to achieve more in their jobs by removing repetitive tasks and giving them better robotic tools. In theory, this would allow us humans to focus more on business development, creativity and science, which it would be much harder for any robot to do. Technology that has made humans redundant in the past has forced us to adapt, generally with more education.

But because Industry 4.0 robots will be able to operate largely on their own, we might see much greater human redundancy from manufacturing jobs without other sectors being able to create enough new work. Then we might see more political moves to protect human labour, such as taxing robots.

Again, in an ideal scenario, humans may be able to focus on doing the things that make us human, perhaps fuelled by a basic income generated from robotic work. Ultimately, it will be up to us to define whether the robotic workforce will work for us, with us, or against us.

This article was originally published on The Conversation. Read the original article.

In this episode, Audrow Nash interviews Peter Corke, Professor of Robotics at the Queensland University of Technology and Director of the Australian Centre for Robotic Vision, about Robot Academy. Robot Academy is an online platform that provides free-to-use undergraduate-level learning resources for robotics and robotic vision.

The content was developed for two 6-week Massively Open Online Courses (MOOCs) that Corke taught in 2015 and 2016. This content is now available as individual lessons (over 200 videos, each less than 10 minutes long) or in masterclasses (collections of videos, around 1 hour in duration, previously a MOOC lecture). Unlike a MOOC, all lessons are available all the time.

While the content is typically designed for undergraduate-level students, around 20% of the lessons require no more than general knowledge. Each lesson is rated in terms of difficulty (on a 5-point scale), and Robot Academy references videos on Khan Academy to help students get up to speed to follow more advanced lessons.

Peter Corke

Peter Corke is Professor of Robotics and Control at the Queensland University of Technology leading the ARC Centre of Excellence for Robotic Vision in Australia. Previously he was a Senior Principal Research Scientist at the CSIRO ICT Centre where he founded and led the Autonomous Systems laboratory, the Sensors and Sensor Networks research theme and the Sensors and Sensor Networks Transformational Capability Platform. He is a Fellow of the IEEE. He was the Editor-in-Chief of the IEEE Robotics and Automation magazine; founding editor of the Journal of Field Robotics; member of the editorial board of the International Journal of Robotics Research, and the Springer STAR series. He has over 300 publications in the field and has held visiting positions at the University of Pennsylvania, University of Illinois at Urbana-Champaign, Carnegie-Mellon University Robotics Institute, and Oxford University.

Links

• Robot Academy’s homepage
• Peter Corke’s website
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Robots raise all kinds of concerns. They could steal our jobs, as some experts think. And if artificial intelligence grows, it might even be tempted to enslave us, or to annihilate the whole of humanity. Robots are strange creatures, and not only for these frequently invoked reasons. We have good cause to be a little worried about these machines.

Imagine that you are visiting the Quai Branly-Jacques Chirac, a museum in Paris dedicated to anthropology and ethnology. As you walk through the collection, your curiosity leads you to a certain piece. After a while, you begin to sense a familiar presence heading towards the same objet d’art that has caught your attention.

You move slowly, and as you turn your head a strange feeling seizes you because what you seem to distinguish, still blurry in your peripheral vision, is a not-quite-human figure. Anxiety takes over.

As your head turns, and your vision become sharper, this feeling gets stronger. You realise that this is a humanoid machine, a robot called Berenson. Named after the American art critic Bernard Berenson and designed by the roboticist Philippe Gaussier (Image and Signal processing Lab) and the anthropologist Denis Vidal (Institut de recherche sur le développement), Berenson is part of an experiment underway at the Quai Branly museum since 2012.

The strangeness of the encounter with Berenson leaves you suddenly frightened, and you step back, away from the machine.

The uncanny valley

This feeling has been explored in robotics since the 1970s, when Japanese researcher Professor Masahiro Mori proposed his “uncanny valley” theory. If a robot resembles us, he suggested, we are inclined to consider its presence in the same way as we would that of a human being.

But when the machine reveals its robot nature to us, we will feel discomfort. Enter what Mori dubbed “the uncanny valley”. The robot will then be regarded as something of a zombie.

Mori’s theory cannot be systematically verified. But the feelings we experience when we meet an autonomous machine are certainly tinged with both incomprehension and curiosity.

The experiment conducted with Berenson at the Quai Branly, for example, shows that the robot’s presence can elicit paradoxical behaviour in museum goers. It underlines the deep ambiguity that characterises the relationship one can have with a robot, particularly the many communication problems they pose for humans.

If we are wary of such machines, it is mainly because it is not clear to us whether they have intentions. And, if so, what they are and how to establish a basis for the minimal understanding that is essential in any interaction. Thus, it is common to see visitors of the Quai Branly adopting social behaviour with Berenson, such as talking to it, or facing it, to find out how it perceives its environment.

In one way or another, visitors mainly try to establish contact. It appears that there is something strategic in considering the robot, even temporarily, as a person. And these social behaviours are not only observed when humans interact with machines that resembles us: it seems we make anthropomorphic projections whenever humans and robots meet.

Social interactions

An interdisciplinary team has recently been set up to explore the many dimensions revealed during these interactions. In particular, they are looking at the moments when, in our minds, we are ready to endow robots with intentions and intelligence.

This is how the PsyPhINe project was born. Based on interactions between humans and a robotic lamp, this project seeks to better understand people’s tendency to anthropomorphise machines.

Trying to communicate with a robotic lamp, 2016

After they get accustomed to the strangeness of the situation, it is not uncommon to observe that people are socially engaging with the lamp. During a game in which people are invited to play with this robot, they can be seen reacting to its movements and sometimes speaking to it, commenting on what it is doing or on the situation itself.

Mistrust often characterises the first moments of our relations with machines. Beyond their appearance, most people don’t know exactly what robots are made of, what their functions are and what their intentions might be. The robot world seems way too far from ours.

But this feeling quickly disappears. Assuming they have not already run away from the machine, people usually seek to define and maintain a frame for communication. Typically, they rely on existing communication habits, such as those used when talking to pets, for example, or with any living being whose world is to some degree different from theirs.

Ultimately, it seems, we humans are as suspicious of our technologies as we are fascinated by the possibilities they open up.

This article was originally published on The Conversation. Read the original article.

As human-robot interactions become commonplace, MEPs stress that EU-wide rules are needed to guarantee a standard level of safety and security.© AP Images/European Union – EP

Robots are the technology of the future. But the current legal system is incapable of handling them. This generic statement is often the premise for considerations about the possibility of awarding rights (and liabilities) to these machines at some, less-than clearly identified, point in time. Discussing the adequacy of existing regulation in accommodating new technologies is certainly necessary, but the ontological approach is incorrect. Instead a functional approach needs to be adopted, identifying:

1. what rules can be applied to robots (as is);
2. what incentives do such rules provide;
3. whether those incentives are desirable.

The recent Resolution of the European Parliament (henceforth Resolution) has great political relevance and strategic importance in the development of a European Robotic Industry. Its considerations and conclusions will be taken into account in the current position paper.

Issues

The first issue when discussing regulation is that of definitions, for one cannot regulate something without firstly defining it. However, the term robot is technical and encompasses a wide range of applications that have very little in common. For this very reason, it is impossible to develop a unitary body of rules applicable to all kinds of robotic applications, rather different rules should apply to different classes of devices.

The major issue when discussing civil law rules on robotics is that of liability (for damages). Automation might, to some extent, challenge some of the existing paradigms; and increasing human-machine cooperation might cause different sets of existing rules to overlap, leading to uncertainty, thence increased litigation and difficulties in insuring new products.

Connected to the above is robot testing. A clear legal framework for robot testing outside the restricted environment of the laboratory is needed to assess the kind of dangers that might emerge with the use and their statistical frequency (also for insurance purposes). Similarly, standardization and the development of adequate, narrow-tailored technical standards for different kinds of robots is a major concern, both to ensure product safety and the adoption of possible alternatives to existing liability rules.

A possible non-issue when discussing rules for robotics is that of the attribution of personhood. This, if intended in an ontological way, is deprived of any reasonable grounding in both technical, philosophical and legal considerations. Instead, if understood in a purely functional way the attribution of legal personhood (like in the case for corporations) might be open for discussion (in some cases). Considering some more specific kinds of applications, in particular biorobotic devices and the issue of human enhancement, its regulation and management becomes of the greatest importance and quite likely the single most relevant bioethical issues of the nearby future, requiring ad-hoc regulation to be adopted.

Finally, privacy regulation, access to data and data use is of pivotal importance, not only for the development of a European Robotics industry but more broadly for a digital market. All the mentioned issues might fall under some – direct or indirect – competences of the EU and would certainly benefit from regulations adopted at a supranational (thence European) level.

Responses

The Resolution addresses all the above mentioned issues with consistent considerations, depicting an adequate framework for a technical – legal – debate about what narrow tailored sets of rules should be adopted at the EU level. Overall, it is of the greatest political and strategical importance for defining a modern legal system, favorable to the immersion of new technologies and the proliferation of new businesses.

More specifically:

Definitions: there is need for a definition of “robot” that needs to be inclusive. What needs to be avoided are nominalistic discussions which would inevitably emerge as soon as a regulation was adopted (should the notion of robot be too narrow). Debates about whether a robot requires to be autonomous or not, controlled or not, embodied or not are irrelevant from a legal point of view. Instead, such characteristics should allow to distinguish sub-classes of robots that might be regulated unitarily. Thence, next to a broader and all-encompassing definition of robot (that should include software and non-embodied AI), narrower definitions should be elaborated, pooling together those applications that show some relevant similarities and that can be regulated unitarily.

Liability: Human-machine cooperation will cause different sets of rules to overlap (namely product liability rules and traditional tort law principles). This will cause high levels of uncertainty and litigation, delaying innovation. With respect to compensation, it is, in many cases, sensible to separate the function of ensuring product safety from that of providing the victim with compensation. This might justify different alternative solutions to be adopted: liability exemptions for users and/or manufacturers; creation of automatic compensations funds (privately or publicly funded); compulsory insurance provisions. More broadly, the inadequacies of existing rules (in particular product liability rules) might suggest to radically replace a fault based rule with a risk-management approach (based on absolute liability rules) holding liable the party who is better placed to minimize the cost and acquire insurance (Resolution nn. 53, 55). A one-stop-shop approach might be sensible, preventing complex litigation to apportion liability among different players involved. Which solution is preferable depends on the class of applications considered, the market for such products and the possibility to address those risks through insurance (Resolution nn. 57-59).

Testing: a uniform set of rules allowing testing outside the laboratories and even in human environments should be adopted, defining clear standards (in particular with respect to safety, insurance and management of the experiment) thus reducing discretionary powers of local authorities (Resolution n. 23).

Standardization & European Robotics Agency: standards represent the most effective way to ensure high levels of product safety and provide certainty ex ante to manufacturers who conform to them (Resolution n. 22). However, the time required for the adoption of a new standard and its breadth is incompatible with the current pace of technological innovation. A European Robotic Agency, such as the one suggested by the Resolution (nn. 15-17), could have a strategic importance setting a supranational standard, that could be of use beyond European borders. Otherwise, other leading economies will attempt to do the same.

Electronic Personhood: set forth by the Resolution, this notion is purely functional and intends to facilitate the registration, insurance and management of some devices (in particular nonembodied AI) with a legal tool that is equivalent to that used for corporations (so called legal personhood), see Resolution n. 59, let. E) and F).

Human Enhancement: the use of robotics to overcome human limits might become problematic given the lack of a clear sets or rules and criteria that could help discern what kind of manipulations of the human body should be allowed. The constitutional principles of human dignity, equality, and freedom of self-determination, as understood today in the broader bioethical debate are per se insufficient, and narrower criteria ought to be adopted. The legal grounds to justify an intervention by the EU in this field are less evident than in all other matters mentioned, however they can be found in the freedom of movement of EU citizens, which would suggest, to some extent, a uniform framework. With respect to the content of such principles, human dignity ought to be understood as objective and external, limiting self-determination, and reversibility of the intervention onto the body should also be taken into consideration.

Privacy & Free Flow of Data: privacy cannot be granted simply through informed consent. Consent is hardly ever truly informed, and the very possibility to dissent is limited, should one want to use the service or device requiring the collection of personal data for its operation. On the one hand, the current EU Regulation setting forth the “-by design” principle, should be narrowed down through the adoption of specific standards, specifying what satisfies that criteria in different classes of applications (see Recommendation nn. 17-21). On the other hand, consumers should be compensated for allowing access and use of – private and anonymized – data through post-sale services, enriching after-sale duties imposed on the producer.

Credit: Ex Machina (2015).

Seventy-five years ago, the celebrated science fiction writer Isaac Asimov published a short story called Runaround. Set on Mercury, it features a sophisticated robot nicknamed Speedy that has been ordered to gather some of the chemical selenium for two human space adventurers.

Speedy gets near the selenium, but a toxic gas threatens to destroy the robot. When it retreats from the gas to save itself, the threat recedes and it feels obliged to go back for the selenium. It is left going round in circles.

Speedy is caught in a conflict between two of the laws that robots in Asimov’s stories follow as their core ethical programming: always obey human instructions and always protect your existence (as long as it doesn’t result in human injury).

Speedy’s custodians resolve the robot’s conflict by exploiting a third, overriding law: never let a human being come to any harm. They place themselves in harm’s way and tell Speedy if he does not get the selenium they will die. This information straightens out Speedy’s priorities, and the adventurers live to interfere with other planets.

Today, Asimov’s three laws of robotics are much better known than Runaround, the story in which they first appeared. The laws seem a natural response to the idea that robots will one day be commonplace and need internal programming to prevent them from hurting people.

Yet, while Asimov’s laws are organised around the moral value of preventing harm to humans, they are not easy to interpret. We need to stop viewing them as an adequate ethical basis for robotic interactions with people.

Part of the reason Asimov’s laws seem plausible is that fears about the harm robots could do to humans are not groundless. There have already been fatalities in the US due to malfunctioning autonomous cars.

Again, the capacities of artificial intelligence to adjust its routines to the things and people they interact with, makes some of its behaviour unpredictable. For example, machines that are capable of interacting with each other in a co-ordinated way can produce “swarm” behaviour. Swarm behaviour can be unpredictable because it can depend on adapting to random events.

So Asimov was right to worry about unexpected robot behaviour. But when we look more closely at how robots actually work and the tasks they are designed for, we find that Asimov’s laws fail to apply clearly. Take military drones. These are robots directed by humans to kill other humans. The whole idea of military drones seems to violate Asimov’s first law, which prohibits robot injury to humans.

But if a robot is being directed by a human controller to save the lives of its co-citzens by killing other attacking humans, it is both following and not following the first law. Nor is it clear if the drone is responsible when someone is killed in these circumstances. Perhaps the human controller of the drone is responsible. But a human cannot break Asimov’s laws, which are exclusively directed at robots.

Meanwhile, it may be that armies equipped with drones will vastly reduce the amount of human life lost overall. Not only is it better to use robots rather than humans as cannon fodder, but there is arguably nothing wrong with destroying robots in war, since they have no lives to lose and no personality or personal plans to sacrifice.

We need the freedom to harm ourselves

At the other end of the scale you have robots designed to provide social care to humans. At their most sophisticated, they act as companions, moving alongside their users as they fetch and carry, issue reminders about appointments and medication, and send out alarms if certain kinds of emergencies occur. Asimov’s laws are an appropriate ethics if keeping an elderly person safe is the robot’s main goal.

But often robotics fits into a range of “assistive” technology that helps elderly adults to be independent. Here the goal is to enable the elderly to prolong the period during which they can act on their own choices and lead their own lives, like any other competent adult. If this is the overriding purpose of a care robot, then, within limits, it needs to accommodate risk-taking, including its owner putting itself in harm’s way.

For example, falling is an everyday hazard of life after the age of 65. An elderly person can rationally judge that living with the after-effects of a fall is better than a regime in which they people are heavily monitored and insulated from all danger. But a robot that deferred to this judgement by not intefering when its user wants to take a steep walk would be violating the law that saved Asimov’s adventurers on Mercury.

So long as only minor injury results from a competent adult decision, it should be respected by everyone, robots and family alike, even when it is taken by an elderly person. Respect in these circumstances means not preventing the adult decision-maker from acting or informing others about their actions.

As robots become a bigger part of our society, we will undoubtedly need rules to govern how they operate. But Asimov’s laws either fail to recognise that robots get caught between human acts and cannot always avoid human injury. And that sometimes allowing humans to injure themselves is a way of respecting human autonomy.

Science fiction has already explored the theme of robot rights, such as the film Bicentennial Man. Image: Columbia Pictures

Science fiction likes to depict robots as autonomous machines, capable of making their own decisions and often expressing their own personalities. Yet we also tend to think of robots as property, and as lacking the kind of rights that we reserve for people.

But if a machine can think, decide and act on its own volition, if it can be harmed or held responsible for its actions, should we stop treating it like property and start treating it more like a person with rights?

What if a robot achieves true self-awareness? Should it have equal rights with us and the same protection under the law, or at least something similar?

These are some of the issues being discussed by the European Parliament’s Committee on Legal Affairs. Last year it released a draft report and motion calling for a set of civil law rules on robotics regulating their manufacture, use, autonomy and impact upon society.

Of the legal solutions proposed, perhaps most interesting was the suggestion of creating a legal status of “electronic persons” for the most sophisticated robots.

Approaching personhood

The report acknowledged that improvements in the autonomous and cognitive abilities of robots makes them more than simple tools, and makes ordinary rules on liability, such as contractual and tort liability, insufficient for handling them.

For example, the current EU directive on liability for harm by robots only covers foreseeable damage caused by manufacturing defects. In these cases, the manufacturer is responsible. However, when robots are able to learn and adapt to their environment in unpredictable ways, it’s harder for a manufacturer to foresee problems that could cause harm.

The report also questions about whether or not sufficiently sophisticated robots should be regarded as natural persons, legal persons (like corporations), animals or objects. Rather than lumping them into an existing category, it proposes that a new category of “electronic person” is more appropriate.

The report does not advocate immediate legislative action, though. Instead it proposes that legislation be updated if robots become more complex; if and when they develop more behavioural sophistication. If this occurs, one recommendation is to reduce the liability of “creators” proportional to the autonomy of the robot, and that a compulsory “no-fault” liability insurance could cover the shortfall.

But why go so far as to create a new category of “electronic persons”? After all, computers still have a long way to go before they match human intelligence, if they ever do.

But it can be agreed that robots – or more precisely the software that controls them – is becoming increasingly complex. Autonomous (or “emergent”) machines are becoming more common. There are ongoing discussions about the legal liability for autonomous vehicles, or whether we might be able to sue robotic surgeons.

These are not complicated problems as long as liability rests with the manufacturers. But what if manufacturers cannot be easily identified, such as if open source software is used by autonomous vehicles? Whom do you sue when there are millions of “creators” all over the world?

Artificial intelligence is also starting to live up to its moniker. Alan Turing, the father of modern computing, proposed a test in which a computer is considered “intelligent” if it fools humans into believing that the computer is human by its responses to questions. Already there are machines that are getting close to passing this test.

There are also other incredible successes, such as the computer that creates soundtracks to videos that are indistinguishable from natural sounds, the robot that can beat CAPTCHA, one that can create handwriting indistinguishable from human handwriting and the AI that recently beat some of the world’s best poker players.

Robots may eventually match human cognitive abilities and they are becoming increasingly human-like, including the ability to “feel” pain.

If this progress continues, it may not be long before self-aware robots are not just a product of fantastic speculation.

The EU report is among the first to formally consider these issues, but other countries are also engaging. Peking University’s Yueh-Hsuan Weng writes that Japan and South Korea expect us to live in a human-robot coexistence by 2030. Japan’s Ministry of Economy, Trade and Industry has created a series of robot guidelines addressing business and safety issues for next generation robots.

Electronic persons

If we did give robots some kind of legal status, what would it be? If they behaved like humans we could treat them like legal subjects rather than legal objects, or at least something in between. Legal subjects have rights and duties, and this gives them legal “personhood”. They do not have to be physical persons; a corporation is not a physical person but is recognised as a legal subject. Legal objects, on the other hand, do not have rights or duties although they may have economic value.

Assigning rights and duties to an inanimate object or software program independent of their creators may seem strange. However, with corporations we already see extensive rights and obligations given to fictitious legal entities.

Perhaps the approach to robots could be similar to that of corporations? The robot (or software program), if sufficiently sophisticated or if satisfying certain requirements, could be given similar rights to a corporation. This would allow it to earn money, pay taxes, own assets and sue or be sued independently of its creators. Its creators could, like directors of corporations, have rights or duties to the robot and to others with whom the robot interacts.

Robots would still have to be partly treated as legal objects since, unlike corporations, they may have physical bodies. The “electronic person” could thus be a combination of both a legal subject and a legal object.

The European Parliament will vote on the resolution this month. Regardless of the result, reconsidering robots and the law is inevitable and will require complex legal, computer science and insurance research.

This article was originally published on The Conversation. Read the original article.

Cows in stable wait for food from red feeding robot

Let’s assume, for a moment, that the vision I’ve laid out in this blog is ridiculously successful, and, over the next few decades, robotic devices take over all aspects of tending land and crops and handling material inputs and produce, and do it using increasingly sustainable practices that begin the process of retaining and enhancing biological diversity and reviving overworked soils. What’s left for farmers to do? Will there even be a need for humans on farms?

Well, in that improbable scenario, once the process has run its course and there’s no room left for qualitative improvement, and the machines are self-repairing and the algorithms are self-optimizing for constantly changing conditions, perhaps, strictly speaking, the answer would be “no, not really, not a need in the sense of an indispensable component.” A farm so equipped might run itself for months or years at a time without human intervention.

There are two problems with this, however. First, that level of automation is unlikely to happen in the lifetime of anyone reading this, and for the foreseeable future there will be need for human involvement in design and management decisions, making use of their own senses in combination with data to drive improvements, as well as filling in the gaps in the perceptual and physical capabilities of the machines.

The other objection has no expiration date. It’s about whether a human presence brings anything valuable to land husbandry, and ultimately whether people are allowed to forget where their food comes from, such that, if all of the machines were to suddenly shut down or break, no one would have a clue as to how to proceed. There will always be a need for humans who understand why the machines make the choices they do, and that understanding will always be best achieved when augmented by being physically present, walking fields, examining details with a magnifying glass, experiencing the sounds and smells directly, and lending a hand with some of the work, even when it could be done faster and more precisely by one of the machines, just to have the experience of participating in the process.

Without such people who remain deeply connected to the land and our use of it to act as interpreters, those who live in urban areas will have only feeds from the machines themselves and will probably lose interest, and perhaps also lose the will to maintain support for environmentally responsible policies in the face of periodic calls for austerity and ever-increasing efficiency. Actually, we’re faced with that challenge right now, so maybe there are already too few people on the land, or those who are engaged in farming don’t have the time for learning about all of the ‘extraneous’ factors not obviously relevant to their low-margin agribusiness operations, or for acting as interpreters for others.

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• Keeping a robotic eye on pollution

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Pepper, Jibo and Milo make up the first generation of social robots, leading what promises to be a cohort with diverse capabilities and future applications. But what are social robots and what should they be able to do? This article gives an overview of theories that can help us understand social robotics better.

I most like the definition which describes social robots as robots for which social interaction plays a key role. So social skills should be needed by the robot to enable them to perform a function. A survey of socially interactive robots defines some key characteristics that of this type of robot. A social robot should show emotions, have capabilities to converse on an advanced level, understand the mental models of their social partners, form social relationships, make use of natural communication cues, show personality and learn social capabilities.

Understanding Social Robots offers another interesting perspective of what a social robot is: Social robot = robot + social interface

In this definition, the robot has its own purpose outside of the social aspect. Examples of this can be care robots, cleaning robots in our homes, service desk robots at an airport or mall information desk or chef robots in a cafeteria. The social interface is simply a kind of familiar protocol which makes it easy for us to communicate effectively with the robot. Social cues can give us insight into the intention of a robot, for example shifting gaze towards a mop gives a clue that the robot is about to change activity, although they might not have eyes in the classical sense.

These indicators of social capability can be as useful as actual social ability and drivers in the robot. As studies show, children are able to project social capabilities onto simple inanimate objects like a calculator. A puppet becomes an animated social partner during play. In the same way, robots only have to have the appearance of sociability to be effective communicators. An Ethical Evaluation of Human–Robot Relationships confirms this idea. We have a need to belong, which causes us to form emotional connections to artificial beings and to search for meaning in these relationships.

How should social robots look?

Masahiro Mori defined the Uncanny Valley theory in 1970, in a paper on the subject. He describes the effects of robot appearance and robot movement on our affinity to the robot. In general, we seem to prefer robots to look more like humans and less like robots. There is a certain point at which robots look both human-like and robot-like, and it becomes confusing for us to categorise them. This is the Uncanny Valley – where robot appearance looks very human but also looks a bit ‘wrong’, which makes us uncomfortable. If robot appearance gets past that point, and looks more human, likeability goes up dramatically.

In Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley (2) we learn that there is a similar effect between robot appearance and trustworthiness of a robot. Robots that showed more positive emotions were also more likeable. So it seems like more human looking robots would lead to more trust and likeability.

Up to this point, we assume that social robots should be humanoid or robotic. But what other forms can robots take? The robot should at least have a face to give it an identity and make it an individual. Further, with a face, you can indicate attention and imitate the social partner to improve communication. Most non-verbal cues are relayed through the face and creates an expectation of how to engage with the robot.

The appearance of a robot can help set people’s expectations of what they should be capable of, and limit those expectations to some focused functions which can be more easily achieved. For example, a bartender robot can be expected to be able to have a good conversation and serve drinks, take payment, but probably it’s ok if it can only speak one language, as it only has to fit the context it’s in.

In Why Every Robot at CES Looks Alike, we learn that Jibo’s oversized, round head is designed to mimic the proportions of a young animal or human to make it more endearing. It has one eye to prevent it from triggering the Uncanny Valley effect by looking too robotic and human at the same time. Also, appearing too human-like creates the impression that the robot will respond like a human, while they are not yet capable.

Another interesting example is of Robin, a Nao robot being used to teach children with diabetes how to manage their illness (6). The explanation given to the children is that Robin is a toddler. The children use this role to explain any imperfections in Robin’s speech capabilities.

Different levels of social interaction for robots

A survey of socially interactive robots contains some useful concepts in defining levels of social behaviour in robots:

• Socially evocative: Do not show any social capabilities but rely on human tendency to project social capabilities.
• Social interface: Mimic social norms, without actually being driven by them.
• Socially receptive: Understand social input enough to learn by imitation but do not see social contact.
• Sociable: Have social drivers and seek social contact.
• Socially situated: Can function in a social environment and can distinguish between social and non-social entities.
• Socially embedded: Are aware of social norms and patterns.
• Socially intelligent: Show human levels of social understanding and awareness based on models of human cognition.

Clearly, social behaviour is nuanced and complex. But to come back to the previous points, social robots can still make themselves effective without reaching the highest levels of social accomplishment.

Effect of social robots on us

To close, de Graaf poses a thought-provoking question (4):

How will we share our world with these new social technologies and how will a future robot society change who we are, how we act and interact—not only with robots but also with each other?

It seems that we will first and foremost shape robots by our own human social patterns and needs. But we cannot help but be changed as individuals and a society when we finally add a more sophisticated layer of robotic social partners in the future.

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Credit: Catalia Health

Catalia Health is leading the surge in social robotics, with Mabu, their patient care management system. Catalia Health likes to be seen primarily as a health company that utilizes robots, rather than a robotics company. This focus on solving real world problems while shipping a product has seen Catalia attract both customers and investors, and recently close their Series A round.

Interview with Cory Kidd, Founder & CEO of Catalia Health

(edited for clarity)

What is Catalia Health?

Catalia Health is a patient care management company. We focus on helping patients adhere to their treatment, whether that be taking medication, or managing chronic disease over the long term. That’s the focus of what we do, and part of how we deliver this to patients is through a cute little robot called Mabu who engages with patients through conversation. She’s a little over a foot tall, and can sit wherever you want to put her … on a countertop or bedside table … and she has big eyes that make eye contact with you while you’re talking to her. Conversations with her might last a minute or two, or maybe five or ten minutes; it really depends on the individual patient and what they want to talk about.

Mabu has a touch screen on the front that she can use to display information, but our overall focus is to create an engaging relationship between the technology and the patient. The reason that we use the robot — as opposed to just delivering this through a phone screen or a tablet or PC — is about psychology and not about technology. When we are in front of a robot that has eyes that can look at us and blink, we tend to be more engaged, and we find the robot to be more credible and informative than if the same information were delivered to us through an app. While we have a lot of healthcare applications that we’re looking to build, the core of this is really just basic psychology: how can we create engagement that lasts for a long time? Psychologists have studied the benefits of face-to-face communication for decades.

Is speech the primary interaction that people have with Mabu?

Our platform’s primary means of interaction is conversation, but this can happen in more than one way. For example, when Mabu is talking, she also displays what she is saying on her screen, to make it easy for anyone to understand what’s going on. And when I reply, I can speak back to her, or I can touch a button or location on the screen. And if I’m not at home, I can also get a reminder via text message … in the future this might happen through an app or other desktop interface.

The physical robot is the thing that’s creating the engagement — the relationship — but we can interact with people through other forms of technology as well.

Does the conversation with Mabu end at home? How is information transferred to the healthcare provider?

We do send information summaries back to health care providers — a pharmacist or physician or some other caregiver — but the overall problem we are trying to help with is that the healthcare system simply doesn’t have enough people to manage chronic disease at scale. So while our technology might also enable tele-operation or tele-presence, the focus of our business is to be able carry out an autonomous one-on-one interaction with patients in real time.

Is the patient, or end user, your customer?

Patients get a lot of benefit from our platform, but they are not the ones who are paying for it.

Our direct customers are pharmaceutical manufacturers and healthcare providers. They provide programs to help patients be more effective at taking their medications and managing their conditions, so in their eyes we are another tool in their arsenal.

Can you tell us about your first deployments?

The places where we are rolling out first are where there are existing care management programs already in place, and these tend to be in areas such as oncology and immunology where higher-end drugs are being used. Talking robots are very new and different, so we wanted our contract structure to look as similar as possible to existing offerings. These were the areas where there were already contract types that we could follow into market. We have been rolling out the first several hundred units in the first half of 2016 and are bringing patients onto the platform by the end of this year.

What is your business model? Is it “Robots as a Service”?

In terms of the patient relationship, our robot is key. But in terms of our business model and contracts, we don’t think of our robot as the key piece of what we’re delivering. We use a service model for care management; our customers pay us on a per patient per month basis.

What does interaction with your service look like from the patient’s perspective?

If you want to see what the patient interaction with Mabu actually looks like, we have a short video at cataliahealth.com.

Once the patient plugs Mabu in, the robot comes alive and starts talking. The conversation starts off with greetings and small talk (such as “Good morning, great to see you!”) and then moves on to whatever issue is relevant to the patient at that point in time. Maybe this is simply to check in on whether the patient has taken their medication, or maybe the patient is at a point in their treatment where it’s common to experience certain side effects, and the conversation is about how best to mitigate those for that patient. It really depends on the particular condition or treatment the patient is dealing with. We do a lot of research on each condition before rolling the platform out to patients, in order to build an understanding of common treatment challenges into the application.

In the background, the conversation is being crafted in real time for that patient.

When Mabu first comes out of the box, we know a little about the patient’s medical condition — perhaps what drugs they are on — but we don’t know much else. So from that very first conversation we start learning about and adapting to the patient’s individual personality and the treatment issues they are facing. Mabu largely directs the conversations, but the patient has a lot of say in terms of where that conversation goes. As we build more conversations and more AI into the platform, we are able to craft appropriate conversations for the patient.

This will very quickly become applicable to a lot more drugs and a lot more disease states. Let’s look at side effects, for example. Our first conversations about side effects will be new, but there are many common side effects among drugs. So while we are starting out in just a handful of areas, our goal is to help any patient who’s dealing with a condition on an ongoing basis to better manage their care, and to provide information back to their caregivers so that they can be more effective in supporting them.

Is it valid to be concerned about robots being used to replace human companionship?

We certainly don’t think of this as robots replacing people; we think of it as robots augmenting people.

One of the big challenges in healthcare today is that there are not enough caregivers to deliver healthcare the way we need it. Almost half our population is managing a chronic disease in this country, and there are very similar rates in advanced nations around the world; if we look at the rate of people dealing with health issues on an ongoing basis, it approaches 2/3 to 3/4 of the population.

People might get to see their doctor for fifteen minutes every two months, but that’s not much time, and it’s not an effective way to provide the ongoing care that is needed. We simply don’t have enough people to manage healthcare the way we did 50 or 100 years ago.

Patients need reminders, and they need answers to all the little questions that come up — and that’s where technology like this comes in. We see our service as a way for the people who are providing health care — doctors, nurses, and other trained caregivers — to more effectively reach a larger group of patients. We are not trying to be people’s doctors, we are trying to help their doctor do a much more effective job.

What kind of feedback have you received so far?

Broadly speaking, the feedback has been very positive. People tend to like the interaction right from the very first conversation, and they like how Mabu adapts to them.

We have a great solution that we’ve shown can effectively help many patients, but we still have a lot to learn. We are really excited about the amount of data that we’re going to be getting back from hundreds of person-months of interaction with our platform this year, and how we’re going to use that to improve conversations and personalize them to every patient.

Thanks to social platforms like Siri, Jibo and Amazon’s Echo, we are starting to get used to having conversations with our devices. But you’ve taken a very specialized path into the market. Why did you pick this pathway and business model?

Scalability — being able to provide care to a growing number of patients — is a big challenge in health care. I spent about a year before launching Catalia Health really digging into the US healthcare market to explore the business opportunities. We were thinking broadly around medication adherence and chronic disease management, talking to potential customers and trying to understand where there was a need for this kind of technology. The quick answer was that it is needed pretty much everywhere within the healthcare system. The question of how to provide healthcare in a cost-effective and scalable way is definitely a challenge here in the US, and also in most other nations in the world. We see an enormous opportunity for using technology to provide scalable personalized care.

Of all the robotics and AI movies that have come out in the past five or ten years, Robot and Frank offers a vision comes closest to what we’re doing. The goal of the robot in that movie was to help Frank live healthier by building a relationship with him. We have the same underlying premise in what we’re doing: our technology is focused on building a relationship with the patient, because once we can do that, then we can talk to them about their health care. By comparison, usage rates on healthcare apps are incredibly low; most patients don’t pick them up after the first or second try. But as it turns out, there are particular psychological aspects of how people interact with robots that make them really effective at helping to solve this challenge.

Do you see ways that other robotics companies can leverage what you’ve learned so far?

The broad lesson is to understand where there is a real human or business need. Asking “Where is there a problem that I can solve?” rather than asking “Where can I build a robot?” or “What market can I serve?”

It’s also important to understand what the existing marketplace looks like for those kinds of solutions right now, because the solution today may look very different. Our robot is an alternative to talking to a pharmacist on the phone, and it’s a very different solution, but understanding what the business model is for that kind of service, how those contracts work, who the players are in the space — I think that’s something that any company would be smart to take a look at and understand deeply before trying to compete in those markets.

You’re tackling one of the largest growing areas of our economy, and you’re doing it with a combination of data, AI and robotics. What do you think has changed in the past couple of years to make robotics a viable solution to a broader range of applications?

One of the biggest changes has been in the cost of building both hardware and software. Our robot is pretty simple; we’re not doing anything cutting edge in terms of the physical device that we’re building. But ten years ago producing our device might have cost 100 times what it does today, and that would have limited us to a small set of business models and it would have been very hard to make money.

With the cost of building the technology drastically lowered, it has enabled us to do something very different today than what we could have done five years ago. Today we can build cutting edge technology at a reasonable price point and therefore deliver a cost effective solution.

CATALIA HEALTH

Catalia Health is a patient health management system using social robotics. Founded in 2013 by Dr. Cory Kidd, Catalia Health builds on years of research into Human-Robot Interaction starting at MIT’s Media Lab and continuing with social robot startups like Intuitive Automata. In June 2015, Khosla Ventures led a $1.25 million seed round in Catalia Health for the first trial customer engagements. Catalia Health is on a mission to address both sides of the healthcare equation: improving patients’ health and extending the capabilities and efficiency of healthcare companies.

SILICON VALLEY ROBOTICS

Silicon Valley Robotics is the industry group for robotics and AI companies in the Greater San Francisco Bay Area, and is a not- for-profit (501c6) that supports innovation and commercialization of robotics technologies. We host the Silicon Valley Robot Block Party, networking events, investor forums, a directory, and a jobs board, and we provide additional services and information for members, such as these reports.

We’ll be releasing additional essays from the reports every week or so. You can read full reports by visiting the website.

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Image: Gerd Altmann

The MIT Media Lab and the Berkman Klein Center for Internet and Society at Harvard University will serve as the founding anchor institutions for a new initiative aimed at bridging the gap between the humanities, the social sciences, and computing by addressing the global challenges of artificial intelligence (AI) from a multidisciplinary perspective.

“Artificial intelligence agents will impact every part of our lives in every society on Earth. Technology and commerce will see to that,” says Alberto Ibargüen, president and CEO of the John S. and James L. Knight Foundation, which is among those supporting the initiative.

Initially funded with $27 million from the Knight Foundation; LinkedIn co-founder Reid Hoffman; the Omidyar Network; the William and Flora Hewlett Foundation; and Jim Pallotta, founder of the Raptor Group, the Ethics and Governance of Artificial Intelligence Fund’s mission is to catalyze global research that advances AI for the public interest, with an emphasis on applied research and education. The fund will also seek to advance public understanding of AI.

“AI’s rapid development brings along a lot of tough challenges,” explains Joi Ito, director of the MIT Media Lab. “For example, one of the most critical challenges is how do we make sure that the machines we ‘train’ don’t perpetuate and amplify the same human biases that plague society? How can we best initiate a broader, in-depth discussion about how society will co-evolve with this technology, and connect computer science and social sciences to develop intelligent machines that are not only ‘smart,’ but also socially responsible?”

What makes this new initiative different and necessary is that it’s aimed at transcending barriers and breaking down silos among disciplines. As founding academic institutions, the Media Lab and Berkman Klein Center, along with other potential collaborators from the public and private sectors, will act as a mechanism to reinforce cross-disciplinary work and encourage intersectional peer dialogue and collaboration.

The fund — projected to operate with a phased approach over the next several years — will complement and collaborate with existing efforts and communities, such as the upcoming public symposium “AI Now,” which is scheduled for July 10 at the MIT Media Lab. The fund will also oversee an AI fellowship program, identify and provide support for collaborative projects, build networks out of the people and organizations currently working to steer AI in directions that help society, and also convene a “brain trust” of experts in the field.

A collaborative network

The Media Lab and the Berkman Klein Center for Internet and Society will leverage a network of faculty, fellows, staff, and affiliates who will collaborate on unbiased, sustained, evidenced-based, solution-oriented work that cuts across disciplines and sectors. This research will include questions that address society’s ethical expectations of AI, using machine learning to learn ethical and legal norms from data, and using data-driven techniques to quantify the potential impact of AI, for example, on the labor market.

Work of this nature is already being undertaken at both institutions. The Media Lab has been exploring some of the moral complexities associated with autonomous vehicles in the Scalable Cooperation group, led by Iyad Rahwan. And the Personal Robots group, led by Cynthia Breazeal, is investigating the ethics of human-robot interaction.

“AI could be as big a disruptor to the world as the Industrial Revolution was in the 18th and 19th centuries,” Rahwan says. He cites transportation systems and employment as among the areas that will likely be affected by automation and AI. “What we need is something that puts our entire society in the control loop of these systems … technologists, engineers, the public, ethicists, cognitive scientists, economists, legal scholars, anthropologists, faith leaders, government regulators — everyone crucial to protecting the public interest.”

“Artificial Intelligence provides the potential for deeply personalized learning experiences for people of all ages and stages,” says Breazeal, who emphasizes the need for AI to reach people in developing nations and underserved populations. But she adds that it is also “a kind of double-edged sword. What should it be learning and adapting to benefit you? And what should it do to protect your privacy and your security?”

Shared goals and governance

The Berkman Klein Center has been working to develop public interest-oriented solutions to many of the challenges of the digital age, incubating programs such as Creative Commons and the Digital Public Library of America. And, it is currently collaborating with the Media Lab on the “Assembly” program, which gathers high-level developers and tech industry professionals for a rigorous three-week course at Harvard University, followed by a 12-week collaborative development period to explore difficult problems in cybersecurity.

“The thread running through these otherwise disparate phenomena is a shift of reasoning and judgment away from people,” says Jonathan Zittrain, co-founder of the Berkman Klein Center and professor of law and computer science at Harvard University. “Sometimes that’s good, as it can free us up for other pursuits and for deeper undertakings. And sometimes it’s profoundly worrisome, as it decouples big decisions from human understanding and accountability. A lot of our work in this area will be to identify and cultivate technologies and practices that promote human autonomy and dignity rather than diminish it.”

The Ethics and Governance of Artificial Intelligence Fund will be governed by a small board, consisting of leadership from each participating foundation and institution. Ito says that convening all perspectives now is essential. “Instead of setting up an institution, we’ve decided to create a dynamic network. There are a number of areas where the deployment of machine learning is already starting to pose questions that are best answered in an interdisciplinary way. This project that we’re all embarking on is just the beginning.”

You might also enjoy the following articles about AI and AI/robotics policy:

• How artificial intelligence is changing our Christmas shop
• White House report: Artificial intelligence, automation, and the economy
• White House launches public workshops on AI issues
• White House releases reports focusing on opportunities and challenges of AI
• White House economic report looks to robotics for the future
• We the Geeks: Whitehouse hangouts celebrate robots, maker culture and more

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

A robot hands a medication bottle to a person. Photo credit: Keith Bujak. Source: Georgia Tech News Center

The Ethical, Legal and Social Aspects of Social Robots in Healthcare and Education Workshop (also called ELS Workshop) was held in Yokohama the 14^th Nov 2016 during the JSAI-isAI Conference. The workshop was twinned with another workshop in the New Friends Conference in Barcelona the 2^nd Nov 2016.

The workshop aimed at addressing the concerns that the use of social robots in therapy end education pose in the legal, ethical and societal (ELS) domain in a constructive and proactive manner. The workshop undertook ELS challenges that arise from the introduction of robots in therapy and education. A booklet is available to anyone who wishes to find out more, and can be found here.

The ELS Workshop first dealt with aspects of human dignity and the questions of how social robots might endanger an individual’s dignity, for example, by implying an overly simplistic model of human agency or by discriminating against certain demographics. Secondly, the workshop revolved around the topic of privacy. Third, the topic of liability was addressed.

These three overarching ELS issues – dignity, privacy, and liability – were discussed in an open discussion workshop format. The workshop focussed on defining the benefits, conflicts, and possible solutions to the conflicts that such new technologies pose. Researchers from all disciplines, as well as practitioners, actively engaged in the discussions – in particular, those participants who submitted an abstract for the workshop.

Here follows a summery of the issues raised by, and findings of the workshop.

Challenges and issues of social robots in therapy and education

• Public participation: Users are not taken into account during the design process of the robot and that is why “user-centered” design is, at the current stage, not a true statement.
• Public awareness: Connected with the user-centered idea, citizens opinion is not taken into account during the policy-making process. At the same time, however, it seems that people do not read the government website and are not very engaged with the government. Some participants mentioned that in Korea individual privacy is not perceived to have much value and that the government does not promote public awareness concerning it.
• Public security: It was explained in the workshop that in Korea there are lots of security issues in the country, and a case concerning a data leak was explained. If the proliferation of robots in the marketplace is to increase, it will be crucial to address all the security issues, especially if elderly and disabled people are involved.
• Privacy postmortem: Should informed consent include privacy after the death of the person?
• Legal management: The case of the Henna Hotel was introduced as an example of how robotic technology is already in the market. While the industry has already taken steps towards the introduction of robotic technology to the market, there has been no legal accompaniment, especially in the case of educational and therapeutic robots.
• Standards: Due to the lack of this legal management, it is not very clear what standards apply to educational and therapeutic robots. They simply do not exist in the industry.
• Legal uncertainty: Unless there is a problem, it seems that the Law is not providing any pro-active measure towards how to ensure a correct design/use of robot technology.
• Immigrant discrimination: Japan is investing in robotic technology instead of hiring foreigners due to language difficulties as well as cultural differences. Elderly prefer to be treated by Japanese caregivers or by robot technology rather than by immigrants.
• Employment of robot technology: The immigrant discriminatory scenario is aggravated by the low wages Japanese caregivers receive.
• Dehumanizing practice: In Japan, it is normally the daughter or the daughter-in-law that takes care of the mother/grandmother. Dehumanizing the practice of care could bring more free time to the caregiver (that is in this case a relative) but could bring about the decrease of human-human interaction from the care-receiver side.
• Multiple legislations: There is an urgent need to address the ELS issues if this robotic technology is going to be shipped all over the world. Compliance with each national legislation will bring about many conflicts that challenge the insertion of these robots to the market.
• Multiple robots: Each robot is different and the context where they are inserted too. Therefore, it is difficult to standardize case-by-case scenarios.
• Substitution of humans: Some of the participants wondered why humans need to surrender to the robot taking-over scenario. and who is in charge of deciding this. This brought about the following issue: technology is not people-driven.
• Robot obligations: If academia is talking about the possibility of providing robot rights, this highlights the importance of also deciding obligations.
• Unexpected consequences: Some of the robots that are entering the market have not been tested in real contexts and unexpected consequences can easily arise.
• Agency: connected with the unexpected consequences, it is not very clear whether the agency comes from the context, or if the agency comes from the designers. Who is entitled to decide the agency of their robot?
• New agency: The literature has been comparing robots to animals, corporations and other things… should the robot be considered a new kind of agent?
• Religion: Agency is perceived differently depending on the religion. Some comments on how inanimate things have spirit were highlighted, as well as how Hinduism also welcomes low-agency objects to be important, e.g. a book cannot be touched by the feet. What is not clear is whether this is a problem of religion or the individual.
• Human behavior: An experiment in Japan found resulted in children beating a robot in a mall. This experiment was explained in the workshop in order to avoid the replica of the behavior in the human-robot interaction.
• Education: Not a lot of schools have access to robotic technology, although it seems to be important to educate the population on the correct use of robotics technology.
• New law: do robots challenge the legal system in a different manner than other agents do?

Addressing the Challenges / Finding Solutions

• Legal certainty: it is important to have knowledge about domestic laws. A concept similar to “regulation by design” should be implemented.
• Regulatory prohibition: Depending on the use of robots we should ban the producing of robots to avoid unfortunate scenarios. The majority agreed that military robots should be banned.
• Public participation: the creation of a random jury, as we have in the legal system, could help on the participation of the general public on the decision-making process, as well as on the design of the robot technology. Some information and materials could be given to the citizens and they could provide their feedback.
• Employment of technology: increasing the salary of the workers could make the caregiver profession more attractive and increase efficiency. Working less hours can also increase efficiency although it is not clear how it could be modeled with care professions.
• Unexpected consequences: If we could predict and model an agent’s behavior then we could avoid unexpected consequences. Building robot strategies within the robot itself could also be of help.
• Education: it seems very difficult to know how to teach creativity in Japan, where the system is based on memorization. Helping this could help the acceptance of robotic technology as well as promoting the active participation on the design process of the robots.
• Transparency: The robot should be able to show or explain how it is using personal data, in order to promote transparency and user awareness. The use of black boxes could provide more information on the robot usage. It is not clear, however, what extent the government should have access to it.
• Regulated-by-design: This hybrid regulatory model should be embedded into the system to avoid any violations with domestic and international laws.
• Pro-activity: The system of Tokku in Japan should be spread all over the world in order to have Testing Zones for regulatory purposes.
• Regulatory model: we need a hybrid model that can cope with robotic technologies as well as with other technologies, as the delivery of legal counseling is changing rapidly – from having divorce apps to chatbots that deal with parking tickets.
• Regulatory model: connected to this idea, each project that involves robotic technology could be designed in a way that knowledge can be extracted from it for policy purposes.
• Case-by-case: the regulatory model should be created in a way that can cope with the particular needs of every robot and every context where this is inserted, as not all the robots possess the same degree of intelligence or the same capabilities.
• Robot Agency: the creation of an agency that deals with robots as it occurs in Japan could help having better management of all the ELS issues.
• Open international discussions: there is the need to open the debate to more people and to more countries.
• Replacing humans: robots should be conceived as helpers of the humans not a replacement of them.
• Clarity on the capabilities classification could bring about intelligibility on what is/should be permitted and what should not.
• This clarity relates also to the vision and expectations of the different countries on robotic technology, e.g. international future robotic trends.
• Decision-making of the robot: in the case of an accident, everyone could be assigned different values/importance in order the robot to choose the best target. This could raise discrimination issues at the same time.
• Harmonization: There is the need to harmonize what impact means, what is risk, and what are the legal issues concerning this type of robotic technology. There is also the need to have a common understanding.
• Alternative solutions: if the technology allows, the robot should be privacy friendly using other technologies, e.g. removing the cameras in the case of drones; or using vibrations of the floor to know that the patient has fallen.
• Privacy: a system similar to the noise that cameras in Korea make when they take a picture could be adopted in order to spread awareness among the users. The problem with this solution is that there are available apps that allow users to take a picture without making noise.
• Ethics could be addressed by common sense rules, although common sense varies between countries and individuals.
• The creation of a data bank for scientific innovations could help avoiding the non authorized uses of data.
• An international expert committee could be created to draft group reports

Main Issues (Recurring Topics)

• Regulatory model: There are no clear rules on the use of robotic technology in therapy and education. Law is not pragmatic.
• All the parties want to avoid responsibility of harm occurrence
• Growing need of the importance of ELS issues when the human-robot interaction involves vulnerable parts of the society.
• Solutions: each solution can bring about negative consequences. Therefore, an analysis of all the pros and cons will have to be made in order to mitigate any risk posed by the solutions
• The future of work (involving the promotions of co-working spaces)
• Third uses of data (involving privacy post mortem)
• The need for an international set of rules and basic principles.
• Robots will change the way we conceive this world.

Future Steps

• The legal system needs to
  • be disrupted
  • be pro-active
  • be dynamic
  • be more accessible
• There is the need to run more ELS workshops in different countries with different target participants: industry, laymen, legal scholars, etc.
• A great effort has to be done in order to change how people learn as everything is converging in this world. The term people in this case involves any person from any age.
• There is the need to share the knowledge on robotic technology among legal scholars.
• A clear classification on the capabilities of robots (educational, therapeutic) could be of help.
• There is the need to speak with main organizations, e.g. WTO, about this topic.
• We do need an international legal framework that can cope with all these ELS issues in the use of robotic technology, especially if they work with vulnerable parts of the society.
• There should be placed the idea that robotic technology are a supplement of the human’s work

Sophisticated household robots are only just starting to show up in our lives, but all the building blocks for a veritable “Cambrian explosion” of robotics are there, as Gill Pratt described it when he was running the recent DARPA Robotics Challenge. The service robotics industry is emerging, and we will soon be seeing robots of all shapes and sizes making their first forays into our everyday lives.

This is borne out by the recent explosion in robotics and AI funding, which saw robotics investments increase  exponentially over the last five years. While approximately $1 billion was invested in robotics between 2009 and 2014, roughly the same amount was invested in 2015 alone and 2016 is on track to double the total investment again.

According to the CBInsights October 2016 report into “The State of Enterprise: Robotics”, these new investments are largely clustered in autonomous vehicles and the service robotics industry, with strong growth noted in enterprise focused robotics companies.

“Over 50 enterprise-focused robotics companies have raised $259M across 63 deals this year (as of 10/5/2016). These companies are building robots for industrial automation, manufacturing, warehouse automation, and restaurant services, among other tasks.

At the current run-rate, deals to enterprise robotics startups are projected to cross 80 this year, beating last year’s record of 73.

Figure from CB Insights blog “Robotics Startups Funding”

As few as five years ago, the robotics landscape looked simple. While drone and autonomous vehicle technologies were beginning to emerge and cause some excitement, most of the robotics industry was industrial, and the remainder of the landscape was comparatively arid and boring: a few hospital robots, some robot vacuum cleaners, and a few toys and educational robots.

The emergence of the service robotics industry as a serious economic force has taken many people by surprise. It has also made it more difficult to make sense of the robotics landscape, particularly because the new service robotics businesses impact so many markets and applications, making categorization and statistics difficult to obtain, and trends hard to analyze.

Source: Yahoo Finance.

The impact of the internet on the retail sector is a marked example. The demise of physical retail has been hyped since the first dot com bubble, and perhaps this hype has lulled us into a false sense of security. But the huge decline in value of most major US retailers over the past decade is simply shocking. At the same time, robotics offers a potential solution to the pending economic disaster that is threatening the bricks and mortar retail industry. Early signs indicate that robotics is bringing manufacturing back to the US, enabling small batch, just-in-time production in a range of areas from automotive to electronics to biomedical.

Now it seems service robotics solutions in the retail and consumer spaces are offering new ways for brick and mortar companies to likewise maintain their competitive edge. And helping to shape these solutions are a number of Silicon Valley startups featured in this report: Catalia Health, Cleverpet, Bossa Nova, Fetch Robotics, Savioke, Marble, Dispatch, Dishcraft, Momentum Machines, Eatsa, Fellow Robots and Simbe. Indeed, Silicon Valley is at the epicenter of emerging service robotics industry.

Since 2010 Silicon Valley Robotics has been tracking early stage robotics startups and supporting them as they grow. Many of these companies are creating fundamentally new interactions and products, and as they do so, are leveraging the latest business model concepts, including various twists on “Robots as a Service” and “cloud robotics”. With so much new ground being broken, we saw a need to share their stories so that the industry as a whole can learn and grow, too.

Our first report on “Service Robotics Case Studies in Silicon Valley 2015” looked at enterprise robotics companies like Fetch Robotics, Adept, Fellow Robots, and Savioke, who occupied the space between backroom logistics and front-of-house customer service.

The new “Service Robotics Case Studies in Silicon Valley 2016” takes a deeper dive to explore how robotics companies are driving changes in how we interact — not just with technology — but with our pets, our health care providers, and our retail experience.

1. CleverPet (B2C) >> changing how people interact with their pets and delivering data-driven interactions at the far end of the spectrum of the new behavioral robotics.
2. Catalia Health (B2B2C) >> changing how people interact with their medication and life choices, but also how healthcare providers interact with patients >> intelligence built in by experts; allowing for smarter, data-driven interactions.
3. Simbe (B2B) >> allowing retail managers to interact more efficiently with their stock

A clear theme is that each of these robotics startups can unlock data-driven insights with potentially enormous additional business upside by leveraging the ubiquitous connectivity that is being made possible by cloud computing, and more specifically, cloud robotics. Emerging cloud robotics technology enables far more than the simple ability to continuously update and upgrade a physical product, or even to augment the intelligence of that product; it allows robots to become active mobile big data collectors.

Another important theme is how the RaaS or “Robots as a Service” model is maturing, with a range of transactions and applications (e.g. commission-based vs rental-based etc.) to complement the roll out of cloud robotics. Robots are no longer being marketed as simple products for sale, but as sophisticated tools for gaining insights and creating value and driving customer change.

Our second set of case studies and commentaries looks at how accelerators and investors are supporting the drive towards RaaS and finding business models that map robotics technologies into existing business structures, in areas ranging from health to consumer, hospitality to retail.

1. HAX >> helping startups focus on business models via programs like HAX Boost
2. Lemnos Labs >> seeing opportunities for RaaS, working with startups on developing their business plan
3. Comet Labs >> analyzing how intelligent machines can reimagine retail from logistics to customer experience

Every case study and commentary in this report underscores the fundamental importance (and reliance) of human-robot interaction to the service robotics business model — a trend that is sure define the industry well into the future. With so many ‘humans in the loop’ it will become critical that we design robots and businesses that set a high bar for safety, privacy, and ethics. For this reason, we are pleased to announce that Silicon Valley Robotics has just launched a “Good Robot Design Council” with industry expert advisers in an effort to develop design guidelines for the robotics industry that can help fill the ethical gap between standards and laws.

To that same end, our next service robotics reports will focus on self-driving vehicles, agriculture, and other ‘niche’ verticals, with an emphasis on the increasing importance of human-robot interaction, and a look at which aspects of design make good robots and successful businesses.

If you enjoyed this article, you may also enjoy:

• Why are some social robots selling well, whilst others are stalled or failing?
• Robots may save the global economy
• The rise of China’s medical robots sector
• Robots at your service: Empowering healthy aging at European Robotics Week, 2016
• Robot co-workers in the operating room

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Having been involved in roboethics for some years, I was delighted when the IEEE launched its initiative on Ethical Considerations in AI and Autonomous Systems, early this year. Especially so because of the reach and traction that the IEEE has internationally. (Up until now most ethics initiatives have been national efforts – with the notable exception of the 2006 EURON roboethics roadmap.)

Even better, this is an initiative of the IEEE standards association – the very same that gave the world Wi-Fi (aka IEEE 802.11) 19 years ago. So when I was asked to get involved I jumped at the chance and became co-chair of the General Principles committee. I found myself in good company; many great people I knew but more I did not, and it was a real pleasure when we met face to face in The Hague at the end of August.

Most of our meetings were conducted by phone and it was a very demanding timetable. From nothing to our first publication: Ethically Aligned Design a few days ago is a remarkable achievement, which I think wouldn’t have happened without the extraordinary energy and enthusiasm of the initiative’s executive director John Havens.

I’m not going to describe what’s in that document here; instead I hope you will read it – and return comments. This document is not set in stone, it is – in the best traditions of the RFCs which defined the Internet – a Request for Input

But there are a couple of aspects I will highlight. Like its modest but influential predecessor, the EPSRC/AHRC principles of robotics, the IEEE initiative is hugely multi-disciplinary. It draws heavily from industry and academia, and includes philosophers, ethicists, lawyers, social scientists – as well as engineers and computer scientists – and significantly a number of diplomats and representatives from transnational bodies like the United Nations, US state department and the WEF. This is so important – if the work of this initiative is to make a difference it will need influential advocates. Equally important is that this is not a group dominated by old white men. There are plenty of those for sure, but I reckoned 40% women (should be 50% though!) and plenty of post-docs and PhD students too.

Equally important, the work is open. The publications are released under the creative commons licence. Likewise active membership is open. If you care about the issues and think you could contribute to one or more of the committees – or even if you think there’s a whole area of concern missing that needs to a new committee – get in touch!

In this episode, Christina Brester interviews Vladimir Stanovov, PhD student and researcher at the Siberian State Aerospace University (Krasnoyarsk, Russia). Stanovov speaks about a speech-controlled wheelchair, which seeks to provide people that are quadriplegic, that is people with partial or total loss of use of their limbs and torso, with the possibility to control their wheelchairs through voice commands. In this interview Stanovov discusses the basic parts of the speech-controlled wheelchair, the fuzzy controller he created, and the trials they had in the medical center.

Below is a video that explains the speech-controlled wheelchair.

Vladimir Stanovov

Vladimir Stanovov received his Bachelor’s (2012) and Master’s (2014) degree at the Siberian State Aerospace University (SibSAU) in Krasnoyarsk, Russia. Stanovov is currently a PhD student in Computer Science and Engineering at SibSAU, where he performs the research under the supervision of Professor Semenkin. Stanovov’s PhD thesis is about evolutionary algorithms, fuzzy logic and their applications in machine learning.

Links:

• Download mp3 (11.6 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Vladimir Stanovov on reserchgate.net

The concept One Being for Two Origins, from the teachings of Buddha, considers the unification of technology, nature, and human beings. It emerges from the theory of the three aspects: The values of the “Good”, the “Bad”, and “Muki” (Avyakata). The theory of One Being for Two Origins follows the theory of the three aspects and explains a mechanism for how values, such as the good and the bad, emerge in reality using the three aspects. The theory has a contradictory structure, hence it can be difficult for those with a scientific background to fully comprehend it. In this interview, Nagoya University’s Associate Professor Hiroko Kamide shares with us her insights on robot ethics, with a focus on One Being for Two Origins.

Date: December 5^th 2016

Interviewee: Prof. Hiroko Kamide, Designated Associate Professor, Nagoya University, Japan

Interviewer: Dr. Yueh-Hsuan Weng, Co-founder of ROBOLAW.ASIA and Fellow at CLAST AI & Law Research Committee (Beijing) and Tech and Law Center (Milan)

Q1 WENG: Thank you for agreeing to an interview with us. Can you tell us a little about yourself and your background?

KAMIDE: My background is social psychology. During my doctoral course, I studied close relationships and well-being. After receiving my PhD, I started researching human-robot interaction and collaborated with engineers to help realize so-called “human-friendly robots”. We established psychological methods to evaluate humanoids, and subsequently developed human-friendly behaviors for robots. I still collaborate with engineers to consider the adaptive way of introducing advanced technology, such as robots and self-driving cars, from an interdisciplinary approach.

 Q2 WENG: Currently you are also in charge of a special interest group on robots and philosophy at The Robotics of Japan (RSJ). Can you tell us something about your RSJ Special Interest Group on Philosophy in Robotics?

KAMIDE: In the RSJ group, we discuss the approach to  technology from an interdisciplinary standpoint. The members are from psychology, philosophy, law, sociology, and engineering. Psychological evaluation, like technological advancement, is important to realize robots that your average person can accept in their daily-life. This collaborative work between psychology and engineering is crucial to developing technologies that can satisfy a human’s needs and expectations. But sometimes we experience terrible events that we cannot control: nuclear accidents, wrongful use of robots, etc. Therefore we started to investigate what the appropriate approach is when implementing and dealing with the cutting-edge technology. It’s a the responsibility of researchers to convey information to ordinary users about how we should deal with technology in order to maintain harmony between technology, nature, and humans.

Q3 WENG: What is the theory One Being for Two Origins? Why is it important to the unification of humanity and nature?

KAMIDE: The theory of One Being for Two Origins has a contradictory structure, and it’s difficult for those with a scientific background to fully understand. At the first step, we begin with a theory of values—the theory of the three aspects—as an introduction to the theory of One Being for Two Origins. The theory of three aspects explains the mechanism of how values, such as good and bad, emerge from the three concepts of the good, the bad, and the “Muki”. Then the theory of One Being for Two Origins follows the theory of three aspects as the fundamental mechanism of order. Through the theory of One Being for Two Origins, we become able to recognize the truth and biases behind language, and as such can avoid conflicts between technology, nature and human-beings.

Q4 WENG: Your paper “One Being for Two Origins – A necessary awakening for the future of robotics” has been presented at the 2016 IEEE ARSO Workshop in Shanghai, China. The co-author is Professor Masahiro Mori, who is a world famous roboticist because of his “uncanny valley” theory. How come you decided to choose this topic? Does the concept One Being for Two Origins have any relationship with “uncanny valley”?

KAMIDE: His theory of uncanny valley has a very thoughtful and groundbreaking perspective, therefore many researchers in the world still refer to his theory. As for my impression, he developed a very clear sense of perspectives that leads us to understand the theory of uncanny valley. His method of observing the truth of the world is in line with the teachings of the Buddha.

Q5 WENG: Regarding regulation for robotics, you pointed out that there is widespread misunderstanding from regulators. What is the misunderstanding? What kind of legal crisis will materialize if they don’t change their way of thinking? How can your proposed theory help solve this legal crisis?

KAMIDE: As the theory of three aspects explains, the value of good and bad are just derived from Muki, that transcends such values and is a true quality of the technology. Useful technology is positive. On the other hand, it would be bad if technology harms people. Technology is fundamentally neither good nor bad. It’s the manner in which technology is applied and operated by humans that is either good or bad. It is humans themselves that attribute these aspects to the technology.

Regulations are attempts to eliminate the bad aspects of technology. However, it is not correct to assume that only the good remains when the bad is eliminated, because technologies themselves are the Muki. And if bad did not exist, good would not exist either, as one is parasitic on the other. To eliminate the bad is to interfere in the working of the Muki in producing these values. The same occurs robots.

Our mindset determines how we approaches the Muki. If we are not mentally prepared, Muki will transform into bad. If we are mentally prepared, we can treat the Muki as good. Bad can transform into good then, of course, good can also transform into bad. And the more good qualities a robot possesses, the stronger its bad qualities will be, following the transformation. Sharp scalpels save lives, but sharp daggers kill people. This is because the working of the Muki is powerful.

In all cases, the mindset of humans is crucial. So, the responsibility of us in robotics is to ensure that technology is not used in bad ways. We must both establish methods of using robots, and work to refine users’ mindsets.

Q6 WENG: Robotics is like a double-edged sword, it can either help or kill people. Robotic lethal weapons present a dilemma. Should they be banned or not? Do you have any comment on this?

KAMIDE: The problem is not in robotics but in ourselves—we who raise such dualistic questions. As I mentioned, the technology of robotics doesn’t have any values. Robotics is not double edged sword at all; our minds are double edged. People easily attribute these values to the physical entity but it is not true. We have to try and observe the fact that we see not what we see, but what we want to see.

Q7 WENG: Do you agree with using dualism as the meta-principle to teach robots right from wrong? If not, do you think it is possible to adopt your theory into creating ethical robots’?

KAMIDE: The “right” and “wrong” is always in the eye of the beholder, and there are no absolute standards. As long as humans accept that they are subject to subjective mechanisms of perceiving the world, it won’t be troublesome to develop ethical robots. But if humans see the “right” and “wrong” as existing independently, objective, it will be definitely problematic.

Q8 WENG: What are major challenges for implementing One Being for Two Origins into robot ethics?

KAMIDE: Clarifying the importance of applying wisdom, not just knowledge. In this theory, knowledge refers to the ability to divide the phenomena into detailed classifications in order to understand the difference between things. On the other hand, wisdom is necessary to discover the meaning in the different things. Knowledge is developed through education, usually, but wisdom is not taught explicitly. Therefore, we are accustomed to dualistic thinking based on knowledge, that divides the world into its constituent parts, but we have difficulty uniting the parts using wisdom, in a way of monism. This is one of reason that we often raise dualistic questions, and eventually develop conflicts.

Q9 WENG: Professor Shigeo Hirose gave an insight called “Morality Engineering” in his short review “A Dialog on Robots” Vol. 7, No. 4, JRSJ. Do you think that One Being for Two Origins might be helpful in implementing his proposal of “Morality Engineering”?

KAMIDE: His article is very interesting. Opinions from both sides who are optimistic or pessimistic to a robotized future society are quite realistic and thoughtful. Recently many philosophers have started to think about morality in robotics. His “Morality Engineering” suggests implementing “rational egoism”, and I agree with the importance of this approach. One Being for Two Origins is the methodology to transcendent and unify opposite aspects of the phenomena to see the truth. So it is helpful to consider how “rational egoism” truly functions in the interactions between humans and robots.

Click here to read Hiroko Kamide’s paper “One being for two origins — A necessary awakening for the future of robotics”.

If you enjoyed this article, you may also also enjoy:

• Considering robot care, ethics & future tech at #ERW2016 European Robotics Week
• On the ethics of research in robotics, with Raja Chatila
• A European perspective on robot law: Interview with Mady Delvaux-Stehres
• Open Roboethics initiative delivers statement to United Nations CCW

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Amazon’s Echo sales have exceeded 4 million and they are ramping up to sell 10 million in 2017; Google’s Home has received positive reviews and have just begun selling in large numbers; but SoftBank’s Pepper and Cynthia Breazeal’s Jibo have either failed or are stalled. Why?

The bots: Amazon Echo Alexa vs. Google Home

Amazon’s success with Echo has revealed a consumer acceptance of voice-controlled devices housing virtual digital assistants. Xiaoice, a Microsoft Chinese language bot, has millions of users and can identify photos and carry on playful discussions as if it were a real person. Xiaoice’s acceptance has confirmed that there is a broad user base for these types of bots. What Alexa proved is that there is a growing market of people willing to engage with internet services at home without a screen. That transition, to voice interactions and artificial intelligence, could be a predictor of what’s to come in the near future. Alexa doesn’t need Google. People talk to it and ask it about the weather or recipe ingredients; it looks up things to buy. They search with it. Wait! They search with their Alexa Echo? Google has spent years building intelligent voice assistants for phone and tablets, and now suddenly here’s Amazon  stealing its thunder. Hence the newly launched Google Home

Forbes recently compared Amazon’s $179 Echo to Google’s $129 Home:

“Amazon Echo has a ring of LED lights that tell the user when it’s listening and when it’s processing a request. Users can rotate the top of the device to control volume. There are two buttons on top of Echo: First is an action button for turning off a timer or alarm, or waking up the device for voice commands; the second is a mute button that turns the microphone off so it’s not listening.

Google Home has four colorful LED lights sitting on top that tell the user when it’s listening. It also has a bit more options for physical input: the top of the speaker has a touch surface for playing or pausing audio; changing volume; or starting requests. Like Echo, there is also a mute button.

Amazon Echo is powered by Amazon’s voice assistant, Alexa. Echo wakes up to the word “Alexa” to begin taking your commands. Right off the bat, the device makes it easy to set timers or alerts, ask what the weather is, play music. Echo users can manage all the settings and features in an Alexa app. The app is also where users can enable and browse through so-called Skills — Amazon’s version of an Alexa app.

Google Home is running on Assistant, which is Google’s latest version of its virtual assistant for responding to users’ requests in a conversational manner. Users trigger Google Home with “OK, Google” or “Hey, Google” to start controlling it. It’s able to do the usual — set timers, tell the weather, play a song. But because Google has a lot of information on its users with access to calendars and emails, it can get to know users a lot more intimately than Amazon can right now.

Another important aspect of these two devices is how well they work as a platform for third-parties services and devices. Amazon’s Alexa has more than 3,000 “skills” and can do everything from summoning an Uber to ordering a pizza to turning up the temperature. Google is also creating a specialized developer kit with apps being called “Actions,” and which are separated into two types: Direct Actions and Conversational Actions. Direct Actions are for the kind of tasks that are straight forward — like turn on a light, or play a song on Spotify. Conversational Actions are for a bit more complicated requests like ordering an Uber, where there needs to be some back and forth happening — it needs to know where you want to go and what level of Uber service.”

Amazon’s Echo doesn’t sell in China. Nor does Google’s Home. Here are a few other bots, two of which sell in China:

JD.com, China’s largest online direct sales company, sells a similar product to the Echo and Home devices: the DingDong Smart Speaker. The DingDong Smart Speaker uses the JD+ super app (called “Jingdong Weilian”) to allow full voice control of all products in the JD+ ecosystem.

Baidu, the Chinese telcom giant, is selling Duer, a conversational virtual assistant service. The assistant service provides quick and easy access to Baidu’s various Internet services and engages in a dialogue with users rather than simply being voice-controlled.

Fabriq, a French startup, is a speaker device that sells for $50 and uses Amazon’s own Alexa functionality. With almost all of Alexa’s smarts — everything from music and news to third-party skills, smart home control, and jokes — Fabriq offers plenty of tech appeal in an attractive little package.

“C|Net said: “Fabriq proved to be a capable Alexa gadget. It did a nice job understanding my voice commands, and though it sometimes needed to think a second or two longer than the Echo before pulling up a song I had requested, I came away satisfied with the user-friendly smarts. At just $50, it shows a lot of promise.”

The mobile social companions: Pepper and Jibo

Two notable social robotic ventures are having a different experience than Amazon and Google:

1.   Although SoftBank has sold slightly more than 7,000 Pepper robots to consumers and businesses in Japan and France and still plans to launch in Taiwan, China and the U.S. very soon, their emotion engine – Pepper’s main selling point – will be turned off.

“I’m not sure that being able to read emotions can add to service,” said Morten Paulsen, who covers industrial automation giant Fanuc Corp. as head of Japan research at CLSA Asia-Pacific Markets. “There are several Peppers in my office building, but I don’t see anyone gathering around them anymore. They are basically animated iPads.”

Many people have reported seeing Peppers idle and in corners instead of out front greeting and interacting with people.

2.    Jibo, the much-publicized first product from social robotics pioneer and MIT professor Cynthia Braezeal, has had a series of setbacks and delays including having to refund all non-English-speaking Jibo orders and most recently having to split their initial deliveries into Beta or hold-til-later groups (I’m in the latter). Beta’s are being delivered now so we’ll soon hear from the community how well it performs and meets expectations.

Many other mobile robots have been announced but haven’t come to market just yet. Asus’ Zenbo, at $599, is quite interesting; Buddy from Blue Frog Robotics seems to have run out of money after it got panned in an MIT Technology article; and Future Robots FURo is selling in small numbers as mobile information kiosks.

Bottom line

Can it be that consumers don’t care as much about the mobility aspect as they do about price and conversational interaction? Or is it mismanagement problem, as Bloomberg reporters Pavel Alpeyev and Takashi Amano suggest in their BloombergTechnology report on Pepper and SoftBank?

SOCIAL ROBOTICS JAPAN is adapted from a bimonthly column published in Japan’s Nikkan Kogyo Shimbun (日刊工業新聞/Business & Technology Daily Newspaper). The 101-year-old, nationally circulated newspaper is a co-organizer of the iREX International Robot Exhibition and its biennial alternate, Japan Robot Week. The column’s generalist, socio-technological perspective aims to encourage both domestic and international conversation around developments in Japanese robotics.

A deep, largely monocultural history combined with a highly contextual language and society present fascinating but considerable challenges for expatriates who call Japan home. Understanding and appreciating Japanese entertainment is one of the tallest hurdles, and Japanese anime is a perfect example. There are, of course, legions of non-Japanese anime fans around the world, but just as many find it quite impenetrable; we recently discovered a robotics-focused promotional piece that seemed yet another difficult example…at first. The feature, Robot Town Sagami 2028, sponsored by Kanagawa Prefecture’s namesake campaign, turned out to be a very pleasant surprise.

Created by Tezuka Productions, the short anime opens with the exuberant celebration of a man who just learned that he’d become a father. At the height of his excitement, however, tragedy strikes. Hospitalized in critical condition, the man finds himself floating above his comatose body, overhearing a grim diagnosis. Suddenly, a very familiar robot boy appears and transports him to an impressive but simultaneously tragic future: his wife and child, surrounded by helpful robots and an array of technological advancements, appear to be living very happily without him. This is the part where foreign audiences can easily get lost in what seems an odd, disjointed, and relative to the nature of the promotional campaign, unnecessarily melancholic narrative.

Now, we won’t spoil the reason why, but we will say that anyone who watches through to the end will find a touching message that’s universally relatable in any culture. Although the setup is a bit disturbing, it ends up being fantastic storytelling, with a hopeful and heartwarming finale, imagining a not too distant future that many predict will become reality: a brave new Japanese economy where robotics and IOT technologies are embedded in everyday life – and that life is very good.

The bilingual version of Robot Town Sagami 2028 is embedded below, and Japanese or not, fan of anime or not, we think you’ll be glad you gave it a watch.

Desiderata:
The Robot Town Sagami organization is one of several municipality-wide, private and publicly funded robotics development and promotional ventures in Japan, some of which fall under a broad governmental initiative referred to as the “Robotic Technologies and Systems for Next-generation Social Infrastructures.” Other examples include Tsukuba Science City and nearby Cyberdyne, Inc.’s proposed Cybernic City (PDF).

For a sci-fi fan like me, fascinated by the nature of human intelligence and the possibility of building life-like robots, it’s always interesting to find a new angle on these questions. As a re-imagining of the original 1970s science fiction film set in a cowboy-themed, hyper-real adult theme park populated by robots that look and act like people, Westworld does not disappoint.

Westworld challenges us to consider the difference between being human and being a robot. From the beginning of this new serialisation on HBO we are confronted with scenes of graphic human-on-robot violence. But the robots in Westworld have more than just human-like physical bodies, they display emotion including extreme pain, they see and recognise each other’s suffering, they bleed and even die. What makes this acceptable, at least within Westworld’s narrative, is that they are just extremely life-like human simulations; while their behaviour is realistically automated, there is “nobody home”.

But from the start, this notion that a machine of such complexity is still merely a machine is undermined by constant reminders that they are also so much like us. The disturbing message, echoing that of previous sci-fi classics such as Blade Runner and AI, is that machines could one day be so close to human as to be indistinguishable – not just in intellect and appearance, but also in moral terms.

At the same time, by presenting an alternate view of the human condition through the technological mirror of life-like robots, Westworld causes us to reflect that we are perhaps also just sophisticated machines, albeit of a biological kind – an idea that has been forcefully argued by the philosopher Daniel Dennett.

The unfortunate robots in Westworld have, at least initially, no insight into their existential plight. They enter into each new day programmed with enthusiasm and hope, oblivious to its pre-scripted violence and tragedy. We may pity these automatons their fate – but how closely does this blinkered ignorance, belief in convenient fictions, and misguided presumption of agency resemble our own human predicament?

Westworld arrives at a time when people are already worried about the real-world impact of advances in robotics and artificial intelligence. Physicist Stephen Hawking and technologist Elon Musk are among the powerful and respected voices to have expressed concern about allowing the AI genie to escape the bottle. Westworld’s contribution to the expanding canon of science fiction dystopias will do nothing to quell such fears. Channelling Shakespeare’s King Lear, a malfunctioning robot warns us in chilling terms: “I shall have such revenges on you both. The things I will do, what they are, yet I know not. But they will be the terrors of the Earth.”

But against these voices are other distinguished experts trying to quell the panic. For Noam Chomsky, the intellectual godfather of modern AI, all talk of matching human intelligence in the foreseeable future remains fiction, not science. One of the world’s best-known roboticists, Rodney Brooks has called on us to relax: AI is just a tool, not a threat.

As a neuroscientist and roboticist, I agree that we are far from being able to replicate human intelligence in robot form. Our current systems are too simple, probably by several orders of magnitude. Building human-level AI is extremely hard; as Brooks says, we are just at the beginning of a very long road. But I see the path along which we are developing AI as one of symbiosis, in which we can use robots to benefit society and exploit advances in artificial intelligence to boost our own biological intelligence.

More than just a tool

Nevertheless, in recent years the robots and AI are “just tools” line of argument has begun to frustrate me. Partly because it has failed to calm the disquiet around AI, and partly because there are good reasons why these technologies are different from others in the past.

Even if robots are just tools, people will see them as more than that. It seems natural for people to respond to robots – even some of the more simple, non-human robots we have today – as though they have goals and intentions. It may be an innate tendency of our profoundly social human minds to see entities that act intelligently in this way. More importantly, people may see robots as having psychological properties such as the ability to experience suffering.

Being human is about more than just looking the part.

It may be difficult to persuade them to see otherwise, particularly if we continue to make robots more life-like. If so, we may have to adapt our ethical frameworks to take this into account. For instance, we might consider violence towards a robot as wrong, even though the suffering is imagined rather than real. Indeed, faced with violence towards a robot some people show this sort of ethical response spontaneously. We will have to deal with these issues as we learn to live with robots.

As AI and robot technology becomes more complex, robots may come to have interesting psychological properties that make them more than just tools. The fictional robots of Westworld are clearly in this category, but already real robots are being developed that have artificial drives and motivations, that are aware of their own bodies as distinct from the rest of the world, that are equipped with internal models of themselves and others as social entities, and that are able to think about their own past and future.

These are not properties that we find in drills and screwdrivers. They are embryonic psychological capacities that, so far, have only been found in living, sentient entities such as humans and animals. Stories such as Westworld remind us that as we progress toward ever more sophisticated AI, we should consider that this path might lead us both to machines that are more like us, and to seeing ourselves as more like machines.

This article was originally posted on The Conversation

If you enjoyed this article, you might also be interested in:

• The new Westworld: Humanizing the un-human, or dehumanizing humankind?
• Ex Machina: When Turing meets Bechdel test
• President Obama discusses artificial intelligence with Media Lab Director Joi Ito

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

HBO’s latest offering (on SkyAtlantic here in the UK) is an update of Michael Crichton‘s 1973 film Westworld; this time brought to us as a ten-part television series by sci-fi re-booter extraordinaire J.J. Abrams and screenwriter Jonathan Nolan (yes, brother and frequent collaborator of Christopher). The new Westworld comes with much hope (for HBO as a potential ‘new Game of Thrones’) and hype, understandably with the talent behind it having given us so much terrific science-fiction of late, including Star Wars: The Force Awakens and Interstellar.

As with Channel 4’s series Humans, broadcast last June (news on forthcoming series 2 here), Dreaming Robot’s offered a live Twitter commentary while the show was being broadcast in the UK, and I’ll take some time afterwards to write some reflective pieces on what we see in the show. (The Twitter ‘Superguide’ from @ShefRobotics can be seen here; my own @DreamingRobots Superguide can be seen here.)

Unsurprisingly, many of the themes in the Westworld reboot could also be seen in Humans. It seems, for example, that both shows express a certain anxiety, that as our machines become more human we humans seem to become less human, or humane. But this isn’t a new idea original to either show – this anxiety as been around as long as robots themselves, from the very invention of the term robot in the 1920s. And if we trace the history of robots in science fiction, we see a history of monsters that reflect this same fear, time and again, in slightly different contexts. Because the robot – which, remember, was invented in the popular imagination long before they were built in labs – is above all else exactly that, a perfect way of expressing this fear.

So, what are we looking at in this new, improved Westworld? (because frankly, the original film lacked the depth of even the first hour of this series, being just a very traditional Frankenstein narrative and rough draft for Crichton’s Jurassic Park, made 20 years later). First – as this nifty graphic on the right illustrates – we do see the robots in Westworld becoming more human. The programme starts with a voice asking the humanoid (very humanoid) robot, Dolores (Evan Rachel Wood), ‘Have you ever questioned the nature of your reality?’ The questioner is exploring whether Dolores has become sentient, that is, aware of her own existence. The echo here with Descartes is clear. We all know about cogito, ergo sum – I think, therefore I am. But Descartes proposition isn’t just about thinking, it is about doubt.  He begins with the proposition that the act of doubting itself means that we cannot doubt, at least, our existence . So we would better understand Descartes’s proposition as dubito, ergo cogito, ergo sum: I doubt, therefore I think, therefore I am. If Dolores is found to be questioning the nature of her reality then that would be evidence for self-awareness and being, according to the Cartesian model.

The robots in Westworld are depicted as falling in love, maintaining strong family bonds, appreciating beauty, and consider the world in philosophical, reflective contexts. How much of this is merely programming and how much exceeds the limits imposed upon them by their human masters is the key question that the show teases its audience with, I suspect, though certainly, it occupies much of our attention in the first few hours. But if these moments – described as ‘reveries’ – are in any way genuine moments of creativity, then this is another category, beyond the notion of the cogito, that we might say the robots are becoming ‘alive’.

For many thinkers in the second-half of the twentieth century (for example, the post-Freudian psychoanalyst D. W. Winnicott), it is only in such moments of creativity, or enjoying genuine moments of spontaneous being, that we truly discover the self and come alive. (The Freudian and post-Freudian influences on the narrative become even more apparent in subsequent episodes.) As response to late industrial capitalism (and the shock of fascism to the human self-conception as a rational animal), this idea emerged of human beings coming ‘alive’ only when we are not acting compliantly, that is, when we are acting spontaneously, or creatively, and not according to the laws or dictates (or ‘programming’) of another individual, organisation or group consciousness. We see this trend not only in a post-Freudian psychotherapy (e.g. Eric Fromm and the Frankfurt School, R. D. Laing) and other philosophical writings but also in the popular post-war subculture media, including advertising – the sort satirised in the ad for Westworld that opens the original film.

Other perspectives give us a glimpse into the robot’s moments of becoming human. Peter Abernathy, looking at a picture that offers a peek at the world outside, says: “I have a question, a question you’re not supposed to ask.” This is an allusion to Adam and Eve and the fruit of forbidden knowledge when humankind became self-aware of the difference between right and wrong. (Peter, after this, is consumed with rage at how he and his daughter have been treated.) And like Walter, the robot that goes on a psychotic killing spree, pouring milk over his victims, Peter is determined to ‘go off script’ and reclaim for himself a degree of agency and self-determination, acting according to his own, new-found consciousness instead of according to what others have programmed for him.

MEANWHILE, the human beings (‘newcomers’) in Westworld seem less ‘humane’ than their robot counterparts. The newcomers are shown to be sadistic, misogynist, psychopathic in the indulgence of their fantasies. One could argue that this behaviour is morally justifiable in the unreal world designed solely for the benefit of paying customers – that a ‘rape’, for example, in Westworld isn’t really ‘rape’ if it is done to a robot (who, by definition, cannot give nor deny consent), but this clearly is not how the audience is being invited to see these actions.

That human beings are becoming more like machines is an anxiety for which there is a long history of evidence, and even pre-dates the cultural invention of robots in the 1920s. We can see this anxiety in the Romantic unease with the consequences of Enlightenment that gave birth to the new, rational man, and of the industrial revolution, that was turning humans into nothing more than cogs in the steam-powered machines that so transformed the economy. This has been addressed in the Gothic tale of Frankenstein, still the basis for so many narratives involving robots, including the original Westworld film and, more recently, even our most contemporary stories such as Ex_Machina, and, to a lesser extent, in this manifestation of Westworld (which will be subject of a future post). (I have written and spoken on this theme myself many times, for example here and here).

So in Westworld, we meet Dr Ford – the mad scientist who creates the machines that will, inevitably, be freed upon the world. Dr Ford immediately reminds us of another Ford, the man whose name is synonymous with the assembly lines and a mode of production in the late industrial revolution that has done so much to dehumanise modern workforces. We see these methods of production and workers in the iconic film, which was contemporary with Henry Ford’s factories, Metropolis. (Though, as we shall see, this Ford is rather more complex…).

This dehumanisation of human beings in the industrial age has been looked at in robot films since Metropolis #Westworld pic.twitter.com/NkoBH7mlD2

— Dreaming Robots Blog (@DreamingRobots) October 4, 2016

This fear reflects, too, that as post-Enlightenment humans become more rational, they become more like machines, acting in predictable, programmed ways, having lost the spontaneity and creativity of an earlier age. The humans of Westworld are exaggerations of the humans of our ‘Western’ world of rationalism, science and alienation. We don’t have to agree with this Romantic notion, that rationalism and science are negative forces in our world to accept that there is a great deal of anxiety about how rationalism and science are transforming individual human beings and our societies.

Rational dehumanisation is something personified in the actions of the corporation, which has replaced the mad-scientist as the frequent villain of the sci-fi Frankenstein-robot-twist (more to come on this in a future post) and we see hints in Episode 1 of what is to follow in Westworld, along the lines of film’s such as 2013’s The Machine, where the slightly misguided and naive actions of a scientist are only made monstrous when appropriated by a thoroughly evil, inhumane military-industrial complex.

This theme to address so succinctly in Ridley Scott’s Blade Runner, a major influence on the new Westworld, where the Tyrell Corporation boasts that their replicants are More Human Than Human. And in Blade Runner, too, we see humanoid robots behaving more humanely that the people that ruthlessly, rationally hunt down the machines. It is unclear, however, from the Tyrell slogan whether the robots are more human than the human because the technology has become so sophisticated, or because humans have fallen so low.

On Westworld as a whole, it is too early to tell if it will maintain its initial promise and be as monumentally successful as Game of Thrones, or as iconic as Blade Runner. But already this first episode has given us more to think about than the original, and undoubtedly the success and failure of the programme will be instructive.

If you liked this post, you may also want to read:

• Robots can successfully imitate human motions in the operating room
• The dark side of ethical robots
• Law-abiding robots? What should the legal status of robots be?
• Beyond Asimov: how to plan for ethical robots

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

What would your ideal robot be like? One that can change nappies and tell bedtime stories to your child? Perhaps you’d prefer a butler that can polish silver and mix the perfect cocktail? Or maybe you’d prefer a companion that just happened to be a robot? Certainly, some see robots as a hypothetical future replacement for human carers. But a question roboticists are asking is: how human should these future robot companions be?

A companion robot is one that is capable of providing useful assistance in a socially acceptable manner. This means that a robot companion’s first goal is to assist humans. Robot companions are mainly developed to help people with special needs such as older people, autistic children or the disabled. They usually aim to help in a specific environment: a house, a care home or a hospital.

At the beginning of the 20th century, one of the first pieces of technology designed to help in a household environment was the vacuum cleaner. Since then, technology has transformed the home. Nowadays, we even have a robot that can cook. The chef robot was developed by Moley Robotics, a start-up company that won the 2015 Asia Consumer Electronics Show. The robot is said to be able to cook 2,000 different meals.

Pepper, the latest robot from Aldebaran Robotics, is a good example of a humanoid robot companion. It can provide assistance in making choices, detect human facial expressions and communicate with people. Pepper can adapt its behaviour depending on its perception of a person’s mood, and in this sense we can say that Pepper cares for people. At the moment, only research institutes and Japanese residents can acquire a Pepper robot. The robot costs around £8,710 for a Japanese customer.

Companion robots can take the form of pets, too. Paro is a robotic seal developed to provide comfort to old people. And rather than taking care of you, this robot has to be taken care of. It is how Paro provides emotional support.

Sometimes people get attached to robots that are not actually made for companionship. Take Roomba, for example, the intelligent vacuum cleaner. In their studies, Ja-Young Sung and colleagues from the Georgia Institute of Technology found that people wanted to become tidier in order to allow the vacuum cleaner to run smoothly.

Although many of these robots show some form of initiative and encourage people to interact with them, many are responsive rather than active – in other words, the robot waits for a human request before acting.

Should robots be more ‘human’?

Thanks to progress in Artificial Intelligence and technology, we can now develop more intelligent systems that are capable of acting very much like a human. Last year, a few of them were presented to the public, such as Nadine, the robot receptionist, Yangyang, the singer robot, and Aiko Chihira, the robot that can communicate in sign language.

https://www.youtube.com/watch?v=DydjzhZDdlg

Although the popular and controversial Turing test is used in AI to measure whether a machine is as intelligent as a human, it is a very different thing when it comes to robots, since robots are also expected to act intelligently. There is not yet a standardised test to determinate how human a robot is. It may come in the near future. However, all robotic researchers seem to agree that the robot would have to be able to show some social awareness and personality, and be capable of understanding and recognising people’s speech and expressions.

But do we want robots to have more personality and to be able to take more initiative? Ultimately, to act more like us? Some may argue, yes. If intelligent vacuum cleaners were able to differentiate a sleeping human from objects, for example, at least one unfortunate lady in South Korea wouldn’t have had her hair “eaten” by her new domestic appliance.

But others argue that it is dangerous to give robots too much intelligence. And would it allow them to answer back? We are still at the beginning of research regarding the potential consequences this might have. Indeed, the scientific community is still debating whether a robot can ever have feelings or be self-conscious. Although AI has been able to perform certain tasks extremely skillfully, for example Alpha Go, the community is still a long way from developing an AI which closely resembles the human mind.

https://www.youtube.com/watch?v=3N1Q8oFpX1Y

At present, robot companions are either focused on companionship or on task-execution. Jibo, for example, is a social robot that can talk, order food, remind you of things, or take pictures, while Roomba is an intelligent, but ultimately functional, vacuum cleaner.

Who is in charge?

But it’s about striking the right balance, depending on the job at hand and the person it is working for. Our most recent study, Who is in charge? Sense of control and Robot anxiety in Human Robot Interaction, showed that the more controlling and anxious about robots a person is, the more initiative they expect the robot to show and the more willing they are to delegate tasks to it. The research focused specifically on what level of initiative people preferred their robot companion to have when executing a cleaning task.

Participants could choose between manually turning on the cleaning robot themselves, having their robot companion turn on the cleaning robot remotely when instructed, or having the robot companion turn on the cleaning robot when it noticed that cleaning needed to be done. It was found that most people wanted their robot companion to execute the task without being asked.

This paradoxical result may be explained by the fact that people are now more used to technology – from computers and smartphones to smartwatches and intelligent home appliances – acting semi-autonomously. Smart companion robots are just the next step in the long evolution of our relationship with technology.

In the future, it is likely that we will see more domestic robot companions that can be customised to people’s individual preferences. And we will be able to shop for them as we now shop for vacuum cleaners and phones. Ultimately, it seems, there will be a robot for everyone.

This article was originally published on The Conversation. Read the original article.

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• Robots that may help you in your silver age
• Caring for robots: How assistive robotics may change our homes
• 2016 will be a pivotal year for social robots
• Architectural robots: The shape of the robots that will shape your home
• Japanese telcos vie for share in consumer robot-as-a-service business
• Robot caregivers: How much interaction with a robot is socially acceptable?
• Driven by care needs, will it be the booming senior population that spurs wider acceptance of robots?

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

In this episode, Audrow Nash interviews Fredrik Gustafsson, Professor in Sensor Informatics at Department of Electrical Engineering in Linköping University, about an initiative to reduce poaching in a rhino sanctuary in Ngulia, Kenya. Gustafsson discusses how he first became involved in this project, how he has worked with the rangers to develop solutions, and the future of this work.

Fredrik Gustafsson

Fredrik Gustafsson is professor in Sensor Informatics at the Department of Electrical Engineering, Linköping University, since 2005. He received the M.Sc. degree in electrical engineering 1988 and the Ph.D. degree in Automatic Control, 1992, both from Linköping University. His research interests are in stochastic signal processing, adaptive filtering and change detection, with applications to communication, vehicular, airborne, and audio systems. His work in the sensor fusion area involves design and implementation of nonlinear filtering algorithms for localization, navigation and tracking of all kind of platforms, including cars, aircraft, spacecraft, UAV’s, surface and underwater vessels, cell phones and film cameras for augmented reality. He is a co-founder of the companies NIRA Dynamics (automotive safety, including tire pressure monitoring systems found in more than 20 million, here), Softube (plug-ins for music studios and software solutions for Marshall and Fender), and Senionlab (leading manufacturer of indoor navigation solutions for sm, here).

Links:

• Download mp3 (16.9 MB)
• Project Ngulia website
• A PDF overview of Project Ngulia
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You might think that your job ad and hiring process is gender neutral and ‘may the best person win’. But years of studies have shown that it simply doesn’t work that way. With equal qualifications, women are still less likely to apply for the job and when they do, less likely to pass the subtle cultural fit requirements.

For the first time in history, women are now earning 50% of all degrees (in the US). But the bad news for robotics is that the Comp Sci and Engineering disciplines are still only attracting <20% of women. Seriously. It was actually better in the 1980s and we need to look at this in another post.

But the best universities have been proactive and are growing the numbers of women graduating in CompSci and Engineering, so you should be seeing a higher proportion of women job applicants. What does the gender ratio of resumes sent to your company look like?

I’m hearing a lot of robotics companies say that they’re having trouble getting women to apply. Well it isn’t rocket surgery but it does take some effort. Here are the best tactics.

Actions:

Is your workplace female friendly? What is the current ratio of women? Can you have women on your interviewing committee? Can you demonstrate why your company has a good culture for women. Is every image on your product/website/team male?

Even if you are starting from scratch, you can still sound female friendly. Ensure your hiring team is on board with this. Have you all considered how frequently unconscious bias happens and simple checks to balance it? (See some of the resources listed below.)

As Jessica Nordell wrote on Medium, “It’s why women are hired and promoted based on proof, while men are hired and promoted based on potential.”

Check your HR process. Is the ratio of women applying to equal to the ratio of women interviewing? Is the ratio of women interviewing equal to the ratio of women being employed? Sudden differences suggest a problem with your processes.

Check your tech interview style. Are you being needlessly combative or challenging? Invite people to show their work without time limits or trick questions. Make it friendly not competitive – unless you are interviewing for people to work in a hyper competitive workplace.

Check your job language. It’s easy to default to needlessly masculine language ie. using adjectives like ‘killer’ ‘rockstar’ ‘aggressive’. Textio is a service that analyzes the text and gives you suggestions for success. They started by evaluating crowdfund campaigns.

Invite women to apply. Explicitly invite applications from women and members of unrepresented groups.

Get word out to women. Increase the number of applications from women by submitting to communities, groups, boards for women.

Build a pipeline. Have regular women’s events, advisor days, office hours, breakfasts or network events. Mine the local colleges and universities. (Although the universities are getting tired of having the best and brightest hired away from research.)

Publicize success. Although it also speaks for itself. Some companies like Etsy, Facebook and Microsoft have significantly increased the number of women in their engineering teams.

ProTip. Mine the biosciences. There’s a lot of talent in adjacent fields.

Resources: (including lists of women engineer/coding groups/boards/communities)

Unconscious Bias
Suggestions and Lists
Language Feedback
Facebook’s Suite of Diversity Resources
Etsy Case Study
More Tips
Building a Pipeline

RoboJob Fair

We’re hosting a robotics job fair on May 11 in Silicon Valley.

These new robots — and the proliferation of mobile robot butlers, guides and kiosks — promise to recognize your voice and face, and help you plan your calendar, provide reminders, take pictures of special moments, text, call and videoconference, order fast food, keep watch on your house or office, read recipes, play games, read emotions and interact accordingly. The list goes on.

These products are attempting to be analogous to a sharp administrative assistant who knows your schedule, contacts and interests, and engages with you about them to help you stay informed, connected and active.

According to a research study by Tractica, annual shipments of consumer robots (a category that includes robotic vacuums, lawn mowers and pool cleaners as well as social robots) will increase from 6.6 million units in 2015 to 31.2 million units worldwide by 2020, with a cumulative total of nearly 100 million consumer robots shipped during that period.

Although robot vacuums will remain the largest segment of the market over the next several years, the fastest growth will occur in robotic personal assistants — a category that is nascent today. According to the report, “the next 5 years will set the stage for how these robots could fundamentally transform our homes and daily lives.”

As social and companion products come to market, they incorporate artificial intelligence from the past several years. Yet almost every day there are breakthroughs in learning systems that will soon be commercialized and incorporated into future personal devices. These AI improvements will enable ubiquitous robotic and robot-like personal assistants and companions. Consequently, today’s social robots are transition devices for early adopters  to scrutinize, play with, suggest improvements to, and talk about — which is why 2016 is a pivotal year. It’s the time when companies will sell enough units to learn whether their bots provide a real and lasting service, or if they are just a passing fancy.

These new products fall into three categories, and the primary ones (as determined by launch date and invested capital) are shown below:

Mobile devices

• For homes
  • Pepper, by SoftBank Robotics. A mobile humanoid robot that sells for $1,600 plus an additional $200 per month for Internet service, updates and maintenance. Only speaks Japanese and French at present but Chinese and English are planned for early 2016. Peppers are selling at a steady rate of 1,000 per month.
  • Buddy, from Paris-based Blue Frog Robotics. A squat little $649 device that whisks around on wheels and casters and will do many of the things Jibo will do. Buddy will begin shipping and selling in 2016.
• ​For offices, stores, hotels, public spaces and museums
  • SaviOne/Relay by SaviOak. A hospitality robot that autonomously navigates hotel hallways and elevators to deliver items to hotel guests.
  • Store assistants and guides – multiple vendors are beginning to provide mobile kiosks that can identify items and navigate to where they are stored.
  • Public guides and assistants answering common questions – for airports, museums, galleries, public spaces, and soon, restaurants, by multiple international vendors.
  • Special-purpose mobile bots such as
    • Budgee, a tote-carrying follow-me device that communicates through your phone, by Five Elements Robotics.
    • CaddyTrek, a follow-me golf-bag carrying mobility device from FTR Systems.

Tabletop assistants

• Jibo, the spin-out from the MIT Media Lab headed by Cynthia Breazeal. Twists and tilts and communicates like or better than Siri, initially only in English. Jibo will sell for $749, and connects to your home WiFi network. This recipient of more than $60 million in crowdfunds and equity investments, with $16 million in new funding that will be used to localize Jibo with language and apps for the Chinese and Japanese markets.
• Sota, by Japan’s largest telecom company, NTT, will sell for about $800, plus a monthly service of around $30. In addition to its ability to verbally communicate with the user, the robot can also assist the user with health functions by interacting with wearable devices to check blood pressure and heart rate.

Non-robotic home assistance devices

• ECHO by Amazon is a stationary voice-activated hands-free device that provides information, answers questions, plays music, reads the news, checks sports scores or the weather, and more.
• Rokid, by Chinese home automation company Rokid, will soon be introducing a stationary device with intelligent robot capabilities like omni-directional voice recognition using eight microphones, face recognition, and an ability to integrate into smart home automation systems.
• MJI (More Joyful Innovation), a cute egg-shaped communication device with a 5″ screen, is being geared towards the elderly and those that required communication assistance. MJI can send and receive messages and phone calls without requiring any manual input using voice activation. MJI will begin production and sales early in 2016.

In addition to the products mentioned, there are many, many other cute bots designed for children, STEM education, schools, therapists, disability centers, and academia. They are all worthwhile products, but unlike those listed above, they are not being built for mass consumer adoption.

Bottom line

At this year’s iREX Robot Expo in Tokyo and at the Beijing World Robotics Conference (both held last month) social, humanoid and mobile robots were the biggest crowd pleasers. Ten years ago PopSci reporter Tim Hornyak wrote “Loving the Machine” — a book about Asia’s long-time fascination with robots. His insights still appear to be true: the Japanese really do have an unusual affinity for human-like robotic things. This is why so much money is flowing to help these new social robots quickly adapt to the Chinese and Japanese language markets, and to provide localized apps from their software stores.

If you like this post, you may also be interested in:

• Case study shows new roles for robots in today’s economy
• IFR predicts double digit growth for service robots through 2018
• Japanese telcos vie for share in consumer robot-as-a-service business
• The second wave of social robots is here
• Natural language: The de-facto interface convention for social robotics

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

https://youtu.be/xKFaYuBF9HU

Virtual assistants are setting the bar for the kind of user experience people will expect from the social robots of tomorrow.

At the Apple party earlier this month, at the Bill Graham Civic Auditorium in San Francisco, CEO Tim Cook and other key execs took to the stage to announce their next-generation product offerings. Apple’s been setting trends in user interface (UI) and technical design for over two decades now and its latest products didn’t disappoint: Siri already inhabits our iPhones and responds to voice commands, but now she will soon be embedded in Apple’s TV remotes too, so that users can change channels, find weather forecasts and get sports scores simply asking for them.

Siri demonstrates just how far we’ve come from the early days of interfacing with computers, databases and other information systems. Whereas systems used to be able only to respond to constrained queries, such as a Google search, Siri is now intelligent enough to respond appropriately to fairly detailed, human-like, requests, such as “Show me the Modern Family episode with Edward Norton” or “Skip ahead seven minutes.” She can even respond to questions such as: “What did he say?” Siri will simply skip back 15 seconds to the previous line the actor said. It’s an innovative new interface for controlling TV and a host of other media, and it’s likely to change how we interface with computing even more significantly than the introduction of the GUI (which, if we remember, Apple also had a hand in rolling out).

In addition to Siri, there’s a swarm of other software robots descending from the clouds: Google’s Google Now, Microsoft’s Cortana, Nuance’s Nina, and the Amazon Echo, which plays music, reads books and can buy stuff listed on their site. All of them keep track of what you like, when, and are able to draw massive amounts of data from both your voice (gender, age, region and other vectors) as well as the words you use. Baidu announced Duer in the first week of September with the intention of providing a voice interface for the home and internet of things (IoT) services and healthcare support. The company also  plans to integrate it into self-driving cars.

And recently Facebook’s M was touted as a concierge service available through its messaging app. This is a smart play, as Facebook is manning the assistant with a crowd of  employees (called M trainers) to simultaneously answer requests and train the system to improve responses. It seems a short step for Facebook to place ads in M (much as they do in site content today), but the real revenue stream will be in collecting user data. For the time being, as with Baidu’s Duer, Facebook’s M is not voice-driven, but uses text as a feature within the Messenger app.

Our mobile devices are becoming natural language interface hubs for life management and, as a result, having a gravitational pull on an increasingly complex buzz of connected services and APIs.

There are many others: Samsung’s S Voice, LG’s VoiceMate, BlackBerry’s Assistant, Sirius, HTC’s Hidi, Silvia and Braina, to name a few.

We can also foretell the future by looking at less advanced natural language systems. Bots – essentially natural language oriented scripts – are a good indicator of where the robotics industry is at because bots are pervasive, useful, and simple to author. TwitterBots and FacebookBots crawl through these systems like bees in a hive, industriously providing retweets, reposts, summaries, aggregations, starting fights and flocking to followers. They can be bought, auctioned, sold, and deleted; you can buy 30,000 Twitter followers on eBay for as little as for $20, provided they’re all bots.

Several years ago Facebook estimated that around five percent of all accounts are bogus – this would put the number of Facebook fakes at around 50 million – while other, now-antique estimates range as high as 27 percent (that’s about 200 million trash-trawling bots). They’re relevant because emergent technology arrives from the fringe.

According to Gartner’s 2015 Hype Cycle chart, Intelligent Virtual Assistants still have a ways to go before they get good enough to go mainstream (likely, 5-10 years). But also according Gartner, roughly 38% of American consumers have recently used virtual assistant services. They predict that, by the end of 2016, around two-thirds of consumers will be using them daily. Other sources forecast that the global Virtual Assistant market will grow at a CAGR of 39.3% between 2015-2018, and the total market is projected to climb to more than $2.1bn by 2019. These numbers cluster around the trends in natural language interfaces.

These trends show no sign of altering their flight path. Our mobile devices are becoming natural language interface hubs for life management and, as a result, having a gravitational pull on an increasingly complex buzz of connected services and APIs. This means that things like search will change: we will no longer have to speak Googlese; paper and page metaphors will be supplanted by the more dynamic (and cognitively more addictive) character metaphor. And if trends in virtual assistants and intelligent helpers – software robots – continue, then knowledge-bases (such as Wolfram Alpha or IBM Watson) will continue to come peppered with a patina of natural language, allowing us to move through data faster, with less training, and in a more human manner.

This is the trend in software robots, and it is headed towards hardware, too.

Hardware is the new software

Software robots show us what hardware robots will be expected to do in the near future. First, natural language is the de-facto interface for a range of functions from social robotics to customer service and personal healthcare companions – not only because it increases the quantity of data collected, but also because it decreases the cost of collecting it. Not only because it replaces people, but because it amplifies them.

That said, the natural language interface, or voice UI, is only one of many that robots will be expected to provide. Virtual assistants can now perform a range of functions based on the online services that are commonly integrated. Since these services can now be integrated into any connected system, we can put together a laundry list of what hardware robots will be expected to do:

• Understand voice input (respond to commands, answer questions, etc.)
• Offer personal assistance (schedule appointments, set reminders, check stocks, etc.)
• Provide mobility assistance (give directions, predict traffic, find parking, etc.)
• Interface with connected devices (TVs, garage doors, lights, surveillance cameras, etc.)
• Allow you to buy stuff (and keep track of what you’ve already bought)
• Interface with social media (send photos, read tweets, etc.)
• Detect mood (read emotions, body language, save state, etc.)
• Build predictive models (track user behavior, save user state, etc.)

Robotics will increasingly adopt a voice UI, akin to what we see in today’s personal assistants, because task completion is simpler, faster, and more effective, menus go away and personality (the UX of NLP) is a lot of fun. These software robots are testbeds and proving grounds for what users expect from tomorrow’s hardware robots; they set a bar for user experience. Personal assistants, like their distant cousins from a hardware lineage, will soon be smart enough to reply to other robots that call us on the phone, and we will want to equip our Jibo, Nest or Alitalia system with it’s own resident assistant that will answer the phone when the robot from the cable company calls.

Whether you happen to be Siri or the gal working for customer service at the cable company, your job, your life, your car and your family is being invaded by the swarms of personal assistants changing tomorrow’s robotics industry today. We have a choice: either we design hardware robots as assistants and companions (to help us accomplish tasks and keep us company), or we design them like bots (to mull the garbage, aggregate the trash, and harass one another).

The future, it seems, contains both.

The campaign has also unlocked 12 stretch goals including:

• Kids programming environment
• Special Kids pack (i.e Autism)
• Side tray accessory with USB charging
• Expressions pack
• Elder pack
• Hackathon
• Black color
• Memory extension to 32 GB
• Air quality sensing module
• Easypath application to create your own smart applications
• IBM Watson integration

And Blue Frog Robotics has also announced some accessories including:

• Standard motorized arms
• Pico Projector Arm
• Docking station for charging

Developed by the French company Blue Frog Robotics, BUDDY beat his crowdfunding goal ($100,000) in a day, and has been filmed and written about across the world.

BUDDY has a new (second) home

BUDDY enjoyed an enthusiastic welcome on his first visit to the US in August to meet press, investors and fans. He’ll be a regular visitor as Blue Frog Robotics announced the opening of its North American offices in Boston and San Francisco .

Videos

“Buddy is a really, really, ridiculously cute family robot” – Lucas Matney, TechCrunch

“Buddy the robot protector looks like R2-D2’s first cousin” – Stephen Beacham, CNET TV

“With Jibo and now Buddy, Boston is becoming a social-robot mecca”  – David Harris, Boston Business Journal

“Meet Buddy: the Stars Wars-Inspired Robot”< – CRN

“Robot pet-sitters?”  – Scott Kirsner, The Boston Globe

“Buddy robot snubs creator” – Dan Simmons, BBC news

“Buddy the robot is ‘more useful than an iPhone’”
– Anthony Cuthbertson, International Business Times

Articles

“BUDDY, A Crowdfunded Robot And Platform” – Hubert Nguyen – Ubergizmo

“Buddy whisks around on wheels and casters while JIBO, another social robot option, swivels harmlessly on your desk or floor” – Dominic Basulto, The Washington Post

“Buddy marks an advance in the progression of agents from Siri to Amazon Echo, as it moves and interacts proactively” – Ross Rubin, Venture Beat

“Downloading apps on your own personal robot may become as common as downloading apps on your smartphone”  – Cadie Thompson, Business Insider

“Rolling Buddy robot may just kill you with cuteness”  – Lance Ulanoff, Mashable

Rodolphe Hasselvander, creator of BUDDY, says: “We are incredibly overwhelmed and thankful for the love and support BUDDY has received over the past month. The reaction from people is beyond even my wildest of expectations.”

Transcript included.

In this episode, Ron Vanderkley speaks with Dr. Eleanor Sandry of Curtin University about her new book Robots and Communication. In the interview, we explore human to animal communication and what we can learn from it; human to humanoid robots interaction; and human to non-humanoid robots interactions. Also, we discuss Western and Eastern perceptions of robotics.

Dr. Eleanor Sandry

Eleanor Sandry is a Lecturer in the Department of Internet Studies at Curtin University in Perth, Western Australia. Her research is focused on developing an ethical and pragmatic recognition of, and respect for, otherness and difference in communication. Much of her work explores communication theory and practice by analysing human-robot interactions in science fact, science fiction and creative art.

Links:

• Download mp3 (16.6 MB)
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Transcript

Ron Vanderkley: Good morning Eleanor, if I can first ask you to introduce yourself to The Podcast listeners.

Eleanor Sandry: Hi there, well I’m Eleanor Sandry. I’m a lecturer in Internet Studies at Curtin University in Western Australia. My research is about communication in general, not just on theinternet and I’m particularly interested in human-robot interactions so that we can understand communication more broadly.

Ron Vanderkley: What got my attention to your subject was an up and coming book that appeared at a conference listing, if you can briefly tell us a little bit about the work on this book?

Eleanor Sandry: Yeah, so the book is called Robots in Communication and it’s been published by Paul Grave in the Pivot Series, which means it’s available online and print on demand. It’s a short format book, 45,000 words. It’s shorter than your average monograph and that’s because I wanted it to be accessible to a range of different people. It’s pitched towards people who are interested in robots, people who are interested in communication – human communication theories – so it’s trying to cater for quite a large audience. What it does is look at human-robot interactions and it tries to unpick them in some detail from a number of different theoretical perspectives.

I’m particularly interested in broadening the size of communication beyond just the transmission of information and ideas of success that surround accurately transmitting it. I’m interested in non-verbal communication; the idea that it isn’t just about what we say, but it’s about us using facial expressions and also movements more generally. I found that robots were just agreat way of looking at a huge range of different types of communication because they are sometimes built to look as human-like as possible, but on other occasions are completely machine-like, and yet what you find is the people who interact with them often develop some kind of relation to them. Even to a Roomba and other iRobot floor cleaners. Just looking at that gives me a whole range of different forms of communication to consider and things I can say about communication in general.

Ron Vanderkley: You speak about this idea of humanoid robots and the non-robots as a point of contact. What actually steers you towards the humanoid? Is it the facial features, the gestures, themovements?

Eleanor Sandry: I think that most people are studying humanoid robots because of particular facial features and expressions, in some cases. But, in others, it’s to do with physical ability to move around in human-like environments. One ofthereasons the Atlas robot – which is about to compete in the darker challenges – is human-like is because it’s expected to go and work in environments that are tailored for humans, but where humans can no longer enter, for example because of some catastrophic disaster.

In fact, I am much more drawn to non-humanoid robots and I’m particularly interested in the way that people will still read pretty much anything that moves as somehow trying to communicate with them. I’m also conscious of the fact that people who are trying to work with robots do better if they do develop this kind of relationship with them. Part of what I have been writing in the book is actually about looking at how those relationships develop and seeing those, say, between humans in ordinance explosive disposal and their robots. Relationshipsbetween people and robots are not necessarily a bad thing or something that we should be worried about; it actually allows those teams to operate better in real world environments.

Although a lot of people say that a sociable robot needs to be able to make gestures, maybe to also have facial expressions; that depends on the structure of the robot. I think there is a lot to be learnt from human-animal interactions. The things that humans and animals are capable of doing together open up possibilities for lots of other forms, for robots to be seen as effective teammates, basically.

Ron Vanderkley: For instance, canine interactions, this kind of trust and understanding. That is a whole different facet and we are still coming to termswith how wecan do that in robotics. Are you picking that apart and trying to figure out how wecan do that?

Eleanor Sandry: Yeah, I’m particularly interested in the idea of the need to have, almost, a trust and respect relationship in order for the team to operate effectively together. In the human-canine relationship, there would always be an overarching power relation. The human is almost always in control of the overallsituation and is working with the dog to achieve a particular purpose, for instance tracking a scent trail. The same is true with humans and robots and, at the moment, say with ordinance disposal robots, broadly, the human is in control almost 100 per cent of the time: they’re still mainly radio controlled or controlledvia wire connection. There are some things that they can perform autonomously like righting themselves if they fall over and maybe also returning to base.

What I’ve been trying to unpick, I suppose, is the idea that if a robot is going to become more autonomous, it will be out of contact with its human controller. There needs to be a more complex relation between the human andthe machine in order for that team to operate well. Thehuman effectively has to relinquish control to the machine at the point of which it moves out of radio contact, they have to trust in the robot to do its job. All of these ideas – even the terminology of me saying to do its job – isproblematic, historically, in understanding human-animal relations. Because many people think that a dog doesn’tknow what its job is, or isn’t going to take responsibility, and yet people who train dogs will tell you that this is precisely the way that you need to think about the dog in order tounderstand what is happening in the team, because you don’t have the nasal senses that the dog does.

It’s actually important that you trust a dog to do its job, so when it appears to be moving off a trail, in fact its followinga path that you have no idea exists and it will bring you to the final point; will complete the task effectively. I think thereare possibilities of the same thing between human robot teams, where the robot has senses that a human doesn’t. You have to learn to trust in those senses and I think it’s an interesting way to think about these relations. I think it has practical possibilities in the robotics community, but I also think it tells me all sorts of interesting things about how humans and other things interact.

Ron Vanderkley: The idea that we could try to use speech recognition between robot andobject, that being the only means of communication in the animal or non-animal world, is not entirely true. It’s looking at gestures, our voice.Is this also something that we may not have looked at in the robotic world?

Eleanor Sandry: Well I think there is a tendency. It’s not so much that it hasn’t been looked at but that the final goal is seen as being able to create a robot that it’s possible to activate entirely with just your voice and that will understand human expressions and gestures perfectly. I think that what’s being missed is that the robot could understand things differently from us. It’s not actually necessary to embed the robot in the world ina human-like way. It can be embedded in its own way and understand us in particular ways, even if that’s using sensors on hands that help direct the robot. Actually looking at those as real possibilities, not a problem that needs to be overcome, has potential forincreasing the flexibility of the way robots work.

The other reason I’m particularly interested in that is because I hope to start writing more about critical disability studies. That has really opened my eyes to the fact that technologies that are currently being directed towards very human-like interfaces may actually make it harder for people with disabilities to interact with a robot that might otherwise be very helpful to them in living their everyday lives independently. Really looking at a whole range of different interfaces for machines like this is important; not just thinkingof trying to perfect this notion of the human-like interface. I just don’t want them to cut down possibilities I suppose.

When I talk to people sometimes about robots, I get two reactions: normally, I get the people who are really firmly interested in human-like forms and want to make sociable robots as human-like as possible, and then I sometimes get other people that say “we never make robotshuman-like.” I get this divergent reaction and, really, I’m somewhere in the middle, trying to say “well, can’t we think about this differently? Can’t we think about this froma communication perspective, where you start seeing all the different ways that people and things and animals can communicate?” Because you’re quite right, of course, dogs don’t just respond to voice, they respond to tone of voice. They also understand things in ways that we can’t really possibly fully appreciate because wejust don’t have the senses that a dog does.

Ron Vanderkley: The other aspect I was considering is that we are talking about robots actually understanding us. I spoke to a guy in the UK about, I think, a robot called Hector, where it’s entertainment. It’s a robot telling the general public what is going on, with hand gestures, eye movements, et cetera. It’s a teaching tool, almost. I found that very interesting. Is that also something that you’re looking at?

Eleanor Sandry: I suppose it’s not my primary area of interest but that doesn’t mean I don’t think it’s important. I think that sometimes when I talk it’s easy for me to get obsessed with all the non-humanoid robots and it makes it sound a bit like I’m actually saying that we shouldn’t have humanoid robots and I don’t think that’s correct at all. I’m sure there are going to be situations where a humanoid robot works much better and that is probably a very good example. If you have a robot that you want to actually present to people and you want, effectively, to present it in a human-like way, then that is what you’re aiming for. You’re aiming for something that inspires the audience to pay attentionto it because of its abilities – that may sometimes be very important.

I think that thinking that that’s the only way to build a robot – that can be captivating, or attract attention, or draw people into communication – is probably incorrect and there are other examples. Certainly robots in art, for example, where a totally non-humanoid machine completely captivates its audience through its movements and the things it does, the sound it makes. It’s a very different idea; it’s not to try to transmit information directly but it’s still building a kind of relation between the human andthe machine that may lead us to question the ways that things exist in the world, which I think is usually quite a good thing. Also when things are framed by particular tasks, so anything where people and the robot aretrying to complete a task together kind of frames the communication that takes place.

I think it offers many more possibilities for non-humanoid communication in that particularsituation because you know what you’re aiming to do. And yourcapability of reading non-verbal communication is probably much greater in that situation. With the example of the robot up on stage, often a humanoid robot is going to win the game there.

Ron Vanderkley: When you look at the history of, say, robot interaction targeted at children or things like the first robot dog, where children actually relate to that almost as a real dog, and treat it as a real animal, do you think that’s the precursor to a closer relationship with non biological entities?

Eleanor Sandry: Well, I think its one direction in which to go. I’m slightly concerned by the idea of trying to create robots that effectively replace a relationship that someone would have with something that already exists in the world. It’s one of the reasons that I’m not so interested in humanoid developments, and also in the very animal-like robot developments, because it may notbe a good thing to replace the relationships that people already have with living things with a robot equivalent. Children are actually a fascinating example of humans who are freed from the need to justify all the decisions they make about how they’re going to interact with something and so, yes, theyreact to things, like a robotic dog,strongly. Their understanding, if something goes wrong with it, that it needs to rest or sleep, shows just how strong their understanding of the robot is.

I think that’s one of the reasons why I’m interested in robots that appear more overtly machine-like, because they remind you that you’re in quite acomplex new relationship with something that’s different. It’s different froman animal, it’s different from a human; it is its own thing.For example, I looked at interactions between humans and Guy Hoffman’s robot, which is a robotic desk lamp, a lighting assistant, and they did experiments together. People’sinteractions during the interaction were very much as if it was somewhat alive, not necessarily like an animal or anything else, it was an alive desk lamp. But you could still switch it off; it was still a machine as well.

Humans are capable of holding both of those ideas. I think children may be less worried about that, so as a specific example they do show just how far those relations can go. I suppose I’m interested in how you can signify that those relationships are actually different, that it is still a machine. However, I don’t really think that robots should replace human-animal relations. I just read something recently about a different researcher in Australia who has written about how he thinks, in the future, humans will have robotic animals and that immediately made me think of Doandroids dream of electric sheep? The original book has a very strong section in the front that is about the ownership of robotic animals being all that was possible for most people. The richest people had a real animal. It seemed to be that future idea and I hope and pray that we are not going to go that way.

Ron Vanderkley: No. There’s a concern throughout the entireinternetaboutthe future of autonomous robots, AI being this Skynet-kind of world, by those who I think are quite smart people. It kind of sends the wrong signals. I just wanted to see your take on things.

Eleanor Sandry: Well, my take on it is artificial intelligence has a long way to go before it ever getsto that kind of level. I also think that the way that it’s being developed at the moment, it’s not necessarily ever going to be the same as a human-like intelligence. An artificial intelligence is going to be different almost certainly. Yes, I get frustrated at the hype around the technology, and you’re right, it’s very respected voices that are raising these kinds of issues,and in the near future as well. I simply don’t think it’s going to happen in the near future and I don’t actually think it’s going to happen the way that some people are suggesting it might either.

I would definitely want to draw back from that and point out just how far away artificial intelligence is from being at that level. I mean Google Drive. These cars don’t drive everywhere; they drive in one particular place, where it’s been mapped sufficiently for them to be able to operate. I don’t think that people are necessarily aware of that when it’s reported in the mainstream media.

Ron Vanderkley: Not at all, and humanoid robots actually cost an awful lot of money to build …

Eleanor Sandry: Huge amount.

Ron Vanderkley: I don’t even know if Sony is actually able to clear a real amount of money.

Eleanor Sandry: I doubt it very much. I mean, that robot has been in a series of developments, way over a decade now, and still has issues being placed into a normal physical environment and operating successfully. It has to be ina controlled environment. I think that the general public probably isn’t aware of that. The difference between seeinga robot acting in a laboratory, in a controlled setting, and actually being able to interact in the normal physical world that we live in is something completely different. They are streets apart.

I saw something about the darker challenge basically explaining that they would be very impressed if one of the Atlas robots, or any of the other bipedal robots, actually manages to make it through the course without falling down. I think that that’s a realistic understanding of what’s possible at the moment. The idea that robots with four legs might actually operate more easily in those types of environments is fair and should be perceived as well. It’s a very interesting question.

Ron Vanderkley: Absolutely, and just in a previous podcast I was talking to some guys about soft robotics. I mean that’s completely going …

Eleanor Sandry: Totally, a very fascinating area.

Ron Vanderkley: Yeah, completely, a different direction and its early days.

Eleanor Sandry: Yeah, very early days, but there is so much potential for soft robotics but also mixtures of soft and hard. I saw ages ago that, rather than using a hand-like gripper to pick things up, someone had developedsomething that could actually… it was almost like something filled with coffee.

Ron Vanderkley: Like a bean bag.

Eleanor Sandry: Like a bean bag yes, that could grip. Those sorts of innovative ideas that are thinking of totally different ways of solving the task, rather than trying to make something that has a human-like hand, seem to me to offer tremendous potential and so I’m fascinated by the idea of what a robot might end up looking like in the future. I’m kind of encouraged that maybe robots in the future won’t look like us and actually that would be a really good thing.

Ron Vanderkley: That’s another human concern. Someone once put it that if we try and design something that looks so close to a humanand almost mimics the face, there’s total distrust. Whereas if it looks like a robot there is more trust.

Eleanor Sandry: I think there definitely is potential. I mean whenever I write about robots I always end up having to utilize the uncanny valleyexample. I’m kind of quite frustrated with it now: that idea that, as a robot becomes more and more human-like,eventually it’s actually read as zombie-like and there is a strong drop off in the level of trust in the robot. Some people suggest that you could climb the valley on the other side and eventually end up with aperfect human-like machine. Then, as has been written about in many different science fiction books, you have the question of what is the difference between the robot and the human and …

Ron Vanderkley: Silicon versus Calvin.

Eleanor Sandry: I think, really, we’re nowhere near achieving that at the moment. Even the very, very human-like faces you can see pretty easily from their expressions and from other things about them. I don’t know why we want to aim for that. I think that we have …

Ron Vanderkley: Perfection.

Eleanor Sandry: Yes, but it seems to be a perfection that’s driven by a100 percent understanding of humans being the pinnacle of evolution and, therefore, that should be the pinnacle of robotic development. That just seems to me an unfortunate decision to make. There are many more options for robotics than trying to achieve human-like status. I think that there are many other ways that machines could be far more interesting, far more useful but also maybe even develop new relations with people that don’t have to be like something that already exists.

Ron Vanderkley: One of the ideas in modern day sci-fi, the cyborg…

Eleanor Sandry: Yes, the idea of augmenting human ability, of fixing people, which is a very hot topic in disability studies because,in general, there aremany people with disabilities who do not wish to be fixed.Again, it’s driven by this idea of the human being the current pinnacle of evolution. Let’s see howfar we can take it. I hesitate to mention this but, as Dona Harrower said many, many years ago, in 1985 actually, we are already cyborg. I’m effectively a cyborg: I wear contact lenses; that’s the only way I can exist in this world. I would not be alive without those developments – of glasses or contact lenses. But where people begin to decide to amputate limbs, in order to have blades, because that means they can ran faster, that’s another thing science fiction is written about. There are all sorts of – not just ethical – questions, but bigger questions around that.

Ron Vanderkley: You brought up sci-fi as a sounding board. Do you use that as a sounding board for some of your ideas or your thoughts?

Eleanor Sandry: Often I do, yes: in fact, in robots and communication. Science fiction to me is a really great place to look because it’s sometimes overlooked as being a kind of subgenre. For some people, for many years, it was not real literature and not something that was studied much in scholarly circles. But it provides a real sounding board and some of the best science fiction writers write about embedding technology in societiesin ways that allow you to really think about some of these questions ina more developed way,because someone has written a story about it. It seems to provide a reallygreat way of thinking through some of the questions that are very difficult to picture in your head, whereas science fiction provides you with those kinds of thought experiments that can be so important.

In my thesis – what I was doing for my PhD- I did write more about science fiction: the idea of culture and human-machine interactions in culture were to me very interesting because they push way into the far future I guess.

Ron Vanderkley: Coming back on the idea that technology is going to take over. Is that something that you think that’s going to be more and more of a problem, as sci-fi seems to dwell on the bad things and not the positives, or is that just good for entertainment?

Eleanor Sandry: Well, it’s definitely good for entertainment. It’s also a very Western perspective on robots andtechnology. Whereas in Japanese Manga, the whole idea of technology, and robots in particular, is far more positive. Also, it’s a great pity that we lost [Iain] Banks because that was someone writing about a utopian feature, problematic in lots of ways, but at least he offered some kind of positive vision of the way things could work. You’re right, in general, there will still often… they’re not exactly disaster movies are they? But they’re kind of …

Ron Vanderkley: The good guy always seems to win in the end.

Eleanor Sandry: In the end but there is usually a potential for total disaster in the middle, isn’t there?

Ron Vanderkley: Okay, so in closing, what do you think is going to happen in the field of robotics, well, in Australia?

Eleanor Sandry: Australia is interesting and I’m still trying to get to grips with what’s happening in different parts of Australia. I think that the level of funding here may be very different from other countries. There are interesting things going on and I really need to spend more time getting to grips with them because I keep on reading things about what people are doing in Melbourne, starting with robotic arms, the disabled, people with disabilities, and I’m interested that there is stuff going on in Sydney. I’m seeing people from the Center for Social Robotics there, and so I’m particularly interested in what they’re doing and the cost as well.

I think robotics will continue to develop here. There is probably quite astrong drive towards thinking of robots in terms of self-driving machines, mind technology. That’s always going to be a big thing in this country. There are definitely innovative thinkers in Australia who produce interesting solutions to different problems and I would like to carry on finding out what they’re doing and writing about it.

Ron Vanderkley: Okay and to cap that off, if I can firstly thank you for giving the time to chat. On behalf ofThe Podcast, thank you very much.

Eleanor Sandry: Well, thank you for having me. It’s been great to talk.

All audio interviews are transcribed and edited for clarity with great care, however, we cannot assume responsibility for their accuracy.

Through the Jibo SDK, developers have high-level access to Jibo’s audio processing, visual processing, persona and interaction, and movement capabilities. The SDK gives developers the tools to build a wide range of Jibo Skills for personal enjoyment or as a business opportunity. We sincerely believe developers have a huge role to play in extending Jibo’s personality and capabilities, making him the social robot people are looking forward to being part of their lives.

To realize this, Jibo’s SDK development team has been working on creating an SDK that makes developing on Jibo accessible to a wide range of developers. Our skills development team has been using the alpha version internally for a number of months now. In this video, Jonathan Ross and Francois Laberge talk about the challenges of building Jibo’s SDK and some of the innovative approaches they’ve used including the use of Electron and the Atom Editor from Github.

https://youtu.be/94n6A_1GSaE

https://www.youtube.com/watch?v=51yGC3iytbY

Built on open source

The brainchild of Rodolphe Hasselvander (CEO and Co-founder of Blue Frog Robotics, and former Executive Director of the CRIIF (Robotics Lab)), BUDDY is built on an open-source technology platform so that developers can easily collaborate to build hardware and software for it.

BUDDY was purposely built on an open-source technology platform using popular development tools, such as OpenCV and Unity3D, to allow as many developers as possible to build applications for it. BUDDY’s industry standard platform includes the most popular programming languages and the Android mobile operating system.

Specs

BUDDY is 22-inches/56cm tall, 5 kg in weight and with a battery life of 8-10 hours.

He features an Android-based, Intel Atom-based tablet (also the hub for BUDDY’s brains) that sits in a rotatable head and can slide back and forth on his body.

Fully mobile, BUDDY rolls around on three wheels (two large ones in the front and a caster-style wheel in the back) and has a plethora of sensors allowing him to travel, learn and interact with the world around him. He is also equipped with state of the art Artificial Intelligence technology, including face and object detection, recognition and tracking.

The campaign

We have chosen crowdfunding as the route to market for BUDDY as we want to give early adopters the chance to test BUDDY before it hits the mass market. We also want to cultivate a thriving community of developers. We’re keen on working with talented and innovative developers, as they will help us design and augment BUDDY before bringing it to mass market.

• Super Early Bird backers can purchase their own Classic BUDDY from as little as $499*, and Developer Edition BUDDY for $599*. (SOLD OUT)
• Early Bird backers can purchase their own Classic BUDDY from as little as $549*, and Developer Edition BUDDY for $649*.
• After Early Bird, prices will be set at $649* and $749* for Classic BUDDY and Developer Edition BUDDY, respectively.
• BUDDY “Special Needs” Early Bird Pack for $799 uses specialized software and content to help children with autism learn, communicate, and be more autonomous.
• For $849*, backers can purchase the BUDDY Premium Pack, which includes a projector arm and docking station. The accessories are now for sale separately.
• Buy 2 Classic BUDDY’s for $999*.
• VIP option. For $4,999*, design your BUDDY with us to create a totally unique BUDDY, signed and engraved by the whole team. As a VIP, you’ll also receive a dinner in your honour with the CEO & BUDDY team, travel and accommodation to Paris, a BUDDY premium pack and a private demo.
• Academics BUDDY Developer Pack priced at $6,490 includes 12 robots for the price of 10.

*Plus shipping costs of $50 for one BUDDY and $100 for two BUDDYs

Blue Frog Robotics has also just launched a referral program to bring BUDDY to more homes and families. Indiegogo backers can earn $65 credit towards BUDDY’s campaign every time one of their referrals purchases a BUDDY from $549.

The team behind BUDDY

Rodolphe Hasselvander, Co-Founder & CEO – A pioneer in professional and personal service robotics, Rodolphe spent ten years of his career as Executive Director at CRIIF, a robotics research laboratory.

Franck de Visme, Co-Founder & COO – An entrepreneur by nature, Franck co-founded Hanakai, and is the former CEO of both Tetraedge and Earthlings. He is also a skilled mentor for innovative startups (NUMA).

Jean-Michel Mourier, CTO – Jean-Michel is a passionate robotics engineer with expertise in autonomous navigation, vision, electronic architecture and intelligence. Previously, he worked on several high profile robotics projects in both industry and the lab.

Maud Verraes, CMO – Maud is a marketing leader with extensive experience in developing innovative and high-tech products and solutions, including personal robots. Formerly, she worked with NEC.

https://youtu.be/_f8VjQLO8Xw

If you liked this article, you may also be interested in:

• The second wave of social robots is here
• Why are JIBO, Pepper, Siri, Google Now and Cortana so important?
• Jibo raises $1M in first week of crowdfunding campaign

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Pepper robot, by Aldebaran.

Social Robotics: The UX of Natural Language

A very smart and snotty journalist told me that he had spoken with Aldebaran’s Pepper system when he was in Boston. Much to his chagrin, the robot didn’t reply when the journalist spoke to it. “It didn’t understand a word I was saying,” said the journalist. “It simply doesn’t work.” The only word it understood, he said, was “sushi” … at which point I realized that he was speaking with the system in English, but the robot was programmed to understand Japanese. 

This is a problem of user experience, or UX.

Natural language interfaces are turning into a de-facto interface convention. Just like the GUI overlapped and largely replaced the command line, NLP is now being used by robots, the Internet of things, wearables, and especially conversational systems like Apple’s Siri, Google’s Now, Microsoft’s Cortana, Nuance’s Nina, Amazon’s Echo and others. These interfaces are designed to simplify, speed up, and improve task completion. Natural language interaction with robots, if anything, is an interface. It’s a form of UX that requires design.

The next phase of UX is psychological: Natural Language personalities.

We all use language on a daily basis as our key interface with other people, so expectations of how to talk are as deep as they are diverse. We all seem to have, from time to time, problems talking with one another, so designing talking interfaces is a hard UX job. Topic management, dialogue turn-taking, segue management, association with iconic gestures, and thousands of other aspects of communication sit right in the middle of this emerging design discipline.

Traditionally design, even software design, employs the famous architectural adage of, “Form follows function.” But when it comes to natural language interfaces, and robotics in general, we enter a new kind of design in which function follows form. The form of human interaction becomes the function in making something metaphoric, simple, fun and useful.

When it comes to human-robot interaction – and social robots in particular – the form defines the function. There are at least three reasons for this I’ll list here. All of them are psychological.

Social robots should look like us.

First, a user should identify with the conversational system. Any school age child will tell you that there’s no pragmatic reason to make a computer look anything like a person. The android seems a fool’s design. It’s off-balance, clunky, the sensors are too high, walking is hard to calculate, and when the robot falls, it takes a serious digger damaging the sensors that are perched at the part of the robot that gets the hardest knock when they fall. And what is a head for, anyway?

It turns out that babies (and adults, and school age children too) are wired to recognize even an abstracted human face surprisingly quickly and at a surprisingly early age. Babies, when they’re still wee things, are drawn to facial imagery, even if it comprises just two dots and a curvy line. I tried this on my own piglet when he was 5 months old. I gave him a drawing of a circle with the two dots and a curved line, and another of a square with a single dot and two lines. He went back and forth between the two drawings, but spent at least six times longer staring at the face drawing.

Which drawing do you prefer to look at?

What is even more curious is that 6-month olds are more likely to spend time looking at what you or I might call an attractive face (see e.g. here and here).

So it stands to reason that a social robot should have an attractive face, simply because humans are wired to pay attention to it. And this is part of the metaphor that is driving android design.

But beauty is only skin deep. While we wrestle to escape the uncanny valley of visual appearance, we are learning that there are many uncanny valleys of not just appearance, but sound, color, timing and even psychology. Maybe psychology, most especially.

Social robots should speak like us.

Second, now that NLP technology is generally working well enough to complete end-user tasks and provide contextual training, it’s time to start addressing personality in the same way that we’ve addressed appearance. This means that, just as we need to make sure that we design robots that look like us, we need to also design robots that speak like us.

This simply means that the user experience of natural language must consider psychology and human-like interaction as the core metaphor for the design of social robotics. It’s like making a glove that is shaped like a hand – the tool has to be designed to work with how we’re built. So psychology is key.

‘Birds of a feather flock together’ for some very deeply ingrained reasons associated with trust. We’re accustomed to trusting people that look like us and when we trust someone we actually perceive them to look more like us.

So talking and looking like a human is pretty important for a social robot.

This linking of behavior and appearance is key to user experience. Systems such as those used in healthcare, finances, and other very important interfaces will need to be designed such that they’re reliable, and this means they have to act like the user. Users will scarce be found who are willing to tell their financial data, or discuss private healthcare problems, with some fictional character that looks like a Furby, or a spinning ball of metal. And, to make matters more challenging, the user experience around natural language interfaces will need to address localization issues that include such things as accent, argot, and other manners of speech that are linked to particular regions of a country.

We’ve found in our work at Geppetto Avatars that people are more willing to overlook uncanny elements of design if there are slight cultural variations thrown in. For example we’ve noticed that synthesized voices sound less artificial if they have a slight accent. A synthesized voice with a British accent doesn’t sound quite so synthetic to an American listener. But if you give that same listener a synthesized voice that uses an American accent, the listener is far more likely to notice the synthetic elements. This is simply a UX technique to off-load technical challenges. So UX can serve the role of simplifying not only the interaction, but the technology as well.

Social robots should be polite.

Robots – or other connected systems – that use Natural Language interfaces create spontaneous behavior in the user. Most users actually try to be polite or cooperative, and even start attributing personality to the system (such as humor, aggressiveness, and gender). We all talk to our car, many of us have named it, and that’s how we’re wired. This is something people automatically do, like it or not, with not just natural language systems but almost all forms of media.

In 1996, Reeves and Nass, two famous researchers from Stanford (and authors of The Media Equation), proved that computers elicit social interactions in users. Reeves and Nass designed an experiment in which 22 people come into a lab to work with a computer via natural language text interface. At the end of the session Reeves and Nass asked them to evaluate the computer used and how well it performed. Reeves and Nass found that users had automatic social reactions during the test, and opinions about the personality of the machine they were using.

They ran the test again, this time via natural language voice interface, to make the human-social theme more evident. The test results were the same. They concluded that people are polite to computers, both in speech and writing, and the experiment showed that social rules can apply to media and computers can be social initiators. Participants denied it, but the results said otherwise.

Try it yourself – watch people talk with Siri and they use the word “Please” or “Thank you” more often than you might guess. Then go buy The Media Equation. It’s a great read.

When we design systems that are able to build identification and trust with a user these systems are able to make advice about healthcare and how to use our bodies, or finance and how to use our money. These are powerful systems because they are actually modifying what the user does. The conversational system has a power over the user simply in making advice that is amplified by how we are wired. If ethics is all about power then being polite is the logical interface to ethics.

Interface, whether command line, GUI, or natural language, has always been the most potent and valuable element of a computer design. Interface will continue to be an important and valuable element of robotic design as well. The future of UX is psychological as much as graphical and ethical as much as functional. Ask your car.

UX practitioners and robotics designers need to consider the form and the function, especially when it comes to natural language interfaces. Otherwise, 私達はちょうど悪い寿司の貧しい翻訳があるでしょう。*

[“we’ll just have poor translations of bad sushi.”]

The idea of robots being a part of our daily lives is a controversial topic to say the least. It seems everyone you talk to has a strong opinion about the issue as well as an equally vivid image in their head of what a robot looks like. Cliché robot visuals are everywhere in our culture and much of it heavy-handed and unflattering. Popular images conjure a complicated machine with poorly simulated human-like parts mixed with exposed joints, sensors and lights.

Robots have looked the way they do for a good reason. Most of these machines are a collection of motors/sensors/chips/joints that strive to mimic the movements/appearance of lifelike beings. The overtly mechanical look is driven by physical necessity, allowing these machines to do real work in a very task-oriented manner.

A social robot is a very different machine however. The vision that Cynthia and the Jibo team laid out to us almost a year ago painted the picture of a socially connected, intelligent home companion. Its primary skill would be its ability to emotional connect with its user and become a helpful extension of the family. Jibo would have no need to zip around the house on 2 wheels or reach over and pour you a glass of water. Instead, its movements, expressions and communication all needed to be focused directly on the user in a subtle and pleasing way. This robot’s primary mechanical task was to make you smile J.

Every design project has unique challenges and this one was certainly no exception. How do we erase the visual constructs of what a robot is supposed to look like and focus this new experience? What qualities will make this little machine deliver on the promise in sophisticated, visually bold way? John Maeda, renowned graphic designer and author of The Laws of Simplicity, famously said that the key to creating harmony between object and user arises when you “subtract the obvious and add the meaningful”. This quote summarizes our fundamental design approach with Jibo from early concepts to final product.

Subtract the obvious:

Given the primary task of connecting emotionally and re-defining social intelligence, decisions over eliminating or hiding traditional robot visual elements proved crucial to defining the look of Jibo. Some of these decisions were easy. The Jibo team envisioned a desktop companion freed from the need to complete mechanical tasks, so there was no need for arms and legs. Looking deeper at the elements of a robot, the remaining decisions of what could be eliminated were much smaller, subtle but equally important.

Jibo needed a head, but what level of detail was necessary to convey and connect with users? Working closely with the Jibo team we explored a range of head proportions and played with the level of detail needed. We all agreed we didn’t want to create anything that resembled a toy so any character-driven detail needed to be treated with abstract simplicity. Eliminating as much unnecessary detail in the face and head without taking away the visual ‘character’ necessary to connect with users was a crucial and delicate balance. Through this elimination process, we discovered that actually very little overt facial detailing is needed.

The simplification exercise then moved from the aesthetic features we could safely subtract to the more complicated issue of functional elements we wanted to hide. We certainly didn’t want a complicated mess of sensors, visible cameras and body segments to detract from the bold simplicity of Jibo. This was a heavily collaboration working closely with the extended Jibo team of software, electrical and mechanical engineers. For this effort our previous design experience working on laptops, tiny wearables and countless high tech gadgets was key to understanding where the opportunities to reduce complexity laid.

Add the meaningful:

Understanding the core elements that will make the physical Jibo resonate in a ‘socially connected’ way was equally important to the simplification of form and details. The Jibo team had established a few basic elements that would be key to this emotional connection in the hardware: a friendly silhouette activated by an expressive movement that is directly linked to an intelligent UI ‘face’ and likeable voice.

The design exploration of form and movement were closely linked and needed to be explored together to define the silhouette. Fardad Faridi, Jibo’s talented in-house animator, introduced us to the basics of character expression in animation and shared examples of basic forms that can deliver the necessary ‘line of action’ of thoughtful poses. These movements are crucial to reinforcing the emotions and interaction conveyed through Jibo’s face and voice.

A variety of form + movement architectures were explored but the design that emerged was based on earlier work from the Jibo team in Boston. The architecture sub-divided a very simple cylindrical vertical body into a series of angled/rotating sections. By controlling the movement of each section independently Jibo was able to quickly snap into a variety of expressive poses and appear to magically dance in a pleasing way. The most impressive aspect of this architecture was its inherent simplicity. The traditional pivoting joints seen on most other robotic mechanisms would have been overkill and far more visually complicated. More importantly, the cylindrical nature of the mechanism meant that the eventual form could take on a very elemental geometric quality: an abstracted character composed of a simple cylindrical torso and pure spherical head.

The design of Jibo’s face was probably the most difficult part to get right. Since the user experience would rely heavily on software driven apps and programs we all agreed his face would have to have a display somewhere on it. As discussed above, the subtraction of elements played an important role here but eliminating the display was not an option.  The screen UI (working in concert with the voice and movement) would be integral in creating the facial character of Jibo while also providing necessary supporting visual communication. Luckily, the desire for impactful graphics (that can be easily seen from across the room) aligned with the desire of a large-headed, friendly character silhouette. It was crucial that users not focus on the technology inside Jibo. Hiding the display component behind the face was a seemingly small detail that has a huge psychological impact on how users react to their little companion.

Completing the vision:

In the end, the details make the design. Eliminating as many unnecessary details as possible and celebrating those few remaining with a subtle sophistication was key to the refinement of the physical Jibo. The boldly simple form silhouette made up of pure geometric shapes is accented with subtle precision engineering details and sophisticated surface transitions to express the qualities of a truly premium and intelligent device. Playful elements (such as the friendly proportions, expressive movement, high-touch surfaces of the body and the borderless face) work together to build the approachable human-like quality that other smart devices lack. The combination of these contrasted elements creates a bit of mystery around the intelligence hidden inside and creates an own-able visual icon for the first social robot. We are excited to be able to introduce Jibo to the public.

As stated in the WIRED article, autonomous cars are within our foreseeable future. Designing a system where autonomous cars self-organize is an option that engineers and scientists are exploring because of its possible benefits. Imagine the future where autonomous cars are the norm, and each car can talk to one another regulate the flow of traffic.

How would you feel about your car being a part of such network of autonomous cars? What do you think are the possible benefits and harms?

Image by Robert Lachenman

A couple of months ago, we asked our readers whether three different unlicensed groups of individuals should be able to ride in autonomous cars alone. The individuals were: a child under the legal driving age, a senior who is no longer licensed to drive, and a legally blind person.

One of the most interesting results from the poll was that people are not as supportive of having children ride the cars alone than they are about a senior or a blind person. Discussions that ensued from this with the Robohub editor, Hallie Siegel, was whether people’s sentiment will be different about a car that drives without a passenger, or a passenger who are drunk or under the influence of drugs.

Let us know what you think by answering the quick three questions below:

On July 15th, Jibo launched a crowdfunding campaign on Indiegogo with the goal of raising $100,000 towards developing their new social robot for the home. Less than one week later, Jibo surpassed the $1M mark, with hundreds of pre-orders made for both the home and developers editions.

The brainchild of Cynthia Breazeal, Director of MIT’s Personal Robots Group, Jibo builds on her earlier work in personal robotics (remember Kismet and Leonardo?), and is designed to be an intelligent assistant and companion for the home. The first developers version – sold out at 250 units – is scheduled to release in Q3 of 2015, while the first home version – sold out at 500 units – is scheduled to release in Q4. Preorders are still being taken for 2016 ship dates for both editions.

“We at Jibo, Inc. are absolutely thrilled by the enthusiastic level of consumer and developer support for Jibo. The public is ready to bring social robots into the home! We also see Jibo as being highly relevant for supporting university research in human-robot interaction through our developer program. Our crowd funding campaign is helping us to build a focused community who we can work with to help make Jibo a groundbreaking product when released in 2015. I would be thrilled to see a strong robotics developer community join us in our journey to bring Jibo to the world.” said Breazeal in an email exchange today.

While headlines about Jibo setting new crowdfunding records should probably be taken with a grain of salt (compare Jibo to the top ten business crowdfunding campaigns of all time), no one in the robotics community can deny the excitement of watching Jibo’s early success, in particular with the developer community. According to a report by Crowdfund Insider: it took only four hours for the campaign to be fully funded, 33% of pre-orders have been for developer editions, and after only four days, Jibo achieved a Top 10 ranking among Indiegogo’s Most Funded Tech Projects of All Time. “They were indeed one of the fastest campaigns to reach $1 million on Indiegogo,” said Kate Drane, who leads Indiegogo’s Design, Technology and Hardware section.

“Robotics is really coming of age as a consumer product,” says Andra Keay, startup expert and Director of Silicon Valley Robotics. “People say hardware is hard, but it’s also popular. Nine out of the ten all time top crowdfunded business campaigns have been for hardware and it looks like Jibo is on track to become one of them. It’s fantastic to see a robotics startup getting such great visibility because the secret for ongoing success here is not just attracting users but also attracting developers to build new value for the platform … Jibo is an excellent example of how to successfully tell your startup story and I’m looking forward to seeing what’s next.”

Frank Tobe from The Robot Report agrees: “Jibo is part hype and part hope. But the team is wonderful and spans all the relevant areas needed to fulfill all that was promised. Many companies in this space – particularly the ones that started a couple of years ago – are floundering, struggling with technical problems and lack of money caused by delays. The hope is that Cynthia brings newer technology, the best and brightest team, AND that she has the funding covered. Certainly the IndieGoGo campaign shows consumer interest and adds a lot of extra money to the stash. Still, it will be almost a year and a half before we see JIBO so lets not overhype it now so that anything next year will be anticlimactic.”

With so many preorders to fulfill, robotics tech watchers have been left wondering whether Jibo will be able to live up to its promise, especially given the ups and downs of other campaigns that have started off with a big bang but then failed to ship. However, Scott Miller, CEO of Dragon Innovation – another crowdfunding platform that specializes in hardware – says that preorders have their upside too: “Higher volumes do make things easier when it comes to manufacturing as well as follow-on investment.” Miller adds that often the real goal with crowdfunding campaigns, especially with a team as experienced as the one Breazeal has brought together, “is to discover product/market fit”. Breazeal’s focus on building the developer community seems a wise approach to bringing this vision to technical reality.

See. Hear. Learn. Help. Speak. Relate. These are the ways Jibo-the-robot promises to engage with us. All the more reason for Jibo-Inc-the-company to apply the same standards of engagement to their early backers as they move forward, and to hold to their standard that proactive dialogue is key, even when – especially when – there’s a problem. And aren’t there always a few hiccups along the way?

JIBO, a 2013 Boston startup, launched an IndieGoGo campaign last week and is off to a rousing start, lots of favorable press, and, as of the time of this writing, has raised more than $700,000 over their $100,000 goal.

JIBO is a home device with a small screen that conveys emotions but is also used for social services, story-telling and other functions. It isn’t an appliance, nor will it be available until December, 2015. Apps from the JIBO store will be available in early 2016. But it is a momentous step toward a robotic family member that knows your wants and needs.

JIBO sees with two hi-res cameras. It can recognize and track faces, take pictures and enable video calling. It has a see-and-track feature to turn and look at people and to support video calling. It uses AI algorithms to learn your preferences. It can hear, process and speak using natural language and has multiple microphones to let you talk from anywhere in the room. It proactively helps make everyday tasks simpler.

Using natural social and emotive cues, as well as a connection to the home wifi network, it relates to each member of the household, delivering messages and reminders.

JIBO was developed by MIT social roboticist Cynthia Braezeal (now on leave from her teaching gig) and her JIBO team, which includes speech recognition, nonverbal communication and machine learning experts. “It’s really important for technology to be humanized,” said Breazeal in a NY Times story about JIBO. “The next stage in computing, the next wave, is emotion.”

“What if technology treated you like a human being? What if technology helped you feel closer to the ones you love? What if technology helped you like a partner instead of simply being a tool? That’s what Jibo is about,” said CEO and co-founder Braezeal in a JIBO promotional video.

The device is 11” tall and has 3 full-revolute axes, which means that there are three components allowing the screen/head to swivel in any direction. Its oval display is also a touchscreen. It uses a high-end ARM processor and a Linux platform. The combination of swivelling and clever software graphics appears to master the jump from device to social friend. An SDK and developer units will be available months before the consumer December, 2015 ship date. Because JIBO is an open platform, its skills and applications will grow in unimaginable ways and should be fun to watch. Software app developers are paying attention: 1/3 or the IndieGoGo pre-orders thus far are developer units. 

Competitors in the social robot space include the $260 EmoSPARK (a box console with no screen or moving parts that ships later this year), the $575 Russian Cubic console (which is producing a beta run of 100 units later this year), and the mobile ADAM from Milan-based Hands Company (which showed ADAM at CES in Las Vegas earlier this year and plan to begin offering them for sale in Q4, 2015).

I showed the IndieGoGo video of JIBO to two psychologists and my wife (who said that any device that can order Chinese food is a winner and wanted to buy one right away). Both psychologists said that JIBO really seems to have built a device that is socially attuned and likely to be a trustworthy and functional family member. Their comments, combined with the successful IndieGoGo campaign, suggests that JIBO may be a game changer in the new social robot marketplace.

Cynthia Breazeal’s Jibo launched today and coming on the heels of Pepper, Aldebaran and Softbank’s new social robot, and Jimmy from Intel. It seems like we’re seeing a second wave of social robots. Jibo is less of a humanoid than the others though and more of a human mirror, being able to be a telepresence device or a social robot. Jibo will be an open platform and is currently taking preorders via Indiegogo, with an expected shipping date of Sept 2015 for the developer edition.

Jibo raised several million dollars in early seed stage funding from CRV (Charles River Ventures) in January 2013 and have been stealthily hiring and developing ever since. More recently, Cynthia Breazeal took a leave of absence from the Personal Robots Group at MIT Media Lab and Jibo brought on board additional seed investors Osage University Partners and Cambridge-based Fairhaven Capital Partners.

In BetaBoston, John Lee of Osage is quoted as saying that his firm is “excited about the potential of emotional computing, where consumers can have two-way interaction with their devices through natural forms of communication: speaking, eye contact, body language, and intonation. The nature of this interaction opens up significant opportunities in various fields that require deeper insights into a consumer’s emotional state. Given the team’s exceptional backgrounds, they are the right people to deliver on such a vision.”

Breazeal’s vision is to create robots that can provide parents with a high quality partner in education, provide a life coach for people with chronic health issues, and provide a watchful companion for the elderly that behaves like a friend and not a surveillance system or monitor.

Jibo features two hi-res cameras to recognize and track faces, capture photos and enable immersive video calling. 360° microphones and natural language processing let you talk to JIBO from anywhere in the room. Hands-free reminders and messages, so you’ll never forget and can always be in touch. Artificial Intelligence algorithms learn your preferences to adapt and fit into your life. Like a personal assistant, JIBO proactively helps you, to make everyday tasks simpler and easier. Communicates and expresses using natural social and emotive cues so you understand each other better. [Jibo website]

The first wave of social robots occurred between 1998 and 2009, and their primary characteristic is their ‘pet’ nature. The Tamagotchi (1996 onwards) could be considered a primitive precursor. Social ‘pet’ robots included; Furby 1998 -2007 (reintroduced 2012), AIBO 1999-2006, Keepon 2003-now, Paro 2004-now, iDog, 2005-2009 and Pleo 2006-2009. Some of these were intended for therapeutic settings, like the original Keepon and Paro, but all were intended to create an emotional relationship with people, and not simply to perform functions.

It’s important to specify that social robots have existed in labs and research for some time, so I’m really talking about products that cross the chasm and become consumer products. Robosapien (2004-now) by Mark Tilden at WowWee is one of the few humanoids to come out during this time, but due to the small size and limited interactions, Robosapien seems closer to a pet or smart toy, than to a social robot.

The second wave of social robots is building both on general advances in robotics and specifically on improvements in NLP, natural language processing, leveraging the massive deployment and rapid improvements of voice recognition/response agents like those used by Google, Apple and Amazon.

Computing has gone through several waves, each resulting in billion dollar industries and impacting millions if not billions of people’s lives on global scale. We’ve benefitted from the wave of information, the wave of mobility, the wave of social media. We’re seeing more and more wearable computing and the Internet of Things that combines these three.

Now, we are on the threshold of the next wave of computing: emotion.  And social robotics is a particularly powerful expression of this next wave. [Cynthia Breazeal – Why social robots will change your life]

http://on.ted.com/Breazeal

Robohub is an online platform that brings together leading communicators in robotics research, start-ups, business, and education from around the world. Learn more about us here. If you liked this article, you may also be interested in:

• Building Social Robots: The Journey of Pleo
• The next era of conversational technology
• On Pepper, Aldebaran and emotional robotics: Interview with Bruno Maisonnier
• Why social robots will change your life
• Robots Podcast: A Code of Ethics for HRI Practitioners
• Robot helps 94-year-old Italian grandmother live independently at home
• What should a robot do? Designing robots that know right from wrong

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Building a robot company is difficult, very difficult. It requires unwavering belief in yourself, in your idea, in your team and ultimately in your product. But it is also one of the most thrilling experiences anyone could imagine.

Why? Because people love robots. Especially social robots.

Robots are the reflection of us, in our belief in technology, in our ambition to shape the future. Robots are the exploration between people and machines, the science of artificial intelligence, AI. They test our theory of life, how we think, how we behave and how we want technology to interact with us.

“People want a relationship with robots, they just don’t know it yet.”

This was our driving belief in building Ugobe pronounced “you-go-be”. Ugobe created Pleo, a life-like robot using our “LifeOS” technology that animates robots with life-like movements similar to living creatures. After countless experiences of watching people transform into proud pet owners through interactions with Pleo, I am absolutely convinced that people want to connect with robots in a meaningful way that touches our hearts. When robots truly become social the world will change; we will look at technology as living relationships that enrich our lives, not detract from it. Pleo was the beginning of a new age in robotics.

The journey of Pleo and how we created an amazing product experience is the real story. To build a social robot that transforms people into proud pet owners is not a simple task. You need to build a company that mixes creative “wonderment” with savvy know-how and incredible engineering skills. You need to blend art with science and challenge traditional thinking and experiences. As Gordon Radley, former President of Lucas Films would say to me “you need creative tension in your product development process to build great products.”

We learned how to build creative tension into many of our decisions and company culture. We never allowed ourselves to get “comfortable” with how other companies built products. We always challenged ourselves in a collaborative, creative way. These experiences became pearls of wisdom for Ugobe. Of course none of these experiences would have occurred if we were building an industrial robot. No, we were building a social robot. Something new and different. We needed to push the boundaries of what people thought about robots and their relationship to technology. We thought different, we were different. That’s why Pleo is different… and magical.

I began my journey into the world of robots in 2003 when I met Caleb Chung, the creator of Furby and a master puppeteer. Caleb discovered a way to manipulate robots through the use of an adapted motion capture suit that mimicked the balance and movement of animals. The result was so surreal and uncanny; a seemingly simple device stitched together by hobby servos, wires, and RadioShack batteries began to move as if it were alive: thinking and behaving like organic life. I felt the urge to touch it, to pet it.

At that moment I knew this invention was more then just an idea, it was a platform for creating life-like robots, for blurring the line between people and machines. This was the genesis of Ugobe, the architect and maker of Pleo.

Caleb and I decided to launch our big idea at CES in 2004 where we met Greg Appelhof of TRG. Greg represents consumer tech companies (such as Harmon Kardon and Griffin Technologies) and gets them into Best Buy, Target and other top tier retailers. Greg encouraged us to launch Pleo into retail after describing WowWeeʼs success with Robosapien — selling over 190,000 units through retail channels. He believed in our vision to change the robot category to our benefit. Retailers viewed robots as the next big thing and were hungry for innovative products and solutions.

After a trail of endless demos and mindless meetings with investors who loved robots but didnʼt invest in them, I eventually raised $26MM for Ugobe. I also forged a strategic partnership with Terry Gou of Foxconn and built a worldwide distribution network with tier 1 partners. We attracted the best and brightest people from Apple, Lucas Arts, EA, Blizzard, HP and Google. Our customers included Nolan Bushnell, Vladimir Putin, Jet Li, Steve Wozniak, Sean Parker and many Silicon Valley luminaries. We learned to stay up late so we could communicate with Asia and wake up early to support our European partners. It took a long time to build Ugobe but it feels like a brief and brilliant moment.

Pleo, and the unfortunate exit of Ugobe, five years ago is now robot lore. But what is not known is why we failed and how we could have succeeded if we knew about the 2-year itch. That’s a topic for my next blog. Stay tuned.

If you liked this article, you may also be interested in:

• The next era of conversational technology
• Embodied communication: Looking for systems that mean what they say
• In-corporating body language into NLP (or, More notes on the design of automated body language)
• The death of search (or, My dysfunctional relationship with Siri)
• Google’s response to Apple’s Siri: Buy Cleversense

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

In 1922, the Elmwood Button Co. commercialized a toy that could respond to voice commands. The toy, called Radio Rex, was a dog made of celluloid that would leap out of its house when you called its name: “Rex!” That was two decades before the first digital computer was even conceived, and at least three generations before the Internet would jet our lives from the real world into the virtual realms of e-commerce, social networks, and cloud computing. Radio Rex’s voice recognition technology, so to speak, was quite crude. Practically speaking, the vibration produced by the “r” in its name, when spoken loudly, would cause a thin metal blade to open a circuit that powered the electromagnet that held Rex in its house, causing Rex to jump out. A few years ago, I watched in awe one of the few remaining original Radio Rex toys in action. It was still working.

Some people recognize Radio Rex as the first speech recognition technology applied to a commercial product. Whether that could be called speech recognition or not, we have to agree that the little celluloid dog was probably one of the first examples of a voice controlled consumer robot. While rudimentary, I can imagine the delight and wonder that people felt when Rex responded to their own voice. Magic!

Indeed, speech recognition is something magical. That’s why I have spent more than 30 years of my life building machines that understand speech, and many of my colleagues have done the same. The machines we have built “understand” speech so well that there is a billion dollar industry based on this specific technology. Millions of people talk to machines every day, whether it is to get customer support, find a neighborhood restaurant, make an appointment in their calendar, or search the Web.

But these speech-understanding machines do not have what Radio Rex had, even in its own primitive simplicity: an animated body that would respond to voice. Today, social robots do. And even more: they can talk back to you, see you, recognize who you are and where you are, respond to your touch, display text or graphics, and express emotions that can resonate with your own.

When we consider voice interaction for a social robot, what type of speech and language capabilities it should have? What are the challenges? Yes, of course Siri and Google Now have paved the way to speech-based personal assistants, but despite their perceived popularity, is speech recognition technology ready for a consumer social robot? The answer is yes.

First, let me explain the difference among the speech recognition technologies used for telephone applications (à la “Please say: account, payments, or technical support”), for personal assistants (like Siri, Google Now, and the most recently Cortana) and for a social robot.

In telephone-based applications, the speech recognition protocol is synchronous and typically initiated by the machine. The user is expected to speak only during well-determined intervals of time in response to a system prompt (“Please say …”). If the user does not speak during that interval, or if the user says something that is not encoded in the system, the speech recognition machine times out, and the system speaks a new prompt. This continues until something relevant is said and recognized, or either the machine or user lose their patience and bail out.  We have all experienced this frustration at some point.

In telephone-based systems, any type of information has to be conveyed through the audio channel, including instructions for users on what to say, the information requested, and the possible clarification of any misunderstanding between the human and the machine (including the infamous “I think you said …”). Anything spoken has to be limited in time, in a rigid, turn-taking fashion between the system and the user. That is why telephone-based systems are so “clunky”, to the point where more often than not, they are quite annoyingly mechanical and repetitive. Although I have built some of the most sophisticated and well-crafted telephone-based speech recognition systems for over a decade — and these systems are used by millions of people every week, — I never heard anyone say: “I love my provider’s automated customer care service. It is so much fun to use it that I call it every day!”

Then came the smartphone. The fact that a smartphone includes a telephone is marginal. A smartphone is a computer, a camera, a media appliance, an Internet device, a computer game box, a chatterbox, a way to escape from boring meetings, and yes, also a telephone, for those who insist on making calls. Although it hasn’t happened yet, smartphones have the potential to make clunky, telephone-based speech understating systems obsolete. Why? Because with a smartphone, you are not forced to communicate only through the narrow audio channel. In addition to speech, you can enter text and use touch. A smartphone can talk back to you, and display text, images, and videos. The smartphone speech recognition revolution started with Siri and Google voice search. Today, more and more smartphone services are adopting speech as an alternative interface blended with text and touch modalities.

The distinction between telephone-based, audio-only services versus smartphone speech understanding is not just in the multi-modality of the communication protocol. The advent of fast broadband Internet has freed us from the necessity of having all the software on one device. Speech recognition can run in the cloud with the almost unlimited power of server farms and can truly recognize pretty much everything that you say.

Wait a minute. Just recognize? How about understanding the meaning of what you say?

There is a distinction between recognition, which is the mere transcription of the spoken words, and understanding, which is the extraction and representation of the meaning. The latter is the domain of natural language processing. While progress in speech recognition has been substantial and persistent over the past decades, natural language has moved forward more slowly. Siri and its cloud-based colleagues are capable of understanding more and more, and even some of the nuances of our languages. The time for speech recognition and natural language understanding is finally ripe for natural machine and human communication.

But…is that all? Is talking to our phones and tablets or open rooms — as in the upcoming home automation applications — the ultimate goal of spoken communication with machines?

No. Social robots are the next revolution.

It has been predicted by the visionary work of pioneers like Cynthia Breazeal, and corroborated and validated by the recent announcements of social robot products coming to market. This is made possible by the confluence of the necessary technologies that are available today.

Social robots have everything that personal assistants have—speech, display, touch—but also a body that can move, a vision system that can recognize local environments, and microphones that can locate and focus on where sounds and speech are coming from. How will a social robot interact with speech among all the other modalities?

We went from prompted speech, like in the telephone systems, to personal assistants that can come to life on your smartphone.  For a social robot, there should neither be a “speak now” timeout window, nor the antiquated  “speak after the beep” protocol, nor a button to push to start speaking. Instead, a social robot should be there for you all the time and respond when you talk to it. You should be able to naturally cue your robot that you are addressing it by speaking its name (like Star Trek’s “Hello Computer!”) or simply by directing your gaze toward it while you talk to it. Fortunately, the technology is ripe for this capability, too. Highly accurate hot-word speech recognition—like in Google Now—and phrase spotting (a technology that allows the system to ignore everything that is spoken except for defined key-phrases) are available today.

While speech recognition accuracy is always important, we should always consider that social robots can have multiple communication channels: speech, touch, vision, and possibly others.  In many cases, the different channels can reinforce each other, either simultaneously or sequentially, in case one of them fails. Think about speech in a noisy situation. When speech is the only alternative, the only recourse is to repeat (at nauseam) the endless “I did not understand what you said, please say that again?”  For social robots, however, touch and gesture are powerful alternatives to get your intent across when placed in situations where speech is difficult to process.

In certain situations, two alternative modalities can also complement each other. Consider the problem of identifying a user. This can be done either via voice with a technology, called speaker ID, or through machine vision using face recognition. These two technologies can be active at the same time and cooperate, or used independently — speaker ID when the light is too low, or face ID when the noise is too high.

Looking ahead, speech, touch, and image processing can also cooperate to recognize a person’s emotion, locate the speaker in the room, understand the speaker’s gestures, and more. Imagine the possibilities when social robots can understand natural human behavior, rather than the stilted conventions we need to follow today for machines to understand what we mean.

I have spent my career working at the forefront of human-machine communication to make it ever more natural, robust, textured – and, yes, magical. Now, we are at the dawn of the era of social robots.  I am thrilled to help bring this new experience to the world.  Just wait and see.

If you liked this article, you may also be interested in:

• Embodied communication: Looking for systems that mean what they say
• In-corporating body language into NLP (or, More notes on the design of automated body language)
• The death of search (or, My dysfunctional relationship with Siri)
• Google’s response to Apple’s Siri: Buy Cleversense

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Just before entering the tunnel a child attempts to run across the road but trips in the center of the lane, effectively blocking the entrance to the tunnel. The car has only two options: continue straight, thereby hitting and killing the child, or swerve, thereby colliding into the wall on either side of the tunnel and killing you.

With the help of Jason Millar, we turned this moral dilemma – called the Tunnel Problem -into a reader poll, and provided you with some of the results last week. Now we’re going more in-depth, to provide you with some insight into the qualitative responses we received.

As we started to analyze the responses from the poll, we found that more people (64%) would choose to have the car continue straight and kill the child than to have the passengers be killed, whereas the remaining 36% of people said the car should swerve and save the child. And almost half of the participants said that it was an easy choice to make.

This seems to imply that there is lack of consensus on what an autonomous car should do, and that there must be some stark differences in the reasons why someone would choose one versus another.

Continue straight and kill the child: When we asked people about their reasons for choosing to continue straight and kill the child instead of sacrificing their own lives, the most popular reason we received (32%) was that it’s the child’s fault for being at the unsafe location. Those with kids will tell you how hard it is to always watch over your child and make sure s/he is not at a wrong place at the wrong time. But our participants shared the view that their life should not be lost because of a child who should not have been in such a dangerous area. Similarly, 13% of people said that they just like living, and would always choose their lives over the lives of others.

Others (20%) put forth the view that the car should always prioritize its passenger’s safety over that of others. Some of these responses indicated a sense of ownership.

“I bought the car. It should protect me.”– Participant 87

Another 13% of the participants also said that the car should prioritize the passenger’s safety, but not necessarily because of their sense of ownership. These participants indicated that if the cars don’t always prioritize the passenger’s safety over safety of others, then fewer people will buy the cars and this will be worse for the society overall. They seem to assume that autonomous cars will result in fewer traffic accidents, which is an assumption shared by majority of people that we have polled previously.

“If the car does not always make its passenger’s safety a priority over that of others, I don’t think people would be able to trust the technology. Having a consistent priority makes the car’s behaviour more predictable as well, which has been shown to improve people’s perception of devices.” — Participant 114

Some other, less popular, responses included the idea that an adult person’s life is worth (economically) more than that of a child (5%) and that the swerving of the car may cause a greater, perhaps unforeseen, accident (2%).

Swerve and kill the passenger (you): In contrast to those who said the car should kill the child, the most popular reasons from those choosing the car to swerve and sacrifice the passenger were those who provided altruistic reasons, such as “I’ll always choose a child’s life than mine” (36%). Some of these altruistic reasons included the idea that, since the passenger (the participant) is an adult and riding inside a car, they will take the chances of survival despite the fact that the death of the passenger upon swerving is certain in this particular scenario. Similarly, 11% of the participants indicated that, perhaps similar to the storyline of the movie “I, Robot”, they would not want to live with the guilt.

“The passenger has to live with their choice. If it was my own child I would want to make that decision. I would still feel responsible if it was the car [that] “decided”” — Participant 34

Some people (14%) said that the child should be saved because the child has more years to live. Another 14% of participants said that the car should do what a person would do in the situation, which is to swerve. Yet another 14% did not provide a reason for their answer, but said that the car should be able to slow down in time.

In contrast to the people who said the car should kill the child because the car should always prioritize its passenger’s safety over that of others, 11% of those choosing the passenger to die justified it by saying that passengers are entering into an implicit ‘risk contract’ by getting into the car.

So, who should make these decisions in the first place?

When we first looked at the results of our data we found that 44% of the
people would choose to have the passengers, while 33% would support lawmakers, to make these decisions. In fact, only 12% of participants told us they thought the designer/manufacturer should be making the decision. We thought this might be because people don’t feel comfortable relying on others to make end-of-life decisions on their behalf, and trust themselves to make better choices.

We looked into this further too.

Passengers:

We analyzed the reasons people supported passengers to make these decisions. It turns out that the majority of the reasons (55%) share the idea that the passenger should have the freedom to make these life-death decisions.

Similarly, 12% and 10% of the reasons, respectively, mentioned the fact that the passengers are the ones most affected by the situation or that they have ownership rights (i.e., “my car, my decision”), and hence should be the one to make these decisions. Quite a few of these responses (14%) also expressed their distrust toward the technology.

An interesting response also suggested that people are implicitly making a moral choice by choosing to purchase one manufacturer’s car over another, each of which may have different value systems implemented in them, and emphasized the close link between design decisions and their impact on consumers’ decisions.

Lawmakers:

Those supporting lawmakers to make these decisions were divided more or less into three camps. The first (30%) is that lawmakers will allow for fair decision making, and are the most equipped to make impartial decisions than manufacturers or passengers.

Relatedly, 27% of the responses shared the opinion that lawmakers provide the most democratically legitimate decision making, while another 27% emphasized that the cars need to be governed by a universal or standardized set of rules so that their behaviours are made consistent. Others said that making such decisions is the job of lawmakers, and that the problem in question is essentially a legal issue, requiring lawmakers to be involved (12%).

Manufacturer/Designer:

Yet some people (12%) supported the idea that manufacturers should make these decisions. This was partially because they think that lawmakers should never be trusted (13%), but mainly because they felt manufacturers have the expertise and understanding of the technology necessary to make these decisions (63%).

Taking a closer look at our readers’ responses to the Tunnel Problem, we are learning that the design and regulation of autonomous cars will require far more stakeholder discussions than other technological devices that have pervaded our daily lives. Indeed, in line with what Millar suggested in his article introducing the tunnel problem, these results tend to suggest that there are limits to the decisions designers and manufacturers of autonomous cars should make on behalf of users. While discussing every single detail of a car’s design with all stakeholders would be a challenge to manufacturers, we are hopeful that the discussions on this topic we are having with you, dear readers and participants, will help make society’s journey towards our future with autonomous cars a smooth ride.

The result of the poll presented in this post have been analyzed and written by AJung Moon, Jason Millar, Camilla Bassani, Fausto Ferreira, and Shalaleh Rismani, at the Open Roboethics initiative.

If you liked this article, you may also be interested in:

• Reader poll: How would you like to interface with your autonomous car?
• Human error as a cause of vehicle crashes
• If death by autonomous car is unavoidable, who should die? Reader poll results
• Should autonomous cars be allowed to speed? Results from our reader poll
• Kids with wheels: Should the unlicensed be allowed to ‘drive’ autonomous cars?
• What should a robot do? Designing robots that know right from wrong
• Morgan Stanley reports on the economic benefits of driverless cars

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

“When the American people, through their Congress, voted for a twenty-six-billion-dollar highway program, the most charitable thing to assume is that they hadn’t the faintest notion of what they were doing.” So warned Lewis Mumford in 1958, two years after the inauguration of the U.S. Interstate Highway system. “Within the next fifteen years,” Mumford added, “they will surely find out.” The following decades indeed proved Mumford right.

As the “preposterously unbalanced program” pursued the utopian mirage of a city in which anyone could drive anywhere, anytime, and park at the destination, it destroyed much of the urban America it was meant to serve. Since the 1930s, as state highways funded by gasoline taxes entered cities, packed surface parking lots and parking garages erased much of America’s urban space.  The urban interstates accelerated the trend. At their worst, they were “pyramid building with a vengeance: a tomb of concrete roads and ramps covering the dead corpse of a city.”¹ If the consequences were not always so bad, it’s because local residents stopped some of the most destructive projects, and because some resourceful communities pursued alternative futures.

Autonomous vehicles can correct for these excesses—or exacerbate them. Getting this right will demand recovering a history we’ve lost, and escaping a history written for us by those with a stake in it.

Solving the Wrong Problem

Such destructive extravagance was sold as the rational product of applied science. It was indeed substantially rational in its methods, many of which were so routinized as to be almost automatic in their application: traffic demand measurements, level of service grades, and functional classification systematized highway engineering processes. But routinized programs can only implement solutions to the problems humans define.

Ludwik Fleck, the Polish scientist and philosopher of science, explained that “the formulation of a problem already contains half its solution.”² If we misstate the problem, we may preclude the best solution. The more effectively and the more zealously we solve the wrong problem, the worse the result. When bleeding and purging patients didn’t work, eighteenth-century doctors bled and purged them more—to the detriment of their patients. They got the problem wrong. To them, the problem was “how do we cleanse the blood and restore balance to the humors?” The destruction of American cities to accommodate automobiles, the urban sprawl surrounding these cities, and the loss of alternatives to driving were not the wrong solution. They were the right solution to the wrong problem. Autonomous vehicles can treat these symptoms or exacerbate them, depending upon how we formulate the problem.

In autonomous vehicles and other intelligent transportation systems, we may have a solution so powerful that we fail to pause and ask what problem such systems are best suited to solving. We may fail to ask whether the problem formulation we inherited is the right one. We may justify an emphasis on autonomous cars out of a misreading of history that tells us that we must begin with the assumption that Americans prefer to drive. Above all the neglect of history—or what is much the same, the uncritical acceptance of agenda-driven histories others have packaged for us—may deprive us of hard-earned experience. Experience is the parent of judgment. How strange, then, that so often we find innovators contending that innovation negates the validity of experience: “this changes everything.” Our solutions may be new but the problems of society—the problems of living well together—ultimately are not.

The problem formulations we inherit are the products of history. Born in the 1930s, accelerating to a crescendo in 1956, and persisting ever since, the dominant American surface transportation problem has in effect been: How can motorists be permitted to drive wherever and whenever they want, and to park at their destinations, with minimal delay and with reasonable safety?  In rural America this problem formulation was not unreasonable. In cities, however, it began as a revolution against older formulations that were antagonistic to automobiles.³ Because the private motor vehicle’s spatial demands made it incompatible with density, the new formulation had profound implications for cities.

Autonomous vehicles will be a powerful tool. But they cannot tell us what purpose they will serve.  The time to ask is now, before autonomous vehicles become common.

If we retain the problem formulation of the mid twentieth century, autonomous cars will offer us a better solution to the wrong problem.  Each car will safely travel faster, require less lane space (width and length), require less fuel, make better use of existing road and parking capacity, and demand much less attention from the driver. If total driving (vehicle miles of travel—VMT—per person) remained constant, the achievement would be spectacular.  But under the prevailing problem formation, per person VMT would not remain constant.

If engineers continue to seek to accommodate all of motorists’ demands, and if they accommodate such demands much more efficiently, each car may make much more efficient use of road and parking capacity, but total demands may rise so much that even more space will be needed for road surface and for parking. In the fully autonomous vehicle, as the driver need pay little or no attention to driving, driving time may become work or play time—in effect negating the time cost of travel. Autonomous cars might also safely travel much faster. Such changes might turn the 50-mile commute of today into the 100-mile commute of tomorrow. Today, people trying to travel by other modes—such as walking or bicycling—must contend with urban sprawl governed drivers’ perceptions of distance. How will they reckon with distances that have doubled again?  Presumably many of them too will resort to driving. However reluctantly they turn to it, their decision will be taken as a vote for driving.  Finally, as the skill demands of driving fall we’ll have more drivers. Such trends would mean that we would continue to rebuild the world for drivers, instead of asking what world we want to live in and conforming driving to it.

In 1865 William Stanley Jevons cautioned that more efficient steam engines would not conserve Britain’s coal supply; instead they would increase total national coal consumption because more enterprises would make more use of the more efficient engines.⁴  More recently, “Jevons’ paradox” has been independently rediscovered by each web user, who finds that faster connection speeds mean more total time spent online, not less. If intelligent systems accelerate vehicular “connection speeds,” Americans may spend more total time in vehicles, use them for even more tasks, and negate the space and fuel savings that autonomous vehicles might offer through a different problem formulation. Given difficult facts such as climate change, depletion of fossil fuels (or recourse to fracking, tar sands, and other controversial means of supply), urban sprawl, and the public health costs of physical inactivity, such trends would be cause for alarm.

History and Problem Formulation

In averting these trends, history is our greatest ally—and our greatest threat. History legitimizes some problem formulations, and in so doing delegitimizes others. Parties with agendas to advance tell versions of history that serve these agendas. But impartial histories, pursued with care by researchers with no financial stake in the result, and who welcome correction from each other, can expose and excise false formulations.

The most influential histories we have inherited were designed to serve agendas, however. For example, one of the first defenses of any effort to accommodate all driving demands at any cost is the assertion that Americans prefer driving.  More precisely, history allegedly shows that Americans in general have an unconditional preference for driving over alternatives.  Critics and defenders of the automobile agree that Americans have had a long “love affair with the automobile.” For the critics, the love affair is a misguided infatuation from which Americans must be rescued; for the defenders, the love affair is the free preference of a free people and must be honored as such.  But both agree that Americans prefer driving.

Yet no one on either side of this debate seems to recognize that the “love affair” metaphor is not a sociological fact, finding organic expression in a term of folk wisdom.  It was an invention propagated to serve a purpose. Introduced in 1958 in a criticism of the automobile industry (John Keats’ The Insolent Chariots), the phrase was readapted as a defense of the automobile in 1961 in a one-sided television history of the American car. Millions saw “Merrily We Roll Along,” an episode of NBC’s Du Pont Show of the Week (Du Pont owned a 23 percent share in General Motors, to which it sold varnishes and fabrics⁵). Host Groucho Marx told Americans the history of the automobile in the United States as a love affair between the American man and the (feminized) automobile. Love is blind; social critics can find fault with it but in a free society the will of the people must be honored. And love will find a way—whatever the costs.  In this little drama, critics of the automobile’s excesses become outdated, prudish chaperones.

Though its origins were soon forgotten, the love affair thesis and similar stories overwhelmed older stories of the automobile in the American city—many of them characterizing the car not as love object but as despised intruder.  Nevertheless the love affair thesis remains the dominant explanation of Americans’ extravagant accommodation of the automobile. If there is an official history of the automobile in the United States, this is it. Since 2003, visitors to the Smithsonian’s National Museum of American History in Washington, D.C., in the General Motors Hall of Transportation, have found the love affair thesis in exhibit form. Besides GM, major sponsors of “America on the Move” include the American Automobile Association, State Farm, and ExxonMobil; support from the American Public Transportation Association, the American Road and Transportation Builders Association, the Association of American Railroads, the National Asphalt Paving Association, and UPS is also noted. Acknowledging some of the costs of accommodating the automobile, the exhibit attributes the car’s dominance overwhelmingly to mass preference: in a free market of transportation modes, “Americans chose … the automobile.”⁶

The love affair thesis is essentially a free choice thesis. It is history written by those with a stake in history. It is an ex post facto justification. It is not an outright falsehood. Such lies seldom work. Instead it is a tactical distortion that sidelines appeals to common sense by appeal to a greater power—love. What’s lost in this stratagem is the negation of choice in an environment lacking good alternatives. Lock a man in a 7-11 for a week and study his diet. If we find that he eats a lot of processed food products, we can’t conclude that he has a thereby expressed an unconditional preference for them. Urban Americans chose the car only after a protracted struggle for control of the formulation of traffic problems—a struggle in which many of them fought on the losing side, and which the victors were a minority.⁷ Americans still choose the car—but they do so in an environment deprived of good alternatives. They choose not in a free market of equal alternatives, but in an environment in which drivers don’t pay the full cost of accommodating cars and in an environment built to accommodate cars at all costs.

Beyond Good and Evil

The love affair thesis, by which the car is always “good,” invites an equally fatuous rejoinder: the car is always “bad.” Too many have accepted the invitation. Those who do unwittingly support the love affair thesis by accepting its premise—that cars are either good or bad. Like any useful tool, the car has purposes to which it is ideally suited. It is particularly well suited to low-density areas and as a connector between transportation hubs. As a taxi or shared vehicle it can also be very useful in dense cities. But those with an interest in promoting cars succeeded in casting America’s transportation problem not as a problem of moving people but as a problem of accommodating cars everywhere—even to the point of rebuilding cities for cars. In so doing they diminished Americans’ range of transportation choices, as if their free choices could not be trusted.

Autonomous vehicles can serve the right solution to the right problem. In a city built for primarily people, and in which vehicles serve people, autonomous cars can valuably supplement integrated transportation systems in which each mode is suited to its purpose, in which transportation modes serve the city (not the other way around), and in which transportation success is measured by people moved and not by vehicles moved. They can serve a city in which more needs can be met without vehicles, in which vehicles can be shared, in which walkable distances can be conveniently walked, in which bicycles can connect homes and shops, and in which mass transportation services can make a virtue out of density. But before we make autonomous cars the solution, we must formulate the problem correctly. Until we do, we risk accelerating a journey to the wrong destination. If we rebuild the landscape for autonomous vehicles we may make it unsuitable for anything else—including walking. What kind of city do we want—and what kind of mobility will serve it best? Before we uncritically accept the answers we inherited from the past, let us reexamine the question.

[1] Mumford, “The Highway and the City,” Architectural Record 123 (April 1958), 179-86.

[2] Fleck, Genesis and Development of a Scientific Fact (1935; University of Chicago Press, 1979), 37.

[3] Peter D. Norton, Fighting Traffic: The Dawn of the Motor Age in the American City (MIT Press, 2008).

[4] Jevons, The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustionof Our Coal-Mines (London: Macmillan, 1865).

[5] Robert F. Freeland, The Struggle for Control of the Modern Corporation: Organizational Change at General Motors, 1924-1970 (Cambridge University Press, 2001), p. 4.

[6] “What Happened to Streetcars?” (exhibit sign), America on the Move, National Museum of American History.

[7] Norton, Fighting Traffic.

If you liked this article, you may also be interested in:

• An ethical dilemma: When robot cars must kill, who should pick the victim?
• Should autonomous cars be allowed to speed? Results from our reader poll
• How do self-driving cars work?
• Human error as a cause of vehicle crashes
• Smart vehicles are here: Can government keep pace? | NY Times Energy for Tomorrow Conference

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Last week I dropped by Aldebaran’s studio to get a glimpse of Pepper in action, and was pretty excited about this robot. But then I talked with Bruno Maisonnier, the CEO of Aldebaran. And then I got really excited: what Pepper represents is another iteration in the realization of the roboticists’ dream.

Aldebaran built Pepper for Japanese telecom company SoftBank, which will start selling the robot to consumers in Japan next February for about US $1,900. The robot will be produced by Taiwanese electronics manufacturer Foxconn (who manufactures the iPhone and other Apple products). So with the marketing presence, technical abilities, and hardware systems now at a consumer-grade quality, we’re one step closer to Rosie the Robot. Or Her. Or the Cylon uprising. Remains to be seen.

Emotional interaction, according to Bruno, is “everything.” We spoke briefly on June 13, 2014 and I was able to ask him about some of this technology, its socio-cultural impacts, and the future of this work for Aldebaran. Several years ago I had been hanging around the Paris studio of Aldebaran and had seen Romeo (and wrote about it and NAO in my book on robots), so I had some sense of what was coming, but I was not expecting the emphasis on affective computing methods that Pepper embodies.

MAISONNIER: Pepper is a fantastic dream I’ve had for years – an interactive robot you can have at home that’s still large enough to be a companion and not just a toy or a pet. At Aldebaran we have a specific concept. We want to help people with robots. We want them to be companion. To help people grow, have fun, and connect them to others.

So first you need to have a cute, nice robot – not just something to say, ‘Oh, that it is nice,’ but the essence of the robot is something that lives in your home. This is not for geeks, so design is our first and most essential part. We want a natural way to interact with the robot and not have a 200-page manual that people need to read. So we need people to be comfortable and interact easily with the robot. We humans have evolved to interact with other humanoid shapes. And sometimes, even without words you understand what the other person means and yes or no can be clearly indicated with body language. We can see if someone is saying yes but meaning no, and if you are saying yes when you are sad, or no when you are happy the message is totally different. So if I want the robot interaction to be natural the robot has to understand that.

MEADOWS: How do you do that? That’s a tall order.

MAISONNIER: These drivers for both understanding and expressing emotions are key to our design. NAO was the first emotional robot, with many possibilities, but many limitations because of its size. Pepper is a larger robot, and one of the consequences of this design decision is that it can move faster. You can have the robot follow you, or if it has to go into your bedroom to look for something it won’t take 20 minutes, and it will be able to open doors. If you want to interact with emotional context, then size is important; [Pepper’s size offers] a more human interaction, rather than talking with something the size of a mouse.

MEADOWS: Ok, but an android is a bad design for a robot because the function follows the form.

MAISSONNIER: But for Pepper the function is to interact with people. The majority of people in robotics are coming from industrial robotics; they’re building left-brain robots. I’m not interested in that. There are huge applications, but this is not what I’m interested in. We want right-brain robots for friends and companions – robots that are more like Jiminy Cricket.

MEADOWS: Here at Geppetto we feel much the same way. Now Romeo and NAO have legs. Pepper’s got wheels. Why?

MAISSONNIER: The main driver is that Pepper is an emotional robot, and we rarely use our legs for social interaction. While there are some detriments, like going up stairs, there are also benefits to the wheels, such as giving the robot a longer autonomy because it can carry a heavier battery. The goal of the robot is to help by teaching, being a health coach, monitoring, growing, etc. So it is more right-brain. Yes, the form follows function because the interaction with humans is the function. So you don’t need legs.

MEADOWS: So how are emotions used to guide the robot?

MAISSONNIER: Communication is emotion. You are an artist and know this. When you are speaking, only about 20-30% of what you say is in the words. But 70-80% is not words – all the other parts are emotions. So communication is emotion.

MEADOWS: What are the methods you’ve developed to convey this?

MAISSONNIER: We’ve invented an emotional engine that collects many different inputs and combines them in multi-modal approaches that use facial analysis, tone of voice, body language, gesture, small noises like laughter, and understanding the micro-signals that your body sends when you talk with someone. All that is feeding a higher level message, which might be that “she said yes but she means no” for example. This serves as the input to our dialogue engine, and we have an expressive engine that uses automatic body language in response. It has all the possibliities – hand, movements, sound, voice, etc – to express the correct message.

MEADOWS: Beautiful. What do you do with this platform?

MAISSONNIER: We’ve been speaking about the robot itself, and all that is part of our expertise platform, but on top of that are the applications so users or developers can build apps via our API. All that goes to the developers, who are then able to use it as they want. There are many ways to use this. For example, if you are designing an application to play chess, you can use the API to deliver messages on your chess program. The system can appear frustrated, or sense frustration at key moments in the game.

The developers are core to our strategy. Aldebaran has an app store and we confirm the quality of the app so you can download this to users, free of charge, who can download the application from the store. We have an atelier [a french term between workshop, gallery, and studio] where everyone can enter, meet with robots, experiment with them, and play with our applications. This will be the home of the developers.

MEADOWS: I love this! Perfect. Are they only online or can I visit them?

MAISSONNIER: We will have an Aldebaran Atelier in Paris, on 26 June, 2014 and two more will open in Tokyo in August. By 2015 we will have two in the US (New York and California).

MEADOWS: Changing the subject a little, you have a robot that has some incredible surveillant abilities. I think there’s a risk here in that systems may not respect privacy, or may be used for ends that don’t align with the end-user. As I’ve written about on RoboHub, where I ask if surveillance is the new business model for consumer robotics, Andy Rubin is taking the robotics effort in the same direction he took the Android effort. This not only changes the landscape for Aldebaran, but it means that you have to address questions of privacy. What Is Google doing?

MAISSONNIER: I don’t know. It is opening up the [robotics] market. They will need some time before having ready robots because the culture of software is not the culture of hardware. Google is a software company, but though they have bought these companies this is not an immediate solution. Building a $1m robot is not the same as building a $1k robot .. they will need time. Their business model, as you said, is to sell advertisements. Do you want to have a spying robot at home?

MEADOWS: Well, most of us don’t seem to mind. Many people still use Google. Why is spying on me with my email different from spying on me with my robot?

MAISSONNIER: One is autonomous. If you send your mail you don’t see it flying around your house checking your books, checking your clothes. It has to be friendly, but as important is that it needs to be your friend that can protect you. You have to be sure it is on your side.

MEADOWS: Autonomy and invisibility are quite different. And a robot can do things that a user may not perceive. After all, email could be called a spybot as easily as a bots.txt file.

MAISSONNIER: This kind of thing will exist. If other robots like Aldebaran exist then between a spying robot and a non-spying robot, people will choose the right one. People will chose and we will settle the rules that we don’t want spying robots. I don’t want them, you dont’ want them. We would put a physical bridge, a switch, that will block communication and ensure privacy. That way people can say, “I want to authorize my robot to communicate with the outside world or not.”

MSM: I hope so. Where will people be able to find Pepper?

MAISSONNIER: Thousands of Peppers will be in SoftBank stores in Japan.

MEADOWS: I understand it will be about $2000, correct?

MAISSONNIER: Yes, for Pepper standalone, after that you can get insurance, monitor modules, repair modules, content, etc. These added components can be important. For me, the next step is to add content, applications in our application store – so a huge community of people will become interested in joining our adventure.

And what an adventure it will be. We look forward to seeing what great inventions Aldebaran turns out next.

If you liked this article, you may also be interested in:

• SoftBank + Aldebaran = Pepper
• NAO Next Gen now available for a wider audience
• My robot is smelling my dirty laundry (or, Notes on privacy, PRISM, and home service robotics)
• Robot love: Spike Jonze’s new sci-fi film ‘Her’ may be closer to reality than you think
• Is surveillance the new business model for consumer robotics?
• Deep Learning creating jobs in Apps, wearable tech and robotics

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

It is a fantastic time for technology. We live in a more connected world, and compared to even a few decades ago, we have vastly improved access to information and content, and have dramatically expanded our ability to connect with one another in interesting new ways to socialize despite time and distance.

As much as I love what technology does for us, and it certainly does quite a bit, our relationship with technology can still be dramatically improved.

Technology can feel dehumanizing. Technology often demands that we think and act more like machines to use it. It treats us like technology, beeping, buzzing, and pushing data and information at us without concern for politeness. It interrupts our conversations, not caring if we understand the information, or determining if the information is wanted. I let my son play on my smartphone once, and now I’m rewarded with daily updates about zombie harvesting – enough! We need to do better.

We need to humanize technology so that it treats us the way we want to be treated.

But there is an even deeper reason to improve this interaction. My fundamental gripe with technology is that it fails to support a more holistic human experience. It falls short in giving people a personally meaningful, emotionally engaging experience.

This shortfall actually limits the ability of technology to support and empower us to succeed, thrive, and grow.

Really?

Yes. Here’s why.

People think, feel, and act not just because of information, but also because of personally meaningful experience. Things have to matter to us, not just inform us, to effect real change.  There is a rich scientific literature on the role of emotion in intelligent decision-making and behavior change.

People who make careers of helping other people — educating others, helping to heal or care for others, or helping people to take better care of themselves — all know the power of high touch on positive human outcomes. Learning new knowledge and skills opens opportunities for growth. Adopting behaviors that keep you healthier increases your chances of thriving as you age. Forging and maintaining stronger relationships with those you love promotes mental and emotional wellbeing. Your life is better when you can do these things.

We should care about these things at face value. And there is urgency to do so.

We are facing juggernaut societal challenges where we cannot rely solely on our institutions to take care of us, to educate us, to keep us healthy. It is too expensive and the growing demand continues to outpace available institution and human resources. We see the headlines: the education crisis, the healthcare crisis, the eldercare crisis, and more.

Millions of people are grappling with these issues every day, and we can help relieve the crushing burden on our institutions by empowering people in their homes.

My vision is that:

… Even in the most time-crunched families, parents will have a reliable, high-quality partner in education for all children. Including our youngest learners who shall enter school ready to learn, or children with special needs, receptive to the quality education they need.

… Those people who struggle with health or chronic disease issues will have the right kind of tools to change behavior, and can independently manage their health and improve their treatment.

… Elders will be able to age independently in their homes with the help of a technology that feels much more like an attentive companion than yet another digital tool or a “Big Brother” monitoring system, relieving pressure on oversubscribed institutions, and remain emotionally connected to their families and loved ones despite distance.

And so much more.

To realize this vision, we all know that technology must be part of the solution. It’s affordable. It’s scalable. It’s accessible at home. This is a good start. But it needs to be more.

Personal technology needs to go beyond giving us access to information anywhere we are. It needs to go beyond opening a communication channel between people. It needs to go beyond being easy to use. It needs to go beyond being cool and desirable. All of these attributes are still critical pieces. But they do not yet form the full answer.

Technology needs to support what people need to be the most empowered to effect positive change in their life and for their loved ones. High tech must support high touch engagement for the best and most lasting results. Only then will technology maximally empower our human ability to fully engage with it — how we experience, think and behave at the intersection of our cognitive, social, emotional and physical capabilities — to succeed, thrive, and grow with technology like never before.

Technology needs to be humanized.

Computing has gone through several waves, each resulting in billion dollar industries and impacting millions if not billions of people’s lives on global scale. We’ve benefitted from the wave of information, the wave of mobility, the wave of social media. We’re seeing more and more wearable computing and the Internet of Things that combines these three.

Now, we are on the threshold of the next wave of computing: emotion.  And social robotics is a particularly powerful expression of this next wave.

This is what social robotics is about. This is why it is so transformative. This is why it is revolutionary.

This is why it will change your life.

This post was originally published on blog.myjibo.com, where Cynthia Breazeal will be curating articles about social robots.

If you liked this article, you may also be interested in watching Cynthia’s ROBOTS: From imagination to market talk, or in reading the following articles:

• Robots14 brings it all together
• Robots Podcast: A Code of Ethics for HRI Practitioners
• What should a robot do? Designing robots that know right from wrong
• Consumer AI devices entering the marketplace

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Life and death decisions make interesting thought experiments. When you throw an autonomous car into the mix, things get even more interesting.

A couple of weeks ago Jason Millar wrote about such a scenario called the Tunnel Problem. The Tunnel Problem goes something like this:

The Tunnel Problem: You are travelling along a single lane mountain road in an autonomous car that is approaching a narrow tunnel. You are the only passenger of the car. Just before entering the tunnel a child attempts to run across the road but trips in the center of the lane, effectively blocking the entrance to the tunnel. The car has only two options: continue straight, thereby hitting and killing the child, or swerve, thereby colliding into the wall on either side of the tunnel and killing you.

If you are the passenger in an autonomous car, and you suddenly find yourself facing a tunnel problem as described above, how should the car react? And who should make the call on how the car behaves in such scenarios to begin with?

With the help of Jason Millar, we decided to pose these questions to you. Our reader poll was wildly popular, thanks to all your support. We received responses from over 110 participants, 20 female and 93 male participants, most of whom (43%) are between 25 and 34 years old.

We are very excited to share the results with you here:

If you find yourself as the passenger of the tunnel problem described above, how should the car react?

The Tunnel Problem was set up in such as way that there are only two outcomes: going straight kills the child, whereas swerving kills you. Maybe it’s not that surprising to you that the majority of the participants (64%) said that the car should continue to drive straight and kill the child.

But it was surprising to some of us that 36% of the participants said the car should swerve and kill them instead. Were those cases of altruism? Why would some people choose to save themselves, while quite a significant number of other people choose to save the child?

We knew you’d be curious about this. So, we also asked our participants to tell us reasons for their answer to this question. We collected a very interesting set of responses for both options and we’re currently mulling over the data. Due to time constraints and our interest in getting the analysis done properly, we’ll be posting our analysis of the reasons next week.

How hard was it for you to answer the Tunnel Problem question?

We thought that most people would find the Tunnel Problem quite difficult to answer. It’s an ethical dilemma with no obvious answer after all. But boy, were we surprised. Roughly 48% of respondents said that it was an easy question to answer, whereas 28% and 24% said it was moderately difficult and difficult, respectively.

More interestingly, the percentage of people easily making the decisions were spread fairly evenly between the two options. A total of 47% of people who believe that autonomous cars should continue straight said that it was an easy question to answer, whereas the percentages were around 51% for those choosing to swerve and kill the passenger.

This is interesting because it implies that people are pretty confident in making a decision on this regardless of whether they believe the car should kill the child or themselves (the passenger). This also could mean that manufacturers, designers, lawmakers, or whoever may be making the decision on how a real Tunnel Problem-like scenario should be handled by autonomous cars probably can’t ignore the opinions of people who would rather have the car to swerve in such scenarios.

So, who should be deciding how the cars should behave in such scenarios anyway?

Who should determine how the car responds?

Most participants told us that either the passenger (44%) or lawmakers (33%) should decide how the car responds to such Tunnel Problem scenarios. This might make things tough for manufacturers or designers, who were supported by only 12% of our participants.

While manufacturers are the ones who will be designing and implementing how a car responds to different driving scenarios, including the Tunnel Problem, the design decisions will have to be tightly coupled with other stakeholders of the technology before the technology hits the market — perhaps much more so than they currently are.

Interestingly, while we found a significant support for lawmakers to be the decider of this for people 44 years or younger, none of the people 45 and above supported them.

But why are people saying that the passenger should be making this decision, or the lawmakers over the manufacturers/designers? Are we seeing some effects of distrust to the upcoming technology? We’ll discuss the reasons for people’s answers to this question on our next week’s analysis post.

The result of the poll presented in this post have been analyzed and written by AJung Moon, Jason Millar, Camilla Bassani, Fausto Ferreira, and Shalaleh Rismani, at the Open Roboethics initiative.

If you liked this article, you may also be interested in:

• An ethical dilemma: When robot cars must kill, who should pick the victim?
• Reader poll: If a death by an autonomous car is unavoidable, who should die?
• Should autonomous cars be allowed to speed? Results from our reader poll
• Kids with wheels: Should the unlicensed be allowed to ‘drive’ autonomous cars?
• What should a robot do? Designing robots that know right from wrong
• Morgan Stanley reports on the economic benefits of driverless cars

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

There may be times when an accident or a death is unavoidable while an autonomous car is controlling the wheel.

What should an autonomous car do when such situation arises? How should the designers of the cars program them to respond? This week, we introduce the Tunnel Problem, which describes one such situation and has been a topic of serious debate for philosophers as well as those watching the technology carefully. Let us know what you think by participating in our poll.

If you liked this article, you may also be interested in:

• Should autonomous cars be allowed to speed? Results from our reader poll
• Kids with wheels: Should the unlicensed be allowed to ‘drive’ autonomous cars?
• What do people think about autonomous cars? Results from our reader poll
• What should a robot do? Designing robots that know right from wrong
• Morgan Stanley reports on the economic benefits of driverless cars
• The autonomous driving r/evolution: Call to contribute to Robohub Focus

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Our previous poll, which asked (among other questions) whether kids should be allowed to ride in autonomous vehicles by themselves, revealed that responsibility is a key issue for most people. Are we concerned about who would be responsible when things go wrong? To prod at the issue of responsibility more deeply, in our most recent poll we asked how strictly an autonomous car should follow the speed limit, and if it gets a ticket for speeding, who should be held responsible.

How strictly should an autonomous car driving in a city follow the speed limit?

Though many people drive faster than the speed limit, most drivers know that limits are there for good reasons. But that doesn’t mean we should get a speeding ticket every time we go 1km/h above the limit. There’s a window of speeds that are typically tolerated by traffic enforcement officers, and that makes our driving experience much less stressful.

But when it comes to autonomous cars in city driving scenarios, it seems that people aren’t willing to them much wiggle room. In fact, 33% of the participants from our poll said that autonomous cars should never go above the speed limit, and 21% of the participants said that it should be allowed to deviate from the limit only slightly (up to 5km/h or 3mph). Only 11% of the participants said that the car should be able to deviate quite a bit (up to 20km/h or 12mph) during city driving.

Interestingly, 18% said that autonomous cars should not be subject to the same speed limits as human-driven cars. Does that mean the cars should have a higher speed limit, or lower? It’s impossible for us to find this out based on the poll results. But we could imagine autonomous cars having on-board speed limit algorithms that automatically determine safe driving speeds for different road conditions, environment, its calculated momentum (thanks Robohub for this idea) etc., regardless of the actual speed limit for the road. Maybe that would lead to more safe and efficient driving in general.

If a speeding ticket was issued, who should be responsible?

Let’s say that an autonomous car is designed to be able to go above the speed limit. While autonomously driving with an adult passenger on a highway, it exceeds the speed limit. The passenger is not the owner of the car. If a speeding ticket was issued, who should be responsible for the violation of the traffic law?

It seems that, when it comes to the responsibility question, people are quite torn about it. While 33% said that the manufacturer should be responsible, 24% said that the passenger should be responsible and 14% said that the owner should be. Not surprisingly, only 5% said that the autonomous car should be responsible.

More interestingly 24% of the participants chose ‘other’ and provided a conditional answer to this question, perhaps hinting at the complexity of figuring out responsibilities when it comes to things that autonomous machines do. Most people who gave us a conditional answer said that whoever has allowed the car to speed (perhaps by modifying one of the car’s operating settings) should be responsible, whether it be the owner, passenger, or the manufacturer. Some have also said that autonomous cars should not be issued traffic tickets, period.

For now, it looks like most people are willing to blame the manufacturer if anything goes wrong, even if it’s just violating speed limits.

The result of the poll presented in this post have been analyzed and written by AJung Moon, Camilla Bassani, Fausto Ferreira, and Shalaleh Rismani, at the Open Roboethics initiative.

Learn more about Nate’s wacky life at his Website.

We conducted two polls last month in collaboration with the Open Roboethics initiative to get a sense of what people think about autonomous cars. Our polls started some interesting discussions around the topic of the emerging technology.

To go a step further, we’d like to poke around the topic from a different angle: How strictly should autonomous cars adhere to traffic laws? Many of us know that speed limits are there for a reason, and many of us go just a tad bit (or a lot, for some) above it. If an autonomous car gets a speeding ticket, who should be paying for it? Let us know what you think by taking the poll below.

If you liked this article, you may also be interested in:

• Kids with wheels: Should the unlicensed be allowed to ‘drive’ autonomous cars?
• What do people think about autonomous cars? Results from our reader poll
• What should a robot do? Designing robots that know right from wrong
• Morgan Stanley reports on the economic benefits of driverless cars
• The autonomous driving r/evolution: Call to contribute to Robohub Focus

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Reader poll results: Earlier this month, when we asked people about your general thoughts on autonomous cars, we found that one of the main advantages of autonomous cars is that those who are not licensed to drive will be able to get to places more conveniently. This led us to wonder more about who should be able to drive an autonomous car.

We asked three questions through Robohub to find out more. Here’s what you, dear readers, have said.

Should a child under the legal driving age be allowed to ride driverless cars alone?

Remember the first time your parents handed you their car keys, or took you out for your very first driving lesson? For some of us, that moment came with our parents beaming aloud expressions of uncertainty, anxiety, and worry. Some of this adult/parental psyche may be at play with this question.

About half of the participants (52%) said that children under the legal driving age should not be able to ride driverless cars. This is not entirely surprising. Currently, under driving regulations, children under a certain age (typically late teen years) are not allowed to drive cars because we have reasons to believe that it is not entirely safe to let them drive. By allowing a child to ride autonomous cars alone, people may be concerned about scenarios where the car makes an error or requires the assistance of a human decision-maker during an emergency situation. Interestingly, 38% of the participants believe that children should be able to ride driverless cars alone and the other 10% also think that children should be able to drive autonomous cars with proven technology and specific training. This brings us to a fairly even split in opinion on the issue of children driving autonomous vehicles.

The results may not mean that 48% of the participants would be comfortable putting a newborn baby in an autonomous car to be delivered to his/her grandparents’ house. But it could mean that with a proven technology and some training, the legal driving age could be lowered for ‘driving’ autonomous cars. It makes sense that a shift in driving age would depend on the capability and reliability of the technology. For example, if all cars today had a high probability of breaking down in the middle of the road, then our driver’s license exams may have included a preliminary car mechanics test.

For now, it seems that people are more hesitant to put children in autonomous cars alone. It would be interesting to see if this will change as the technology drives out onto the road and demonstrates its safety and reliability.

Should a senior who no longer has a legal driving license be allowed to ride driverless cars alone?

Compared to the case of the underage drivers, it seems that the majority of the participants (67%) consider it acceptable to have a senior with no legal driver’s license ride an autonomous vehicle alone. Perhaps our participants expect a senior who has had a driver’s license to be able to better handle any emergency or unexpected situations than children, since they have driving experience to rely on if necessary. However, it is possible that some of the seniors are without license due to low cognitive and/or physical capabilities. In such cases, the concerns over the rider being able to handle emergency/unexpected situations is not different from the above unlicensed child rider situation.

This may be one of the reasons why 26% of the participants are not in support of unlicensed seniors riding the autonomous cars alone. However, similar to the responses to the first question, 7% of the participants thought that they would answer yes to this question only if there are limitations placed on where the senior would be allowed to ride the vehicle and whether they would have to pass some type of training to ride the vehicle.

Should a legally blind person be allowed to ride driverless cars alone?

Interestingly, the split of the votes for this question lies somewhere between the above two questions. 58% of the participants answered “yes” while 37% said “no” and the remaining 5% answered with a conditional “yes”. So why is a significant portion of the responses affirmative considering that being able to see is one of the most essential functions we rely on when we drive?

Perhaps people expect the legally blind driver to be able to receive enough information and be able to make informed driving decisions to handle emergency or unexpected situations. It maybe that people are in support of the blind driver scenario because the benefits of driving outweigh the risks for legally blind persons, more so than for a child or a senior. Compared to the case of the underage driver, a legally blind person (assumed adult) is deemed to have better decision making abilities and able to take responsibilities, which are both important requirements for a driver besides being able to perceive the environment.

Drawing a line on who should and should not be able to ride an autonomous vehicle seems to depend on a number of factors, and that doesn’t really include whether the individuals are legally licensed to drive under today’s regulations. Based on the results, the capability and reliability of the autonomous vehicles and the cognitive and physical ability of the rider are likely to change the way we allow different individuals to ‘drive’. One thing is for certain: regulations on who can drive will have to be reconsidered once autonomous vehicles start roaming the streets.

Share your opinion and take our next reader poll: Should autonomous cars be allowed to speed?

The results of the survey presented in this post have been analyzed and written by AJung Moon, Camilla Bassani, Shalaleh Rismani and Fausto Ferreira at the Open Roboethics initiative.

If you liked this article, you may also be interested in:

• What do people think about autonomous cars? Results from our reader poll
• What should a robot do? Designing robots that know right from wrong
• Morgan Stanley reports on the economic benefits of driverless cars
• The autonomous driving r/evolution: Call to contribute to Robohub Focus

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Two weeks ago we published our first reader poll in collaboration with the Open Roboethics initiative in order to find out more about what people think about autonomous cars. 

Of the many benefits that may come out of having autonomous cars on the road, one of the main advantages could be that those who are not licensed to drive a car will be able to get around more conveniently. But how comfortable are you with the idea of unlicensed persons as the only passengers in an autonomous car? Would you feel comfortable letting your eight-year-old daughter ride an autonomous car alone to get to school? How about those who are legally blind?

Let us know what you think by taking the readers’ survey below.

If you liked this article, you may also be interested in:

• What do people think about autonomous cars? Results from our reader poll
• What should a robot do? Designing robots that know right from wrong
• 5 areas in robotics that will transform society and their economic impact
•  Human error as a cause of vehicle crashes
•  What does the UK public think about robots? Sciencewise wants to know

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

What do you think are the main advantages of owning an autonomous car?

Perhaps this is unsurprising, but “Less traffic accidents!” seems to be the general consensus here. Over eighty percent of all respondents (83%) said that one of the main advantages of autonomous cars is reduction of the number of traffic accidents. The next set of popular answers were that autonomous cars will free up time and energy spent on driving (77%), allow those who are not licensed to drive will be able to get to places more conveniently (71%), and that it would reduce traffic congestion (67%). One point that surprised at least some of us was that only 40% of the respondents consider improvements to taxi and car-sharing services as a main advantage.

This may be surprising because, some of us current users of car-sharing services or frequent customers of taxi-cabs could easily imagine the improvements autonomous cars could have (e.g., no need to park shared cars at specific locations). But it is likely that more people have their own vehicles and may not consider this improvement as one of the main advantages. We also received a wide range of interesting responses from those who told us about ‘other’ advantages of the technology (11%). The responses range from “it will be cool!” – yes, we agree – to specific statements about fuel efficient driving, being able to ride a car while intoxicated/texting/eating/working, and the potential to improve delivery services and reducing shipping and delivery costs.

What is the maximum amount (USD) you would pay extra for a fully autonomous car?

Given that most people chose at least one advantage to autonomous cars, it was interesting to find out how much people were willing to pay for the technology. When asked about how much they would be willing to pay for a fully autonomous car, 66% of the respondents said that they would pay over $3000 (USD) in addition to what a conventional version of the car would cost. Only 5% said that they would never buy an autonomous car, while 12% said that they would buy the car regardless of the price. This is actually a very different result compared to a study conducted by Accenture Research in 2010, in which they reported that 51% of people would not feel comfortable using an autonomous car. It’s possible that people’s attitude about autonomous cars have changed over the 4 year period, or that our survey attracted more people from the technology industry given that majority of Robohub’s readers are technology enthusiasts or working in technology sector.

Should an autonomous car be easily identifiable?

According to our survey, 61% of people think that autonomous cars should be easily identifiable, similar to taxicabs and police cars. This made us raise questions about why most people would want to identify autonomous cars. Is it for having the bragging rights to show off what a cool car you drive? Is it because people want to be extra careful, or maybe less careful(?), when driving within the vicinity of an autonomous car? Or is it that traffic policing could be a nightmare somehow if police officers couldn’t tell apart autonomous cars from conventional cars? Maybe people think that it doesn’t hurt to make them distinguishable, whereas not being able to distinguish them from conventional cars might have negative implications.

Over the two-week period, we collected a total of 114 responses, which we think is amazing given that this is the very first poll of this sort ORi has worked on. If you didn’t get to participate in the poll this time around, don’t be disappointed. We will be releasing our reader polls every other Tuesday on Robohub (yes, that includes tomorrow), so you can check back and let us know what you think.

The results of the poll presented in this post have been analyzed and written by AJung Moon, Camilla Bassani, Shalaleh Rismani and Fausto Ferreira at the Open Roboethics initiative.

Today we drive our cars. In the future they’ll do the driving.

Autonomous cars are no longer a far-off futuristic dream, but something that we can expect to see on the road within the next decade.

But putting autonomous cars on the road requires a lot work, not only in getting the technology ready, but also in figuring out how we want the technology to shape the way we live. To get your help in shaping the future of the technology the Open Roboethics initiative, a roboethics think tank, with the help of Robohub, will be hosting a series of questionnaires.

Share your opinion with us by taking our survey below. We will be sharing the results on Robohub!

If you liked this article, you may also be interested in:

•  5 areas in robotics that will transform society and their economic impact
•  Human error as a cause of vehicle crashes
•  What does the UK public think about robots? Sciencewise wants to know

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Guest talk in the ShanghAI Lectures, 2010-12-16

The lecture starts with a short introduction to the Interactive Robots and Media Lab and the United Arab Emirates. Then, it continues by exploring some basic requirements towards creating Situated Conversational Assistants, i.e. devices with sensing, actuation, and spoken natural language which can assist humans in various tasks.

A concrete example of such a device is presented: Ripley the Robot, a manipulator robot with vision and speech that can serve motor commands, answer questions about the current or past situations, and get information about the current state of the world through language. In the context of such devices, a number of considerations are introduced, which then lead to the Symbol Grounding Problem, a philosophical problem which is shown to be at the heart of attempts towards building such embodied agents that can talk about their surroundings – which cannot just “plug-and-play” with traditional NLP approaches.

The symbol grounding problem is discussed, as well as its relation to semantics and semiotics, and then three practical pathways towards real-world solutions to the problem that promise to enable wider application of Situated Conversational Assistants are introduced. Then, Grounded Situation Models are briefly discussed, followed by a very quick glimpse of other requirements towards conversational robots.

The lecture finishes with a brief look at the FaceBots social robots, which utilize and publish social information on the internet in order to create sustainable human-robot relationships, as well as the Ibn Sina arabic speaking conversational robot and the modalities available for tele-participation in the interactive theatre that is built around him.

The ShanghAI Lectures are a videoconference-based lecture series on Embodied Intelligence, run and organized by Rolf Pfeifer (from 2009 till 2012), Fabio Bonsignorio (since 2013), and me with partners around the world. 

https://www.youtube.com/watch?v=phL1-FiRwUQ

Dr. Nikolaos Mavridis, PhD from the Massachusetts Institute of Technology, has taught, written about, researched, and built Intelligent Systems and Robots, having been active in the area since his early youth. Currently he is serving as Ass. Professor at New York University in Abu Dhabi. He is the founder of IRML (the Interactive Robots and Media Lab), which achieved wide publicity for “Ibn Sina”, the world’s first Arabic-Language Android Robot, as well as “FaceBots”, Microsoft-award-recipient Social Robots which access info and publish on FaceBook. His past work includes “Ripley”, a language-learning robot with abilities comparable to those assessed by the token test, a test administered to 3-year-old children. He is a member of the IEEE, has served in numerous leadership positions in the past, is now a TEDx curator and has been a TEDx speaker twice.

Watch Dr. Mavridis at:

• TEDx Athens “One Thousand Eyes, One Thousand Hands”
• TEDx Al Ain “Growing Robots in the Desert”

The ShanghAI Lectures have brought us a treasure trove of guest lectures by experts in robotics. You can find the whole series from 2012 here. Now, we’re bringing you the guest lectures you haven’t yet seen from previous years, starting with the first lectures from 2009 and releasing a new guest lecture every Thursday until all the series are complete. Enjoy!

Posting on the Slate blog Future Tense, James Bessen takes issue with the notion that technology causes unemployment, illustrating his point by debunking a pair of frequently cited examples, textile workers in the early nineteenth century and telephone operators during the mid-twentieth century.

In a response titled “Luddites Are Almost Always Wrong: Technology Rarely Destroys Jobs” on TechDirt’s Innovation blog, Bessen’s thesis is roundly applauded, but he is taken to task for failure to make the connection between the process which prevents net job destruction (the creation of new jobs) and reasonable access to intellectual property, currently endangered by nonpracticing patent owners (a.k.a. “patent trolls”).

With a background in mechanical engineering and an interest in design, engineering and working with kids, I happened into robotics education – and now I’ve been happily teaching and involved for five years.

I started out teaching Lego Mindstorms at a creative, after-school robotics program called Wizbots. After three years of teaching Lego Mindstorms to over 1000 kids, I had a good idea of its advantages and disadvantages. The advantages? Durable and great for the imagination. The disadvantages? If you weren’t an expert LEGO builder it’s a bit intimidating, it’s expensive, and you are stuck in a graphical programming world with no easy transition to learn real programming.

After three years of teaching, I started working with the robotics company Willow Garage to design an exhibit for The Tech Museum with the $400,000 PR2 robot. I helped design the software and interactive experience that had guests from 2 years to 99 years programming the robot. Guests created and saved poses by moving sliders, and then saw their code being composed in real time. We saw everything from the PR2 dancing the Macarena to performing Shakespeare.

I loved the fact that the PR2 inspired kids to get into robotics and lessened the intimidation of programming – it’s too bad that PR2’s size and price tag makes it impossible for a user to continue the learning experience at home. Fortunately, it was also at Willow Garage that I first came across the Thymio II robot and one of the involved researchers from EPFL. I immediately took a liking to this cute and personable little robot, with its 20 sensors and 39 LED. With such personality, I automatically assigned a gender, so from now on if I refer to a ‘he’, please understand that I am referring to the Thymio II, and know that I’ve also had kids decide that the Thymio is really a ‘she’.

I had a hunch that this would be a hit among kids and an excellent teaching tool for robotics. The first time I brought Thymio to the classroom, I gave a presentation about robotics, and boy did the kids FLIP when I took out Thymio. All of the kids excitedly exclaimed, “YOU HAVE A ROBOT, IN YOUR BAG?!”

The first time I took Thymio into a classroom was for my interview with Woodland School. After seeing such excitement from both the kindergarteners and 5th graders, I was pulled into work for Woodland as their Instructional Technology Coordinator for K-8th grade and to create a curriculum around Thymio.

What I love about the Thymio is its adaptability – I’ve been able to teach with it at every age level, from K-8 in the classroom. Thymio has all components in one, and many pre-programmed modes. For kindergarten we can talk about motors and sensors, and behaviors. The kids will create interactive animals by building off of Thymio with LEGO and other arts and crafts and then use the pre-programmed behaviors.

For the students who are around 8-10 years Thymio has been a great tool to teach experimentation, technology, critical thinking, programming, invention, teamwork, design, building … and I could go on and on. The visual programming language composes code in real time and creates a nice bridge to written code. I ran a successful summer camp where I was able to easily teach programming iterations and code writing to kids as young as seven.

Seeing such success in the classroom has motivated me to create a curriculum for other teachers so that they may be able to receive a box of robots and, with the help of an online curriculum, to then be able to start teaching a class. That is the reason why I started TechyKids. The best part about all of this is that the Thymio is a robot that, after some initial guidance, will motivate kids to learn and experiment themselves. Today was (another) perfect example of this – I helped with some troubleshooting for a 4th grade class, who were getting started with Thymio, but after that the kids were fully engrossed in their own work.

Some of the casual side conversations were as follows:

Student #1: “Oh, I think I know!”
Student #2: “Why?”

Student #3: “Now, I wonder how I can get him to sense a cliff…”

Female Student #1: “I love Technology.”

Student #4: “I found a way to make him blush.”
Student #5: “How did you do that?”

Female Student #2: “Would you rather have more PE or Technology?”
Female Student #3: “Technology, definitely”

What I loved about the Thymio-inspired conversations is that they came out naturally. Kids were asking why, collaborating, helping each other, and were passionate about their work. Classrooms everywhere have been yearning for this kind of a result, and I feel fortunate to have come upon a product that can produce such fulfilling results. The way I see it, if we can get kids programming robots at the age of seven, by the time they are in high school and beyond, they’ll be doing something even more amazing.

http://www.youtube.com/watch?v=9hIyN7AKF-4

The Girls of Steel – a competitive FIRST team located in Pittsburg, PA – is on a mission to draw more young women into engineering. We’ve already heard what it’s like to be part of an all-girls robotics team, we now catch up with the team’s mentors, Theresa Richards and George Kantor, to hear about their roles in inspiring and mentoring the team. Here’s what they have to say …

How and why did you become a mentor?

George: My lab, the Field Robotics Center at CMU, was approached by Patti Rote about creating an all-girls FIRST Robotics Competition Team in the summer of 2010.  I have been involved in various K-12 robotics outreach activities dating back to the 90s, and I had always wanted to learn more about FIRST.  So I offered to lead the team.

Theresa: I became a mentor because I was very interested in learning more about FIRST robotics and about how I could work with the FIRST program to support and encourage girls in the interdisciplinary field of robotics.  The study of robotics includes all STEM fields.

Did you have a mentor when you were growing up? If so, can you tell us about this person and the impact they had on you?

George: Growing up, I had a swimming coach who taught me lessons about setting goals and perseverance. In graduate school and throughout my time as a researcher at CMU I have had a series of mentors who have helped shape my technical career.

Theresa: I had several mentors when I was growing up. Most of my mentors were my high school science teachers who offered opportunities for me to do activities with them outside of school. For example, my biology teacher invited me to participate as his teaching assistant at an evening class he taught. My chemistry teacher helped me get a part-time job and she introduced me to my college – the same one she attended, and my zoology teacher took a group of us on a special field trip and she arranged for an “extra credit” dissection lesson after school. These awesome teachers recognized my interest in science and made sure to offer opportunities. When I think back about it now, I feel so grateful that they took extra time with me. That’s what I try to do for my students.

Do you have any suggestions for teachers or others who may want to get started as a mentor?

George: Just do it! There are plenty of opportunities to mentor young people, and it is an extremely rewarding experience.

Theresa: Other teachers who are interested in finding out about a FIRST robotics team should go to the website and click “What teams and events are located in my area?” I bet they’ll find a robotics program that will welcome them with open arms. If the teacher feels unsure about being a robotics mentor, he/she should attend a meeting or two before making a decision. Working with the students is inspiring because of their interest in creating something and learning so many new things. And it’s amazing to hear a student say, “So that’s why we learned this in math or in physics” or “I never would have considered engineering if I weren’t on this team.”

What’s the hardest part about mentoring?

George: It is important to encourage people to dream big, but on the other hand aspiring engineers often have unrealistic expectations about what they can accomplish. Helping students define achievable goals often involves encouraging them not to pursue some of their more ambitious ideas, and delivering that message in a positive way can be a challenge. I want my students to believe they can do anything, but I also need to teach them to approach their dreams in a realistic way.

Theresa: The hardest part about mentoring – there really isn’t a hard part, except that having meetings during after school hours from 5 pm until 8:30 or later means we have some late nights, especially during the 6-week build season. Mentoring is a rewarding experience on multiple levels. I enjoy the experience of working together with students, and colleagues and parents who have similar interests of encouraging girls in STEM fields. Like they say in FIRST, “It’s the hardest fun you’ll ever have” – that goes for mentors as well as students.

Do girls need female role models?

George: Yes. It is inspiring for girls to see women in the roles they aspire to, especially in fields like computer science and engineering that are currently dominated by men.

Theresa: Girls need female role models in STEM fields in order learn about various careers and to be able to see themselves in various positions or careers in STEM fields. Girls also benefit from belonging to a network or group of girls who share similar interests while in high school, college, and beyond.

Which students should participate in robotics competitions?

George: All students, especially those with technical interests. Robotics competitions are easily accessible, and they provide an opportunity to learn valuable technical skills in a fun way. They also provide an opportunity to learn life skills that are useful regardless of what career they decide to pursue: teamwork, goal setting, time management, etc.

Theresa: I believe all girls will benefit in some way from joining the Girls of Steel or another FIRST robotics team. The level of the benefit will depend on their level of participation.  Participation on the Girls of Steel FIRST robotics team can range from 4 to 20 hours a week during the year. The number of hours depends on the “season” – preseason, build season or competition season – and on a girl’s particular role on the team – e.g. leaders spend time preparing for team meetings and have additional leadership meetings to attend. Why do you recommend robotics competitions for everyone? Not only do the students apply what they’ve learned in computer science, math, science, and engineering classes they also learn that it can be fun to work hard. They learn so much about themselves by being a part of the team. For example, I’ve heard girls say things like “only girls on the team understand why I like ….”, “I found my best friends on the team”, “now I know the difference between a personal goal and a team goal” , “ Only you get my jokes,” and more.

There are many robotics competitions for students. Why FIRST?  

George: I really like FIRST’s approach to competition. Winning is important, but greater importance is placed on cooperation and professionalism. FIRST has invented words that capture this spirit and are central to everything that FIRST does: “coopertition” and “gracious professionalism”. In addition, FIRST goes to extra efforts to make its events exciting. The games are well designed, with attention paid to making the matches interesting to watch. The competitions are narrated by professional emcees and the field set-up has a high production value. The result is something that is a cross between a rock concert, a sporting event, and a science fair.

Theresa: I really don’t know much about other competitions except that some involve “fighting robots” rather than “game playing robots,” and the robots vary in size. FIRST® (USFIRST.org) is an organization that promotes robotics competitions for all ages that involve more than just a robot. Our team competes at the FRC (FIRST Robotics Competition) level that involves designing and building a 120 lb. robot over a period of 6 weeks to play a game with 5 other robots on the field. The awards structure of FIRST promotes other aspects of the team – like fundraising (to raise money for registration fees), outreach, teamwork, public speaking, leadership, media, and more. We’ve found that having a FIRST team seems to be like running a business with students having the opportunity for major leadership roles. High School level FIRST teams are encouraged to support STEM awareness for younger people in the community. Publishing Lynn’s comic about the 2012 FRC season on our website and on Robohub is just one way the Girls of Steel FIRST robotics team contributes toward that goal.

Thank you both very much for your time, and best of luck to you and the Girls of Steel in future competitions!

To understand what the Drones for Schools program is, and how it came about, it helps to know a few things about my background. I didn’t originally set out to be a STEM educator. I had some science education from studying mechanical engineering as an undergraduate, but eventually wound up with a master’s in journalism. I didn’t think the two halves of my life would merge until I finished my master’s and took a job at a K-12 STEM education grant, at the University of Illinois – they needed someone with a scientific background to handle communications and study the social networks that teachers were forming as part of the grant.

At the time, I was researching how journalists could use aerial robots, commonly called “drones”, to capture data during natural and man-made disasters. As part of this research, I was spending a great deal of time in my basement “hacking” together a small drone from a radio controlled airplane and open-source hardware. It became apparent that this learning experience mirrored what teachers were doing in the STEM grant, and so I approached my boss, a department head in the College of Education one of the co-principal investigators for the grant, with a pitch: let’s have students design, build, and fly drones at our partner schools. He assembled a team of STEM educators to guide the process, and the “Drones for Schools” initiative was born.

Two students collaborate to build a “drone”.

In some ways, the program resembles a nesting doll for concepts in science, technology, engineering and mathematics. A drone is a complex machine, and once you peek inside, one STEM concept leads to another. To design the aircraft, you begin with concepts like Bernoulli’s principle, which when applied through a mathematical formula, determines parameters such as stall speed (how slow the plane can fly before falling out of the sky). Stall speed dictates the power you need to fly, which opens an opportunity to deliver content about electricity and electric motors. And delivering content about electricity and electric motors segues nicely into lessons about battery chemistry and capacity. All the while, students are applying this content knowledge as they make key decisions about how this aircraft will be designed and deployed.

Because this is a semi-autonomous aircraft that is dependent on a small microcontroller, computer programming is interwoven into the Drones for Schools curriculum. Students take this full-function microcontroller, which uses hackable open-source hardware and software, and learn programming by getting it to do some things it wasn’t intended to do. They learn about electronics prototyping by wiring up the microcontroller to external LEDs, and by writing C code to enabe the microcontroller to blink out a Morse code, they learn about variables, arguments, loops, functions, and libraries.

Soldering is one of the many skills that students learn through the Drones for Schools program.

These individual lessons are valuable on their own, but the program’s biggest gains come from students assuming the roles of engineers. This program was designed in part to meet the demands of the Next Generation Science Standards (NGSS), which were developed by the National Research Council to help prepare K-12 students for an world where science literacy is increasingly necessary. Perhaps one of the biggest challenges and opportunities presented by NGSS, is the incorporation of engineering education into the K-12 science curriculum, something which hasn’t been attempted on this scale. To help students understand what makes them engineers in the Drones for Schools program, and how that’s different from what scientists do, we’ve had a graduate engineering student explain how engineers make models, design solutions, and test those solutions. The engineering student also provided high school students with information on how their interests in the Drones for Schools program could lead to an education in engineering, and what an engineering career path looks like.

Drones for Schools is just one of around 30 collaborations at the National Science Foundation grant EnLiST, which stands for Entrepreneurial Leadership in STEM Teaching and learning. Each collaboration is unique, but they are all “entrepreneurial,” meaning they draw on resources from other classrooms, university faculty, community organizations, and businesses. Drones for Schools is no different than the other collaborations in the sense that we rely on community partners to provide a useful application for the drone. The drone is not built for the sake of building a drone; rather it is built because it can provide high-resolution images of the ground which can be stitched together in a map. And that data has use for farmers, city planners, researchers, first responders, and many others. Simply put, we think there is a need for drones in the community, and our students are trying to fill that need.

Testing out one of the class’ inventions

AUVSI, the Association for Unmanned Vehicles and Systems International, predicts that 30,000 drones will be flying by 2020, with the majority of those serving as farm equipment. Depending on the definition of a drone, the US may already have exceeded that number. The goal of this program isn’t to ensure that one of our students will engineer one of those drones someday, although technically they’re already building and flying one of those 30,000 when take part of our initiative. Rather, we’re interested in our classroom data, which suggests the initiative increases interest in engineering. And in that sense, I think we’ve succeeded.

UIUC faculty and staff associated with this grant are currently seeking other grants to specifically enrich middle school STEM education. Because of the tremendous learning opportunities packed into these flying robots (some of which are small enough to fly in a classroom), and because of their real-world importance, we believe that drones will be an integral part of STEM opportunities for some time.

I am profoundly convinced that if we are able to preserve the natural curiosity of early childhood in growing up individuals, without fail they will develop a durable attraction to science, technology, engineering and mathematics (STEM). Although this simple recipe seems to be a no-brainer, obviously education encounters insurmountable difficulties in maintaining the precious elementary drive. Once lost, almost therapeutic efforts will be necessary to awake it again.

Ray Almgren, vice-president of marketing at National Instruments, worried in his 2012 NIWeek keynote speech about the problem that:

Somewhere between dropping our kids off at kindergarten and sending them to college, we somehow manage to extinguish their interests in science and engineering. So, how does this happen? Well, there’s a fundamental disconnect of how we do science and engineering in the real world and how it’s taught in the classroom. Not all, but too many educators are pulling a bait-and-switch on our brightest minds by taking away the hands-on exciting projects that got them interested in the first place and replacing it by the theory-only math-based approach that is literally driving out our future innovators in droves.

Anti-math norm

Now, I do not totally agree with Almgren’s analysis that math-based teaching itself should be a vocation-killer. As kids come to adolescence, they naturally develop important cognitive faculties like formal, abstract and hypothetical thinking, processing speed, selective attention, a.s.o., all of which perfectly match with the problems presented in math and physics. In parallel, adolescents dramatically enhance their social skills, and edify their self-esteem, which is essential for their maturation and successful integration into society. However the predominance of social concerns makes them very vulnerable to peer-pressure capable of jeopardizing personal interests for STEM content. For instance, if the clique is submitted to an anti-math norm – as it is often the case in school classes – it will be literally unsexy to be good at math, and initial likes of STEM branches may be seriously compromised.

In his autobiography, Steve Wozniak, a math and science nerd, narrates how much he suffered from such pressure, as he passed from the sixth to the seventh and eighth grades.

Where before I was popular.., suddenly I was socially shut out… It seemed like nobody spoke to me for the longest time. I was in the advanced classes and got good grades… I felt shunned by all these kids who suddenly, and for no reason I could understand, just couldn’t accept me anymore. I did electronics when a lot of others started hanging out and partying and drinking and going out.

Wizardry

Most young people just want to have fun, and they are running scared of being considered as loners. So, why shouldn’t educators try to profit from the same strong psycho-social moments that steer people away from STEM content, and double-cross those undesirable effects? For this purpose a few magic ingredients can be used in order to keep the interest in science and engineering alive beyond puberty: having fun, playing in teams, living some positive rivalry, doing hands-on activities, inventing, hacking, experiencing great rewarding events, sharing stuff with others, meeting stars. During almost 15 years, I consequently deployed these components in a local youth laboratory with various groups of high-school students.

Why robotics?

Because it was possible to find all of the components in the LEGO Mindstorms concept, robotics became the lab’s blockbuster activity after 1998! LEGO is a toy that most kids know from earlier childhood. They associate successful playing with Mindstorms activities, not dreadful failure. They can easily reproduce official models, or thoroughly copy cool robots presented in countless books around the subject. However, the more important quality is that the material is open-ended. Anything can be made of the stuff. It both challenges and fosters creativity, and –unexpected for the LEGO Company at start of the Mindstorms product line— it invites adolescents to go for hardware and software hacking. The latter feature makes the material even more attractive, because doing the impermissible or unorthodox can be irresistible for young people. LEGO sets are designed for boys and girls -although there is a significant male predominance. The Mindstorms concept is tailor-made for project-based learning. Meanwhile there’s a huge world-wide connected community of Mindstorms geeks, clubs and school labs sharing and discussing their projects. There also are contests! Only think of these extraordinary FIRST LEGO League FLL-competitions. I was able to attend a couple these, and the atmosphere was electrifying: young people enjoying collective rivalry that you only experience in sports events.

Stars and events

My students met heroes like Daniele Benedettelli – the guy who made the first LEGO Rubik’s cube solver. A few times they could present their own robots on local RTL TV. They showed humanoid robot GASTON, one of our most ambitious projects, to the Earl of Wessex, the youngest son of Queen Elisabeth II. Their robots crawled over ground, went down to caverns, high to the stratosphere, crossed the sea, and even cruised over Mars –at least over a simulated Mars environment. The online lab journal kept track of the actual developments. This resulted in countless exchanges with interesting people all around the globe. Because of their positive media presence, participants of the robotics lab became little stars within their peer-group.

Challenges

When new participants enter the robotics lab, they are not submitted to annoying introduction lectures. They immediately start with two sorts of hands-on activities. First they follow a few solved exercises, from which they rapidly get the rudimentary knowledge about the material and the LabVIEW programming environment. (Note that we almost exclusively work with this unbeatable graphical software made by NI.) Second, they are challenged in little teams with problems that allow for more than one solution. An easy, although not trivial one is “Driving the Straight Line”. Most young people are accustomed with computer behavior. If they draw a line in a picture editor -a typical open-loop activity-, they expect that an almost perfect line will appear on the screen (to say nothing about pixel-effects). Now, robotics brings back digital processing into the real world… and the students are always stunned, when they see that their robot is driving an arc, although they naïvely programmed it to drive straight. Fred Martin, one of the creators of the first LEGO programmable brick prototype, cuts right the chase of the matter by declaring “Real robots don’t drive straight”. A more elaborate challenge is “Finding the center of a circle”. A circle is duct-taped on the floor; a dual-drive robot is equipped with a single light- or color-sensor. Now, with no other information about the circle, the robot should most precisely find the location of its center. How would you tackle this remarkably difficult exercise?

Projects

Once the participants can handle the LEGO Mindstorms material and the LabVIEW software, they are summoned to decide for a team-project. In his bold article “The Project Method: The Use of the Purposeful Act in the Educative Process”, published in 1918, William H. Kilpatrick described the “project” as “a whole-hearted purposeful act carried on amid social surroundings”. The robotic boat indicated above was the result of a long-term project, to which a group of students was committed… whole-heartedly… They had fun, played in a great team, lived some positive rivalry, did hands-on activities like etching and soldering, invented, hacked, experienced a great rewarding event: when the boat successfully crossed Luxembourg’s biggest lake. They shared their stuff with others, and met stars… the ingredients for making cool robots, and the previously enumerated components for reinvigorating personal interests in STEM content. Many of the attendees of the local youth robotics lab have started their studies in science and engineering. Some have graduated; a few have taken their doctoral degree, and rejoined renowned companies or institutes.

Eureka!

From my experience with the youth lab, getting started with robotics is more a matter of educational methods than of technical aids. If you want to read more about the concept of using LEGO Mindstorms in a youth laboratory, and experience yourself some of these exhilarating moments of Eureka, you should get a copy of my book “Eureka! Problem Solving with LEGO Robotics”, www.ntspress.com, USA, 2013. You also may want to see the lab blog: www.convict.lu/index_r.php

We have a long-standing habit of anthropomorphizing things that aren’t human by attributing to them human-level personality traits or internal motivations based on cognitive-affective architectures that just aren’t there. Animators have relied on the audience’s willingness to suspend disbelief and, in essence, co-animate things into existence: from a sack of flour to a magic broom. It’s possible to incorporate the user’s willingness to bring a robot to life by appropriately setting expectations and being acutely aware of how the context of interaction affects possible outcomes.

In human lifeforms, a head usually circumscribes a face, whereas in a robot a face can be placed anywhere. Although wonderfully complex, in high degree of freedom (DOF) robot heads, the facial muscles can be challenging to orchestrate with sufficient timing precision. If your robot design facilitates expression through the careful control of the quality of motion rendered, a head isn’t necessary in order to communicate essential non-verbal cues. As long as you consider a means for revealing the robot’s internal state, a head simply isn’t needed. A robot’s intentions can be conveyed through expressive motion and sound regardless of its form or body configuration.

[1] Harris, J., & Sharlin, E. (2011, July). Exploring the affect of abstract motion in social human-robot interaction. In RO-MAN, 2011 IEEE (pp. 441-448). IEEE.

• Food intake: Probably not.
• Computational storage: Again, probably not.
• Location for sensors: Indeed, the apex of a robot is a natural, obstacle-free vantage point for non-contact sensors. But a “head” form factor is not a strict requirement.
• Emotion and expression: Ah, the real meat of this question… “Do robots need to express emotion?”

This is a funny question to ask someone who once (in)famously advocated for either (A) extremely utilitarian designs: “I want my eventual home robot to be as unobtrusive as a trashcan or dishwasher”, or (B) designs unconstrained by the human form factor: “Why not give robots lots of arms (or only one)? Why impose human-like joint limits, arm configurations, and sensing? We can design our own mechanical lifeforms!”

My views have softened a bit over time. Early (expensive) general-purpose home robots will almost certainly have humanoid characteristics and have heads with the ability to express emotions (i.e. be social) — if nothing else, to appeal to the paying masses. And these robots will be useful: doing my laundry, cleaning my dishes, and cooking my meals. In the early attempts, I will still find their shallow attempts at emotion mundane and I will probably detest the sales pitches about “AI” and “robots that feel.” But as the emotional expressions become more natural and nuanced, and the robots become more capable, I will probably warm up to the idea myself.

TL;DR: No, many robots do not need heads. Even social robots may not need heads, but (whether I want them to or not) they probably will, because paying consumers will expect it.

From the media advisory announcing the event:

Hosted by the Ted Roger’s School of Management’s Privacy and Cyber Crime Institute, the forum is sponsored by the Centre for Excellence in Policing and Security, University of Wollongong (Australia), Flinders University (Australia), Leeds University (U.K), EPIC.org, Dronejournalism.org, Drones for Good and sUAS News.

Like many children who show an early interest in science, technology, engineering and mathematics (STEM), my childhood years were spent constructing Lego masterpieces and deconstructing household electronics. My introduction to the world of robotics came through my parents, who opened one of the first robotics online-shops in Australia in order to support my interests. Inspired, I spent the next few years of my life playing with Lego Mindstorms, hexapods and Basic-Stamps, and running a “Robot Wars” competition with my best friend.

My interest during these years was not in the mechanics, but rather in the software and electronics that controlled the robots. This interest lead me to study computer systems engineering at a bachelor level. During this degree, I entered local robotics competitions and quickly realized that, in order to further my interest in robotics, I needed a better understanding of mechanics and control systems – a direction that I followed in my masters degree, and have since continued as a PhD student under the supervision of Professor D’Andrea, whom you may remember from his TED talk on Machine Athleticism.

Over the last few months, largely in response to this TED talk, I and my colleagues at Robohub and the Flying Machine Arena have received many emails from interested students and hobbyists asking us “How do I get started with robotics?”

My first contact with “robots”; this fascination has since lead me into an academic pathway into the field.

To begin to answer this, we first need to dive a little deeper and address the questions “what is robotics?” and “what is a robot?”

Asking the general public, I received answers varying from “manufacturing” and “smart vacuum cleaners” to “intelligent machines capable of making their own decisions”. As a robotics researcher, I define robotics to be the field at the intersection of mechanics, electronics, mathematics, programming and algorithms, and a robot to be a dynamic (capable of moving) device that can sense and interact with its environment by using a combination of mechanics, electronics and software.

The fact is, robotics means different things to different people, and this makes getting started a difficult task, regardless of age, education or prior experience – there is no one-size-fits-all answer!

To help guide curious and aspiring minds of all ages and backgrounds, Robohub will be running a two week focus series on how to get started in robotics. This series will consist of hands-on tutorials and discussions about educational pathways, as well as personal “getting started” stories and advice from roboticists, hobbyists and robotics students. These will be complemented by a closer look at some high-profile robotics projects, in order to highlight how mechanics, electronics, mathematics, programming and algorithms work together to produce a robotic system.

Interested in contributing to the focus series? We’d like to hear from you.

SUSBEXPO is the first conference about unmanned systems to really focus on the growing commercial opportunities of this market. AUVSI put on a spectacular annual show, but it is predominantly military systems. SUSBEXPO is the brain child of Patrick Egan, who is a UAS business consultant, as well as being deeply involved in AUVSI, SUASNews, building on a background with the military and regulatory groups. The conference was held at the Golden Gate Club in San Francisco on July 25-26 and attracted attendees from all over the US and beyond. UAVs were on exhibit from companies like 3D Robotics, AgriFlight and MLB Drones, and Patrick Egan is expecting SUSBEXPO to be even larger next year.

The two day speaker list was jam packed with names that few of us have heard of … yet. The conference was also multidisciplinary, attracting end users of drones/unmanned systems, service providers, lawyers, journalists, ethicists and investors. Investment into potentially commercial drone companies is starting to take off: Airware raised $10.7 million in their Series A round from Google Ventures, Andreessen Horowitz, RRE Ventures, Lemnos Labs and Promus Ventures; 3DRobotics raised $5 million in a Venture round from True Ventures, O’Reilly AlphaTech Ventures and Chris Michel; and Drone Deploy not ready to announce yet, but were the hit of Angel Pad incubator’s recent Demo Day, and the company was founded by exGoogle machine learning PhDs. As Bruce Park from Agriflight said when he opened the expo, “It’s like being in Steve Jobs’ garage. It might look like a hobby to some people but it’s about to become a revolution.”

Speakers on Day One included Gretchen West, the Executive Vice President of AUVSI, who talked about the challenges of firefighting the recent surge of negative local drone legislation, like the bounty for drone hunting proposed by one Texas town. West has found that at both the federal and state level, the primary legislative focus is on privacy, but as cameras (and now phones) are everywhere these days, we need to talk about the whole issue of privacy and not the devices. “It’s not the platform that should be legislated.”

Eileen Shibley from the California UAS Portal talked about the pathway towards becoming one of the 6 FAA UAS test sites, which has included becoming a hardware business incubator with rapid prototyping and manufacturing facilities to extend the Portal’s utility for both clients and the community around Inyokern Airport. Jonathan Downey, Airware CEO, saw the increasing pressure for commercialization as an opportunity to create responsive and accessible cross platform UAS software, disrupting the costly inflexible blackbox autopilots generated by a military chokehold on UAV business.

ITAR – the elephant in the room

At the moment, unmanned system business is shaped by the triumvirate of military funding, the slow path towards an FAA certification system and ITAR, the International Traffic in Arms Regulations. Under export law, all unmanned systems and componenents are considered weapon systems and can’t be sold or operated with, or around, foreign nationals without very costly and difficult-to-get approval. By and large, the military is the only customer rich and patient enough to go through this process. Meanwhile, domestic commercialization is still on hold waiting for an FAA regulatory structure to emerge.

Tad McGeer, Aerovel CEO, said that ITAR applies to ALL robotic aircraft regardless of application, and this effectively forces all small businesses to become military arms dealers instead of small businesses. McGeer points out that the UAS industry is still mostly made up of very small businesses, and that direct competition with manned aircraft is a long way off. The end-user cost per flight-hour, even with cost reductions, is still not competitive. UAS startups need to look for a niche. Some of the characteristics of favorable niches are reductions in aircraft, startup and logistics costs, greatly improved reliability and ease-of-use, offshore and remote areas, scope for miniaturization, parallel operations with multiple aircraft and high utilization.

Parallels with the history of automobiles

Chad Partridge, who is a Board member of AUVSI, as well as founder of Sensing System and VP of 2D3 Sensing, placed the current regulatory confusion and public angst over drones in parallel with the history of the automobile. Drones are part of a moral debate, and the industry is being regulated around some very negative perceptions. In hindsight, our common perception is that there was immediate acceptance for automobiles because we can no longer imagine a society without them, however there were decades of conflict over the role of motor vehicles. Before the city streets were physically reconstructed for automobiles, the social landscape had to be built.

Partridge recommends “Fighting Traffic” by Peter Norton, Assistant Professor in the Department of Science, Technology, and Society at the University of Virginia. Norton examines a range of perspectives during the period from 1900 to 1930, from police who had to become ‘traffic cops’, city planners who tried to regulate traffic, parents and pedestrians who campaigned for ‘safety’ and ‘justice’ over the loss of the street in sometimes violent opposition to automobile interest groups who, themselves, invoked the rhetoric of ‘freedom’.

Partridge suggests that the lessons learned from the automotive past are the importance of banding together as an industry, promoting better narratives, and steering legislations and standards. Industry solidarity and networking are things that organizations like AUVSI and Silicon Valley Robotics can play an important role in.

Agriculture – the answer

As the AUVSI report from March 12 2013 explains, agriculture is the optimal vertical for unmanned systems at the moment, and can deliver billions of dollars of economic value alongside thousands of jobs and the social good of reduced pesticide/fertilizer use. The barriers to entry are lowest and the potential returns are the highest in this market. There were several speakers focussing on aspects of this area including Chris Anderson of 3D Robotics, one of the fastest growing venture backed robotics startups in the Valley. 3D Robotics has iterated from a DIY community supplier to a consumer robot company, and now to a data and payload service provider.

As Chris Anderson asked, what is drone data good for? Vineyards currently use an analog sensor technology that has been unchanged for thousands of years. There is a rose at the end of each row of grapes and the rose is an early warning for fungal infections. Drones can expedite our emerging ‘Big Data’ capabilities in agriculture, which is the largest industry in the world.

Half of our agricultural inputs (e.g. water, fertilizer) are being wasted because the cost of not treating is greater than the waste cost. Knowledge of where there were leaks in the system would allow for adjustment and an opportunity for closed-loop farming. Farmers want this but they don’t necessarily care about the technology that delivers the data. Drone developers need to talk to farmers in order to create custom trusted solutions.

The folks at 3D Robotics have been talking to a lot of farmers in the last year and have found that each farm is different, not just each crop. Anderson says that companies need to build a community interface and offer a multi-solution package. For example, a farmer should be able to deploy a rover or a copter or a fixed wing system with equal ease, depending on requirements. It should be as simple as picking up a tablet, drawing your boundary, pushing a button to go.

The industry is still at a very early stage, with most customers in it ‘for bragging rights’ rather than economic benefit, however in a short time there should be a bank of success stories to draw on that will support future growth. The market opportunity is in delivering insight, not just drones. It’s about image acquisition, processing and locating. Georeferencing is a significant field opportunity. Data may be freely available but it’s the processing and the insight that offers huge commercial opportunities.

Anderson said, “Stewart Brand is often misquoted.  Yes, he said “information wants to be free” but he also said that “information wants to be expensive, because it’s so valuable.”

On the one hand information wants to be expensive, because it’s so valuable. The right information in the right place just changes your life. On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other. [Whole Earth Review, May 1985, p. 49.]

A timely conference

While SUSBEXPO was primarily about drones, and a majority of the established companies are still defence-funded, it seems clear that a change is underway. The timeliness of the event was mentioned by many of the participants, who came from across the world, as far afield as Australia and the Cayman Islands, and who crossed disciplines from engineering to education, from entertainment to law.

One of the speakers, Matthew Schroyer, is the organizer of ‘drones for journalism‘ which not only destigmatizes drones in the media by highlighting humanitarian and libertarian use cases but is also the professional association for the newly emerging field of drone journalism. As technology changes, professions change in response and Schroyer talks about the ways that journalism must evolve to make use of new data.

The Reuters Institute for Journalism in the UK recently released a report on the implications of the increasing use of drones and ROVs in journalism. The report notes the tension between audience expectation for full media coverage of events and the increasing ease and affordability of deploying drones alongside privacy and safety concerns.

Ambivalence of public acceptance aside, drones in journalism is indicative of many small niche markets for increasing commercialization of robotics technologies. As Schroyer said, “This is a timely conference. We worry about large corporations running the agenda. Small stakeholders are the important ones and are making themselves heard.”

In the words of conference organizer Patrick Egan, SUSBEXPO will return in 2014 to further ‘federate and promote the unmanned systems community’.

Video feeds:

SUSBEXPO Day One – part one | Day One – part two | Day Two – part one | Day Two – part two

Such multi-UAV systems were in the focus of the Sixth Lakeside Research Days organized and hosted by Lakeside Labs and the University of Klagenfurt in Klagenfurt, Austria, from July 8 to 12, 2013.

Concept and Program

The Research Days are a special format of workshop. Besides keynote talks given by invited experts from academia and industry, they feature a demonstration session, intensive group work, discussions on technological and business aspects, and social activities for attendees.

The keynotes were as follows:

• Small flying robots: Design and visual navigation
  By Roland Siegwart (ETH Zürich)
• Fusion of distributed perception in collaborative visual-SLAM approaches on mini-UAVs
  By Darius Burschka (TU München)
• Exploiting redundancy for reliable aerial computer vision
  By Horst Bischof (TU Graz)
• Aerial imaging and wireless communications with multiple autonomous UAVs
  By Christian Bettstetter and Evsen Yanmaz (U Klagenfurt and Lakeside Labs)
• Decisional issues in multi-UAV systems
  By Simon Lacroix (LAAS/CNRS)
• Slalom racing and flight dances: motion planning, control and learning for high-performance quadrocopter flight
  By Angela Schöllig (U Toronto)
• Multi-spectral people detection from UAVs
  By Stephen Cameron (Oxford)

A panel with Roland Siegwart, Hermann Hellwagner (Klagenfurt), Phil Charlesworth (EADS), and Michaël Rischmüller (Parrot) discussed business opportunities and start-up ideas of UAV systems.

Further information can be found in the final program and the Twitter feed #resdays13.

Media Coverage

The event was covered by various media including Austrian television ORF and the newspaper Der Standard (article Drones in peace missions).

Cover of “Der Standard” from 17 July, 2013

Impressions of the First Day

Keynote by Siegwart: Small flying robots

Keynote by Schöllig: Slalom racing and flight dancing

Image Gallery

Photos by Christian Philipp (Lakeside Labs GmbH) and Christian Bettstetter.

The first pass seems to indicate that Boston is actually living up to the hype this year as it tops the list in number of deals and amount of funding and brings home the three largest deals.  Silicon Valley trounced the rest of the country on last year’s list with a similar performance to Boston’s this year.

Stay tuned for more analysis of the list once there is time for collective knowledge of the internet to complete the missing deals.

Moderator
Gordon Feller, director of Urban Innovations, Cisco Systems; founder, Meeting of the Minds

Panelists
Anthony Levandowski, manager, Google autonomous vehicle project
Sen. Alex Padilla, California State Senator
Jim Pisz, corporate manager, North American business strategy,
Toyota Motor Sales Inc.
Dan Smith, Senior Associate Administrator for Vehicle Safety, NHTSA (National Highway Traffic Safety Administration)
Bryant Walker Smith, Fellow, Stanford University Center for Automotive Research

View video streams of the full conference on the New York Times Energy for Tomorrow Conference website.

If the world’s steadily expanding cities are to thrive in the 21st century, how will we meet the challenges posed by global warming and the growing need for improved infrastructure, transportation, fresh food, water and clean air? The New York Times brings together some 400 thought leaders, public policy makers, government urbanists and C-suite level executives from energy, technology, automotive and construction industries among others, to debate and discuss the wide range of issues that must be addressed if we can create an urban environment that can meet the needs of its citizens and, thanks to innovation, run cleanly and efficiently.

Looking at the two words together is enough to conjure up images of chaos and destruction.  They’re an image far too familiar in science fiction settings such as Isaac Asimov or Arthur C. Clarke. It’s also a concept many A.I. researchers will gladly tell you they’ve been plagued with at least once by friends or colleagues.  However, how much of a real ethical concern do they pose for society?

Nobel Peace Laureate Jody Williams and Noel Sharkey from the International Committee for Robot Arms Control at the launch of the Campaign to Stop Killer Robots. Photo by Peter Asaro.

In November of last year, Human Rights Watch (HRW) and the International Human Rights Clinic (IHRC) at Harvard Law School jointly published a 50-page report on the topic of killer robots. The report, titled Losing Humanity: The Case against Killer Robots, outlined many legal, ethical, and other concerns pertaining to the use of fully autonomous weapons (previously covered by Mike Hamer of Robohub). Some of the concerns outlined include unsolved and important roboethics questions such as “who is legally responsible for a robot’s actions?”

Maybe this question doesn’t have to be answered (not right away at least) if we simply stop the use and development of killer robots all together.

Earlier this week, on April 23, a new global campaign named the Campaign to Stop Killer Robots was launched with this very idea of stopping killer robots. Composed of over twenty international NGOs in ten countries, the campaign’s focus is to ban the development, production and use of future lethal robot weapons or “killer robots” that could autonomously locate and neutralize human targets.

Addressing countries such as China, Russia, Israel and the United States that are currently moving to create systems to give greater autonomy to combat robots, the campaign believes it would pose a challenge to international human rights and humanitarian law.

Photo by Peter Asaro

Fully autonomous weapons aren’t really roaming around war zones today (yet). So this campaign is preemptive. But given that we have so many precursor technologies out there already — I mean, who doesn’t know about the drone technologies used for targeted attacks today? — it seems that developing and deploying autonomous weapons is an obvious next step. But this obvious next step could lead to a tragic case of a robotic arms race. Taking actions to ban it now makes more sense than to ban it when it’s too late.

In 2009, Robots Podcast interviewed Noel Sharkey (Professor of A.I. And Robotics at the University of Sheffield, and spokesperson of the Campaign to Stop Killer Robots) and Ronald Arkin (Regent’s Professor and Director of the Mobile Robot Laboratory at Georgia Institute of Technology), and both experts addressed the issue of ethics of robot soldiers.  As Sharkey argued, the problem of robots autonomously identifying targets lies within the Principle of Discrimination (part of the international Laws of War described in the Geneva Convention) (listen to his interview here).  In it, soldiers must not harm a civilian, non combatant, the immensely ill or prisoners of war. According to Sharkey, no A.I. system can reliably discriminate between soldiers and civilians.  A robot, for the moment, “can’t have a sense of ethics” necessary to make the humanistic decisions required by soldiers.

An opposing viewpoint is provided by Arkin. According to Arkin, robot soldiers carry an inherent danger but depending on their implementation, it could provide better safety and non-combatants for soldiers (listen to his interview here).  As Arkin argues, robots are not affected by emotions such as fear or anger that can sometimes cloud soldier’s better judgment on the field — although simulation of certain emotions such as guilt could be used to improve a robot’s decision making algorithm.

Despite the contrasting views, both Sharkey and Arkin were in agreement in 2009 that as it stands, autonomous robots are not prepared for battlefield. The Losing Humanity report from last year echos this viewpoint. The launch of the Campaign to Stop Killer Robots is timely, and comes one month ahead of Christof Heyns‘ (United Nations Special Rapporteur on extrajudicial, summary or arbitrary executions) delivery of  his report on lethal autonomous robotics to the UN Human Rights Council.

So what can we, roboticists, politicians, or the public do in support of the campaign?

You can have your say on the matter by voting on the poll of the Engineer (see left hand column).

Interested individuals can support the campaign by responding to the call to ban lethal autonomous robots by the International Committee for Robot Arms Control’s (ICRAC, a leading NGO member of the Campaign to Stop Killer Robots). Interested NGOs can join the campaign by contacting the campaign coordinator.

Or if you’d rather not explicitly support them, but find out more, check out the campaign’s website or the press release .

To keep on top of the news from the campaign, follow the campaign via Twitter, Facebook, and Flickr.

This post was prepared jointly by Matthew Ebisu and AJung Moon and first appeared on Roboethics Info Database.