I’ve worried about the sustainability of consumer electronics for some time, and, more recently, the shocking energy costs of big AI. But the climate emergency has also caused me to think hard about the sustainability of robots. In recent papers we have defined responsible robotics as

… the application of Responsible Innovation in the design, manufacture, operation, repair and end-of-life recycling of robots, that seeks the most benefit to society and the least harm to the environment.

I will wager that few robotics manufacturers – even the most responsible – pay much attention to repairability and recyclability of their robots. And, I’m ashamed to say, very little robotics research is focused on the development of sustainable robots. A search on google scholar throws up a handful of excellent papers detailing work on upcycled and sustainable robots (2018), sustainable robotics for smart cities (2018), green marketing of sustainable robots (2019), and sustainable soft robots (2020).

I was therefore delighted when, a few weeks ago, my friend and colleague Michael Fisher, drafted a proposal for a new standard on Sustainable Robotics. The proposal received strong support from the BSI robotics committee. Here is the formal notice requesting comments on Michael’s proposal: BS XXXX Guide to the Sustainable Design and Application of Robotic Systems.

So what would make a robot sustainable? In my view it would have to be:

• Made from sustainable materials. This means the robot should, as far as possible, use recycled materials (plastics or metals), or biodegradable materials like wood. Any new materials should be ethically sourced.
• Low energy. The robot should be designed to use as little energy as possible. It should have energy saving modes. If an outdoor robot then is should use solar cells and/or hydrogen cells when they become small enough for mobile robots. Battery powered robots should always be rechargeable.
• Repairable. The robot would be designed for ease of repair using modular, replaceable parts as much as possible – especially the battery. Additionally the manufacturers should provide a repair manual so that local workshops could fix most faults.
• Recyclable. Robots will eventually come to the end of their useful life, and if they cannot be repaired or recycled we risk them being dumped in landfill. To reduce this risk the robot should be designed to make it easy re-use parts, such as electronics and motors, and re-cycle batteries, metals and plastics.

These are, for me, the four fundamental requirements, but there are others. The BSI proposal adds also the environmental effects of deployment (it is unlikely we would consider a sustainable robot designed to spray pesticides as truly sustainable), or of failure in the field. Also the environmental effect of maintenance; cleaning materials, for instance. The proposal also looks toward sustainable, upcyclable robots as part of a circular economy.

This is Ecobot III, developed some years ago by colleagues in the Bristol Robotics Lab’s Bio-energy group. The robot runs on electricity extracted from biomass by 48 microbial fuel cells (the two concentric brick coloured rings). The robot is 90% 3D printed, and the plastic is recyclable.

I would love to see, in the near term, not only a new standard on Sustainable Robotics as a guide (and spur) for manufacturers, but the emergence of Sustainable Robotics as a thriving new sub-discipline in robotics.

The logo of the UAE’s annual World Government Summit which this year included a Global Governance of AI Roundtable for the first time.

In this episode Andrew Vaziri speaks with Nicolas Economou, CEO of the eDiscovery company H5 and co-founder and chair of the Science, Law and Society Initiative at The Future Society, a 501c3 think tank incubated at the Harvard Kennedy School of Government. Economou discusses how AI is applied in the legal system, as well as some of the key points from the recent “Global Governance of AI Roundtable”. The roundtable, hosted by the government of the UAE, brought together a diverse group of leaders from tech companies, governments, and academia to discuss the societal implications of AI.

Nicolas Economou

Nicolas Economou is the chief executive of H5 and was a pioneer in advocating the application of scientific methods to electronic discovery. He contributes actively to advancing dialogue on public policy challenges at the intersection of law, science, and technology. He is co-chair of the Law Committee of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems; is chair of The Future Society’s Science, Law and Society Initiative and Senior Advisor to its Artificial Intelligence Initiative; and chaired the Law Committee of the Global Governance of AI Roundtable hosted in Dubai as part of the 2018 World Government Summit.

Links

• Nicholas Economou’s Website
• Subscribe to Robots using RSS
• Support us on Patreon
• Download MP3 (15.6 MB)

Image from the South China Morning Post

In this episode, Audrow Nash speaks with Karl Weaver (魏卡爾), formerly the Original Equipment Manufacturer Business Development Director for Oasis Smart SIM. Weaver discusses how wearable technology is growing as a form of payment system in China. He speaks about wireless technology, including Near-Field Communications (NFC) and Embedded SIM cards (eSIM), in wearable technology and in other applications, such as bike rental.

Karl Weaver (魏卡爾)

Since the recording of this interview, Karl has begun working for ARM promoting eSIM and iUICC to Greater China and Asia.

Karl Weaver (魏卡爾) previously worked as the Original Equipment Manufacturer Business Development Director (North America and Northeast Asia) for Oasis Smart SIM. Prior to Oasis, Karl worked for Rivetz Corp, a Massachusetts-based start-up to promote developer tools for design-in of TEE-enables applications on Smartphones for payment and security. Karl also spent 5 years working in China for Gemalto (and Trustonic) as liaison and evangelist of embedded Mobile Near-Field Communications Payments & TEE security technologies to the OEM Smartphone/Tablet PC ecosystem. Weaver has a B.S degree in Business Management from Salve Regina University and a Certification in Mandarin Chinese Language, Customs, and Culture from National Taiwan Normal University.

Links

• Download mp3 (17.5 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Support us on Patreon

From the Australian government’s new “data-driven profiling” trial for drug testing welfare recipients, to US law enforcement’s use of facial recognition technology and the deployment of proprietary software in sentencing in many US courts … almost by stealth and with remarkably little outcry, technology is transforming the way we are policed, categorized as citizens and, perhaps one day soon, governed.

We are only in the earliest stages of so-called algorithmic regulation – intelligent machines deploying big data, machine learning and artificial intelligence (AI) to regulate human behaviour and enforce laws – but it already has profound implications for the relationship between private citizens and the state.

Furthermore, the rise of such technologies is occurring at precisely the moment when faith in governments across much of the Western world has plummeted to an all-time low. Voters across much of the developed world increasingly perceive establishment politicians and those who surround them to be out-of touch bubble-dwellers and are registering their discontent at the ballot box.

---

Setting some ground rules

By Christoph Salge, Marie Curie Global Fellow, University of Hertfordshire

How do you stop a robot from hurting people? Many existing robots, such as those assembling cars in factories, shut down immediately when a human comes near. But this quick fix wouldn’t work for something like a self-driving car that might have to move to avoid a collision, or a care robot that might need to catch an old person if they fall. With robots set to become our servants, companions and co-workers, we need to deal with the increasingly complex situations this will create and the ethical and safety questions this will raise.

Science fiction already envisioned this problem and has suggested various potential solutions. The most famous was author Isaac Asimov’s Three Laws of Robotics, which are designed to prevent robots harming humans. But since 2005, my colleagues and I at the University of Hertfordshire, have been working on an idea that could be an alternative.

Instead of laws to restrict robot behaviour, we think robots should be empowered to maximise the possible ways they can act so they can pick the best solution for any given scenario. As we describe in a new paper in Frontiers, this principle could form the basis of a new set of universal guidelines for robots to keep humans as safe as possible.

The Three Laws

Asimov’s Three Laws are as follows:

• A robot may not injure a human being or, through inaction, allow a human being to come to harm.
• A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.
• A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

While these laws sound plausible, numerous arguments have demonstrated why they are inadequate. Asimov’s own stories are arguably a deconstruction of the laws, showing how they repeatedly fail in different situations. Most attempts to draft new guidelines follow a similar principle to create safe, compliant and robust robots.

One problem with any explicitly formulated robot guidelines is the need to translate them into a format that robots can work with. Understanding the full range of human language and the experience it represents is a very hard job for a robot. Broad behavioural goals, such as preventing harm to humans or protecting a robot’s existence, can mean different things in different contexts. Sticking to the rules might end up leaving a robot helpless to act as its creators might hope.

Our alternative concept, empowerment, stands for the opposite of helplessness. Being empowered means having the ability to affect a situation and being aware that you can. We have been developing ways to translate this social concept into a quantifiable and operational technical language. This would endow robots with the drive to keep their options open and act in a way that increases their influence on the world.

When we tried simulating how robots would use the empowerment principle in various scenarios, we found they would often act in surprisingly “natural” ways. It typically only requires them to model how the real world works but doesn’t need any specialised artificial intelligence programming designed to deal with the particular scenario.

But to keep people safe, the robots need to try to maintain or improve human empowerment as well as their own. This essentially means being protective and supportive. Opening a locked door for someone would increase their empowerment. Restraining them would result in a short-term loss of empowerment. And significantly hurting them could remove their empowerment altogether. At the same time, the robot has to try to maintain its own empowerment, for example by ensuring it has enough power to operate and it does not get stuck or damaged.

Robots could adapt to new situations

Using this general principle rather than predefined rules of behaviour would allow the robot to take account of the context and evaluate scenarios no one has previously envisaged. For example, instead of always following the rule “don’t push humans”, a robot would generally avoid pushing them but still be able to push them out of the way of a falling object. The human might still be harmed but less so than if the robot didn’t push them.

In the film I, Robot, based on several Asimov stories, robots create an oppressive state that is supposed to minimise the overall harm to humans by keeping them confined and “protected”. But our principle would avoid such a scenario because it would mean a loss of human empowerment.

While empowerment provides a new way of thinking about safe robot behaviour, we still have much work to do on scaling up its efficiency so it can easily be deployed on any robot and translate to good and safe behaviour in all respects. This poses a very difficult challenge. But we firmly believe empowerment can lead us towards a practical solution to the ongoing and highly debated problem of how to rein in robots’ behaviour, and how to keep robots -– in the most naive sense -– “ethical”.

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

Join us at the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) for a full day workshop that will bring together international stakeholders in robotics to examine best practices for accelerating robotics innovation through strategic policy frameworks.

Best practices in designing effective roadmaps for robotics innovation

IROS Workshop | 8:30-17:00 September 28, 2017 | Vancouver Convention Centre | Vancouver BC

This is a unique opportunity to learn from people who have played a significant role in designing and implementing major strategic robotics initiatives around the globe.

Objectives
In the past decade, a number of governing bodies and industry consortia have developed strategic roadmaps to guide investment and development of robotic technology. With the roadmaps from the US, South Korea, Japan and EU etc. well underway, the time is right to take stock of these strategic robotics initiatives to see what is working, what is not, and what best practices in roadmap development might be broadly applied to other regions.

The objective of this two-part workshop is to examine the process of how these policy frameworks came to be created in the first place, how they have been tailored to local capabilities and strengths, and what performance indicators are being used to measure their success — so that participants may draw from international collective experience as they design and evaluate strategic robotics initiatives for their own regions.

Program Part ONE — Morning Session: “Developing innovation policy for robotics, and establishing key performance indicators that are relevant to your region”
The morning session will feature international speakers who have played a significant role in launching and shaping major strategic robotics initiatives across the globe. The focus of this session will be on the history and process of designing the roadmap (rather than on merely presenting the roadmap itself) and key performance indicators of roadmap success. Via presentations and panel discussion, the outcome of this session will be an exploratory overview of best practices and key performance metrics, so that participants can apply knowledge gained from the workshop as they design strategic robotics policy frameworks for their own regional or national contexts.

Program Part TWO — Afternoon Session: “Towards a national robotics strategy for Canada”
The afternoon session will bring together leading Canadian robotics experts from academia, industry, federal/provincial policy, and the national research council to discuss and strategize the future of robotics in Canada, with an emphasis on addressing the social, economic, legal/ethical and regulatory issues, and the robotics strengths and capabilities specific to this country. The main goals of this session will be to 1) establish a clear picture of the internal Canadian robotics landscape and how it compares to other nations worldwide, 2) discuss lessons learned in the International session within the Canadian context, and 3) discuss and identify gaps and opportunities for a Canadian initiative. Ultimately the Canadian session will serve as a venue for collecting data and viewpoints to support the development of a Canadian Robotics Roadmap.

Who should attend
This workshop is open to all members of academia, government, and industry with an interest in funding, policy and research strategy.

Part One of the workshop (morning session) will be broadly applicable to anyone with an interest in robotics policy, partnerships and funding.

Part Two (afternoon session) will be of particular interest to Canadian conference-goers as well as those who are interested in Canadian research and industry partnerships.

Call for participation
We are actively seeking participants for this workshop. If you are …

… involved in developing or evaluating a major strategic robotics initiative in your region and would like to participate in our international discussion, OR …

… are a member of the Canadian robotics ecosystem or are a Canadian roboticist living abroad who would like to be involved in a national robotics strategy for Canada …

… then please send an email with your expression of interest to: info@canadianroboticsnetwork.com. We look forward to hearing from you!!

Workshop Organizers

• Elizabeth Croft, Director, Collaborative Advanced Robotics and Intelligent Systems (CARIS) Lab, UBC
• Clément Gosselin, Professor, Laboratoire de Robotique, Université Laval
• Paul Johnston, Research Policy Consultant, former President of Precarn Incorporated
• Dana Kulić, Associate Professor, Adaptive Systems Laboratory, University of Waterloo
• AJung Moon, Co-Founder & Director, Open Roboethics Institute
• Angela Schoellig, Assistant Professor, Institute for Aerospace Studies (UTIAS), University of Toronto
• Hallie Siegel, Strategic Foresight & Innovation @ OCAD U, former Managing Editor @Robohub

Workshop Registration

Registration for IROS workshops is separate from the IROS conference fee. Please see the IROS Website for details: http://www.iros2017.org/registration-travel/registration# 

Early workshop registration deadline: July 22nd.

More Info
http://canadianroboticsnetwork.com/iros-workshop/
http://www.iros2017.org/program/workshops-and-tutorials

Contact
info@canadianroboticsnetwork.com

Last week I had the pleasure of debating the question “does AI pose a threat to society?” with friends and colleagues Christian List, Maja Pantic and Samantha Payne. The event was organised by the British Academy and brilliantly chaired by the Royal Society’s director of science policy Claire Craig. Here follows my opening statement:

My opening statement

One Friday afternoon in 2009 I was called by a science journalist at, I recall, the Sunday Times. He asked me if I knew that there was to be a meeting of the AAAI to discuss robot ethics. I said no I don’t know of this meeting. He then asked “are you surprised they are meeting to discuss robot ethics” and my answer was no. We talked some more and agreed it was actually a rather dull story: a case of scientists behaving responsibly. I really didn’t expect the story to appear but checked the Sunday paper anyway, and there in the science section was the headline Scientists fear revolt of killer robots. (I then spent the next couple of days on the radio explaining that no, scientists do not fear a revolt of killer robots.)

So, fears of future super intelligence – robots taking over the world – are greatly exaggerated: the threat of an out-of-control super intelligence is a fantasy – interesting for a pub conversation perhaps. It’s true we should be careful and innovate responsibly, but that’s equally true for any new area of science and technology. The benefits of robotics and AI are so significant, the potential so great, that we should be optimistic rather than fearful. Of course robots and intelligent systems must be engineered to very high standards of safety for exactly the same reasons that we need our washing machines, cars and airplanes to be safe. If robots are not safe people will not trust them. To reach it’s full potential what robotics and AI needs is a dose of good old fashioned (and rather dull) safety engineering.

In 2011 I was invited to join a British Standards Institute working group on robot ethics, which drafted a new standard BS 8611 Guide to the ethical design of robots and robotic systems, published in April 2016. I believe this to be the world’s first standard on ethical robots.

Also in 2016 the very well regarded IEEE standards association – the same organization that gave us WiFi – launched a Global initiative on Ethical Considerations in AI and Autonomous Systems. The purpose of this Initiative is to ensure every technologist is educated and empowered to prioritize ethical considerations in the design and development of autonomous and intelligent systems; in a nutshell, to ensure ethics are baked in. In December we published Ethically Aligned Design: A Vision for Prioritizing Human Well Being with AI and Autonomous Systems. Within that initiative I’m also leading a new standard on transparency in autonomous systems, based on the simple principle that it should always be possible to find out why an AI or robot made a particular decision.

We need to agree ethical principles, because they are needed to underpin standards – ways of assessing and mitigating the ethical risks of robotics and AI. But standards needs teeth and in turn underpin regulation. Why do we need regulation? Think of passenger airplanes; the reason we trust them is because it’s a highly regulated industry with an amazing safety record, and robust, transparent processes of air accident investigation when things do go wrong. Take one example of a robot that we read a lot about in the news – the Driverless Car. I think there’s a strong case for a driverless car equivalent of the CAA, with a driverless car accident investigation branch. Without this it’s hard to see how driverless car technology will win public trust.

Does AI pose a threat to society? No. But we do need to worry about the down to earth questions of present day rather unintelligent AIs; the ones that are deciding our loan applications, piloting our driverless cars or controlling our central heating. Are those AIs respecting our rights, freedoms and privacy? Are they safe? When AIs make bad decisions, can we find out why? And I worry too about the wider societal and economic impacts of AI. I worry about jobs of course, but actually I think there is a bigger question: how can we ensure that the wealth created by robotics and AI is shared by all in society?

Thank you.

The featured image of this article was used to advertise the BA’s series of events on the theme Robotics, AI and Society. The reason I draw your attention to it here is that one of the many interesting questions to the panel was about the way that AI tends to be visualised in the media. This kind of human face coalescing (or perhaps emerging) from the atomic parts of the AI seems to have become a trope for AI. Is it a helpful visualisation of the human face of AI, or does it mislead to an impression that AI has human characteristics?

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.

Robotics technology is no longer limited to industry. Climate Controls, 3D printers, surveillance robots, drones, household and even sex robots are entering the private market. The more autonomous they become, the more difficult it becomes to resolve conflicts, such as those between humans and software.

The law currently recognizes individuals, like you and me. Also companies, organizations and governments can negotiate agreements and liability. These non-natural persons are represented by real people (they should be controlled after all). But what about autonomous systems that take over tasks and make intelligent decisions that might be interpreted as a legal act?

Social robots will not just vacuum your house, they might pay bills, independently enter into contracts and, who knows, get in the car to get groceries for you. Civil law as it is written, however, sees the robot as an object, not as a subject with legal capacity. One issue is that reminiscent of Bicentennial Man, a science fiction film from 1999 based on a story by Isaac Asimov in 1977. The robot Andrew Martin wants to be recognized as a ‘natural person’—a request that the court rejects with the argument that a robot lives eternally. Years later, the robot asks for a review. An update enables him to die. Moreover, according to Andrew, the judge himself makes use of non-natural resources.

Industrial robots do not yet have legal capacity. They carry out instructions in a defined process. The need for legal personality arises only when participating in society. A social robot must make arrangements, for example, in his care function with physicians and suppliers. That cannot be without any acceptance of legal personality. But at what level will artificial intelligence be “equivalent” to that of natural persons?

The Turing test may have seemed definitive in 1950, but does it still count? According to the test, a machine must qualify for intelligence on a “human” level. The interrogator, for example, in a chat, has to get the impression that she is talking to a real person. The robot statements should be appreciated emotionally and morally and react to it appropriately. So, it has to have social intelligence. It also should respond appropriately to changing circumstances to be qualified as a dynamic action-intelligence.

Could you imagine a robot who is your colleague or boss? The Swedish series “Real Humans” has already dramatized the scenario. Can you dismiss individuals once their job is better done by a robot? Can we accept that a robot has control over an individual? Labour law does not give an answer. Topical is a situation in which a self-driving car crashes. According to road traffic laws, the driver is responsible. But what if the controller is dependent on road management, vehicle manufacturer, meteorological service, navigation systems and the algorithm that made the car self-learning?

Robot sustainable law is therefore particularly complicated in the area of liability. And what if a robot is guilty, does it make sense to punish him? Can we pull the plug, as in the movie I, Robot? At the same time, there has to be expected less conflict. Ninety percent of traffic accidents are caused by human error, the rest being due to circumstances such as a falling tree or flat tire.

And what is a natural person anyway? Is it a man or woman who was not born of another human being, but composed of an artificial heart, artificial kidney, artificial limbs, artificial brains, etc., and brought to life in a laboratory? What about discrimination? What if a human body has been upgraded with robotics, can we just switch them off?

Back to the distinction between a legal object and a subject of law. Add to that sui generis, a legal phenomenon that is the only one of its kind. Asimov already offered three laws:

• A robot may not cause a human injury or by omission allow overtaking any human injuries.
• A robot must obey the orders given it by human beings, except where such contracts are in conflict with the first law.
• A robot must protect its own existence, as far as such protection does not conflict with the First or Second Law.

Good thoughts, but motivated by fear and the desire for human control. Adherence to these laws might actually put the brakes on the development of artificial intelligence. But what we want is progress, right?

It’s time to create a commission for this issue—an international multidisciplinary committee consisting of lawyers, philosophers, ethicists, computer scientists, political scientists and economists. Otherwise, the robots might in the long run provide themselves with a solution.

More adapted to the societal need are the proposed laws of Murphy and Woods:

• A human may not deploy a robot without the human-robot work system meeting the highest legal and professional standards of safety and ethics.
• A robot must respond to humans as appropriate for their roles.
• A robot must be endowed with sufficient situated autonomy to protect its own existence as long as such protection provides smooth transfer of control which does not conflict with the First and Second Laws.

But there is a precondition that: A robot must have an added value in society by performing its task. I would add from a legal perspective:

• An autonomous intelligent robot must be accepted as an equal partner in performing legal acts.

Legally acting robots must be certified as such based on preconditions as: >turingtest level with a socially acceptable dynamic intelligence and societal and legal understanding of moral and legal norms.

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

• RoboLaw: Regulating robotics (video)
• Quest for Roboethics: An interview with Prof. Rafael Capurro
• Technical challenges in machine ethics
• How do we regulate robo-morality?

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

Whether an A.I. ought to be granted patent rights is a timely question given the increasing proliferation of A.I. in the workplace. Examples: Daimler-Benz has tested self-driving trucks on public roads^[1], A.I. technology has been applied effectively in medical advancements, psycholinguistics, tourism and food preparation,^[2] a film written by an A.I. recently debuted online^[3] and A.I. has even found its way into the legal profession,^[4] and current interest in the question of whether an A.I. can enjoy copyright rights with several articles having already being published on the subject of A.I. and copyright rights.^[5]

In 2014 the U.S. Copyright Office updated its Compendium of U.S. Copyright Office Practices with, inter alia, a declaration that  the Office will not register works produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author.”^[6]

To grant or not to grant: A human prerequisite?

One might argue that Intellectual Property (IP) laws and IP Rights were designed to exclusively benefit human creators and inventors^[7] and thus would exclude non-humans from holding IP rights. The U.S. Copyright Office’s December 2014 update to the Compendium of U.S. Copyright Office Practices that added requirements for human authorship^[8] certainly adds weight to this view.

However, many IP laws were drafted well before the emergence of A.I. and in any case, do not explicitly require that a creator or inventor be ‘human.’ The World Intellectual Property Organization’s (WIPOs) definition of Intellectual Property talks about creations of the mind^[9] but does not specify whether it must be a human mind. Similarly, provisions in laws promoting innovation and IP rights, such as the so-called Intellectual Property Clause of the U.S. Constitution^[10], also do not explicitly mention a ‘human’ requirement. Finally, it ought to be noted that while the U.S. Copyright Office declared it would not register works produced by a machine or mere mechanical process without human creative input, it did not explicitly state that an A.I. could not have copyright rights.^[11]

Legal personhood

One might also argue that an A.I. is not human, and is therefore not a legal person and, thus, is not entitled to apply for much less be granted a patent. New Zealand’s Patents Act, for example, refers to a patent ‘applicant’ as a ‘person’.^[12]

Yet this line of argument could be countered by an assertion that a legal ‘person’ need not be ‘human’ as is the case of a corporation and there are many examples of patents assigned to corporations.^[13]

The underlying science

To answer the question of patent rights for an A.I. we need to examine how modern A.I. systems work and, as an example, consider how machine translation applications such as Google Translate function.

While such systems are marketed as if they’re “magic brains that just understand language”,^[14]the problem is that there is currently no definitive scientific description for language^[15] or language processing^[16]. Thus, such language translation systems cannot function by mimicking the processes of the brain.

Rather, they employ a scheme known as Statistical Machine Translation (SMT) whereby online systems search the Internet identifying documents that have already been translated by human translators– for example books, and organizations like the United Nations, or websites. The system scans these texts for statistically significant patterns and once the computer finds a pattern it uses the pattern to translate similar text in the future.^[17] This, as Jaron Lanier and others note, means that the people who created the translations and make translation systems possible are not paid to for their contributions^[18].

Many modern A.I. systems are largely big data models that operate by defining a real world problem that needs to be solved, then conceiving a conceptual model to solve this problem which is typically a statistical analysis that falls into one of three categories: regression, classification or missing data. Data is then fed into the model and used to refine and calibrate the model. As the model is increasingly refined it is used to guide the location of data and, after a number of rounds of refinement finally results in a model capable of some predictive functionality.^[19]

Big data models can be used to discover patterns in large data sets^[20] but also can, as in the case of translation systems, exploit statistically significant correlations in data.

None of this, however, suggests that current A.I. systems are capable of inventive or creative capacity.

Patentability?

So to get a patent, an invention must:

• Be novel in that it does not form part of the prior art^[21]
• Have an inventive step in that it not obvious to a person skilled in the art^[22]
• Be useful^[23]
• it must not fall into an excluded category that can include discoveries, presentations of information and mental processes or rules or methods for performing a mental act.^[24]

Why discoveries are not inventions is tied with the issue of obviousness and as noted by Buckley J. in Reynolds v. Herbert Smith & Co., Ltd^[25] who stated:

“Discovery adds to the amount of human knowledge, but it does so only by lifting the veil and disclosing something which before had been unseen or dimly seen. Invention also adds to human knowledge, but not merely by disclosing something. Invention necessarily involves also the suggestion of an act to be done, and it must be an act which results in a new product, or a new result, or a new process, or a new combination for producing an old product or an old result.”

Therefore in order to get a patent, an A.I. must first be capable of producing a patentable invention but, given current technology, is this even possible?

A thought exercise

Consider the following:

You believe that as a person exercises more, he/she consumes more oxygen and have tasked your A.I. with analyzing the relationship between oxygen consumption and exercise.

You provide the A.I. with a model suggesting that oxygen consumption increases with physical exertion and data that shows oxygen consumption among people performing little, moderate (e.g. walking briskly) and heavy exercise (e.g. running).

The A.I. reviews the data, refines the model, collects more data and comes up with a predictive model (e.g. when a person exercises X amount, he/she consumes Y amount of oxygen and when the person doubles his/her exertion, his oxygen consumption rate triples).

As this is essentially a statistical regression, the model will not always completely accurate in its predictions due to differences between individuals (i.e. for some persons the model will predict oxygen consumption fairly accurately, for others its results will be far off).

However, this particular model has another, more fundamental limitation – it fails to consider that a human cannot exercise beyond a certain point because his/her heart would be incapable of sustaining such levels of exertion^[26] or because over-exercise may trigger an unexpected reaction (e.g. death).^[27]

If one were to feed this model data of persons who have collapsed or died during exercise (and thus, in the latter case, not consume any oxygen), would the A.I. be able to ‘think outside its box’ and:

• Question the cause of these data discrepancies and have the initiative to conduct further investigation?
• Note and correct the limitation in the original model (which would require a significant amendment)?

Or would it simply alter the existing model by changing the slope of the regression line?

SMT and other A.I. have similar limitations, in the case of SMT, once the system is built, linguistic knowledge becomes necessary to achieve perfect translation at all grammatical levels^[28] and SMT systems presently cannot translate cultural components of the source text into the target language, provide very literal, word for word translations that do not recognize idioms, slang, and terms that are not in the machine’s memory and lack human creativity^[29] To do so would require a change to the underlying machine translation model, and the question arises whether this would have to be done by the human creators of the SMT or whether the SMT itself would be able to make the necessary corrections and adjustments to the model.

Should the SMT or, in the earlier example the A.I., be unable to improve and, in this case, innovate on the existing model does it have the creative or inventive capacity to conceive an invention is truly inventive? And if either the SMT or the AI can produce something that appears novel and inventive, given the nature of how A.I. presently operates (i.e. as big data models), would such a product be the result of an analysis of existing data to uncover hitherto unseen relationships – in other words, a discovery?

Returning to the original question about patent rights for an A.I., perhaps the question we should ask is not whether an A.I. should be able to get a patent, but whether an A.I., given current technology, can create a patentable invention in the first place and if the answer to that question is ‘no’, then the question of granting patent rights to an A.I. is moot.

References:

[1]  Jon Fingas, ‘Daimler tests a self-driving, mass-produced truck on real roads’, Engadget, Oct. 4, 2016.

[2] Sophie Curtis, ‘Cognitive Cooking: How Is A.I. Changing Foodtech?’ RE•WORK, April 19 2016.

[3] Analee Newitz, ‘Movie written by algorithm turns out to be hilarious and intense’ ArsTechnica, June 9, 2016.

[4]  Susan Beck, ‘AI Pioneer ROSS Intelligence Lands Its First Big Law Clients, The American Lawyer, May 6, 2016.

[5] See for example:

• Madeleine de Cock Buning ‘Is the EU exposed on the copyright of robot creations?‘ www.roboticslawjournal.com,Nov. 2015.
• Daniela Hernandez, ‘Could you take a robot to court if it steals your work? Fusion, Nov. 11, 2015.

[6] Copyright Office, Compendium of U.S. Copyright Office Practices (3d ed. 2014). § 313.2

[7] Hettinger argued that ‘the most powerful intuition supporting property rights is that people are entitled to the fruits of their labor’

• See: Edwin Hettinger, “Justifying Intellectual Property’, Philosophy & Public Affairs, Vol. 18, No. 1, Winder 1989, p. 31-52

[8] Copyright Office, Compendium of U.S. Copyright Office Practices (3d ed. 2014). § 306.

[9] According to WIPO, ‘Intellectual property (IP) refers to creations of the mind, such as inventions; literary and artistic works; designs; and symbols, names and images used in commerce.’

[10] Article I, Section 8, Clause 8 of the United States Constitution states: The Congress shall have Power To…. promote the Progress of Science and useful Arts, by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries.

[11] According to the U.S. Copyright Office, ‘Copyright exists from the moment the work is created. You will have to register, however, if you wish to bring a lawsuit for infringement of a U.S. work’

See ‘Copyright in General’,

[12] s.5(1) Patents Act 2013

[13] See for example, U.S. Patent 5,953,441 ‘Fingerprint sensor having spoof reduction features and related methods’ which was assigned to Harris Corporation.

[14] Nilagia McCoy  ‘Jaron Lanier: The Digital Economy Since Who Owns The Future?’ October 8, 2015.

[15] This was noted by Jaron Lanier who delivered the keynote address at the opening of the Conference on the Global Digital Content Market taking place from April 20-22, 2016 at WIPO Headquarters in Geneva, Switzerland.

• Catherine Saez, ‘IP Should Serve More Actors In New Ways, Keynote Speaker At WIPO Says’, Intellectual Property Watch, April 21, 2016.

[16] See for example:

• Erin Harte, ‘Language Processing In The Human Brain’, Brainworld, July 22, 2011.
• AD Friederici, The brain basis of language processing: from structure to function, Physiol Rev. 2011 Oct;91(4):1357-92.
• Jerry Ball, Mary Freiman, Stuart Rodgers & Christopher Myers, ‘Toward a Functional Model of Human Language Processing.’

[17] Inside Google Translate, July 9, 2010.

[18] Catherine Jewell, ‘Digital pioneer, Jaron Lanier, on the dangers of “free” online culture,’ WIPO Magazine, April 2016.

[19] Noah Silverman.

[20] i.e. ‘data mining’.

[21] s 6, New Zealand Patents Act 2013

[22] s 7, New Zealand Patents Act 2013

[23] s 10, New Zealand Patents Act 2013

[24] See for example:. 93(2) Hong Kong Patents Ordinance, Cap 514 or the Canadian Patent Act R.S.C., 1985, c. P-4

[25] (1903), 20 R.P.C. 123

[26] Wikipedia, ‘Heart Rate’.

[27] This may be caused by a congenital condition but some also believe that prolonged excessive exercise may exacerbate matters. See:

• Lou Schuler, ‘Death by Exercise’ Men’s Health June 8, 2003.
• Timothy D Noakes, ‘Sudden Death and Exercise’.

[28] Mireia Farrus, Marta R. Costa-Jussa, Jose B. Marino, Marc Poch, Adolfo Hernandez, Carlos Henrıque,  Jose A. R. Fonollosa, ‘Overcoming statistical machine translation limitations: error analysis and proposed solutions for the Catalan–Spanish language pair’ Language Resources & Evaluation, DOI 10.1007/s10579-011-9137-0.

[29] ‘Machine Translation vs. Human Translators’ 

See also:

• Wikipedia, ‘Statistical Machine Translation’.

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.

An Air Force airman at the control module of an MQ-9 Reaper. Credit: John Bainter/USAF

Machine ethics offers an alternative solution for artificial intelligence (AI) safety governance. In order to mitigate risks in human-robot interactions, robots will have to comply with humanity’s ethical and legal norms, once they’ve merged into our daily life with highly autonomous capability. In terms of technical challenges, there are still many open questions in machine ethics. For example, what is deontic logic and how can it be used for improving AI safety? How do we fashion the knowledge representation for ethical robots? What about the adaptiveness of the ethical governance? These are all significant questions for us to investigate.

In this interview, we invite Prof. Ronald C. Arkin to share his insights on robot ethics, with a focus on its technical aspects.

Date: February 1st 2017

Interviewee: Prof. Ronald C. Arkin, Regents’ Professor and Associate Dean in the College of Computing at the Georgia Institute of Technology and Executive Committee Member of IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems

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).

Ron Arkin

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

ARKIN: I have been a roboticist for 35 years, so it’s hard to tell [only] a little, but I will do my best. Currently I am a Regents’ Professor and Associate Dean in the College of Computing at the Georgia Institute of Technology. I got my Ph.D. from the University of Massachusetts in 1987, and have been working on robotics since that time. I actually have degrees in chemistry as well—a bachelor’s and a master’s in organic chemistry. So, I have a rather diverse background and followed a non-traditional path compared to most computer scientists.

Q2 WENG: What is your definition of “Ethical Robots”?

ARKIN: That’s an interesting question! I have been asked that one before. I would say an ethical robot is a robotic system that is able to comply with the ethical and social norms of human beings—in some cases in accordance with international law, in other cases in accordance with national or local law. In addition, also being able to comport with humans in a natural manner, obey, and adhere to the same principles as an ethical person.

Q3 WENG: Could you please tell us why you are particularly interested in “Embedded Ethics”? Why is this concept so important?

ARKIN: That’s why you need to read the preface of my book [Governing Lethal Behaviour in Autonomous Robots]. It’s a rather long story. But let me try to give you a short version. Again, it dates back to a meeting—the first international symposium in Roboethics in 2004—where I was exposed to international conventions, e.g., the Geneva convention. It also led me to understand the Vatican’s position on how they viewed appropriate ethical interactions. Perhaps even more important than that one experience was the fact that we roboticists that have been in the field for some time finally started to have success, and we were seeing our technology move out of the laboratory community and into the real world. As such, it wasn’t hard to see how this could go in a variety of different directions.

Some robotics technology could benefit humanity, some not so much. At that point, one has to ask, “who is responsible for this?” So I assumed that, in part, it was myself. I believe that I have to take the responsibility for the technology that I helped to create. The issue is that we, as roboticists, had actually succeeded in many ways in terms of creating technology that we only envisioned when we first started that is going to have potentially profound impact on our society and the world as a whole. As such, we should be proactive in the ways in which we move forward [in order] to get a better understanding of the consequences of the work, and the social implications of the technology we are designing.

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

Q4 WENG: The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems has published their report “Ethically Aligned Design” in December 2016. As a member of the IEEE Global Initiative, could you please tell us about your role?

ARKIN: I serve a variety of roles. First, I am on the executive committee of that particular initiative, so I work at a high-level with about 30 other people or so. We have committees that large. I also co-chair the committee in Affective Computing. Joanna Bryson is my co-chair on that.

Affective Computing is concerned with the issues surrounding the illusion of emotions we can potentially create in these artifacts, and the ways human beings can bond to them. We are exploring a variety of different things, including robot intimacy, or the notion of applying robotic nudges and moving people in certain directions subtly, and in so doing to change the way people act and behave using these technologies, while trying to understand what may or may not be appropriate guidelines based on ethical considerations.

It’s about 15-20 people in that committee. We are one of the newer committees and we only have a couple of pages in the initial design report. But actually, in the June meeting in Austin, for the next release of the document 2.0, we will have as much as the other committees do. Finally, I am also a member of the humanitarian committee. I think it is called economic and humanitarian. I don’t know the exact title, but I am interested in the humanitarian side, and potential uses of robotics for humanitarian applications.

Q5 WENG: What is “Deontic Logic”? Why does it matter to machine ethics?

ARKIN: It may or may not matter. It’s just one approach to a particular problem. Deontic logic is a logic of prohibitions, obligations and permissions. It is one type of framework that is more transparent in order to get a better understanding of the way in which systems operate in the real world. Then it explains its reasoning to a human being, as compared to say deep learning or other forms of neural networks which may indeed provide good results but provide no explanatory capability to humans after the decision has been made.

The notion of prohibitions basically tells the robot some things it cannot do. The notion of permissions describe the things it is potentially allowed to do. And the notion of obligations says things that the robot must do under specific circumstances. It provides a nice framework of being able to explore morality. Others have already explored this, like Bringsjord at RPI who has applied deontic logic in this framework. We are certainly not the first in that particular space. Much of the work we have done has dealt with first-order predicate logic as a basis. It doesn’t have to be deep because it is so explicit in many cases.

Q6 WENG: Your hybrid embedded ethics framework aims for governing lethal behavior of military robots. Can we apply the same technical framework to service robots? For example, personal care robots might have some non-lethal, but still risky autonomous behaviors that need to be regulated by machine ethics.

ARKIN: I believe so. Indeed the whole point of the architecture is trying to design the systems to make them generalizable and not ad hoc for particular sets of circumstances. We have yet to look at service robotics in a traditional sense, but we have already developed something we refer to as the intervening Ethical Governor, which we are using for health care applications—particularly for assisting the management of two human beings in a particular relationship, like a patient and their care giver.

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

We are doing work for the National Science Foundation, joint with Tufts University, looking at how in early stage Parkinson’s there is a condition called the facial masking. The loss of muscle movements in the face of the patient can produce stigmatization, and the patient-care giver relationship deteriorates due to the loss of non-verbal communication. We just had a paper accepted at ICRA describing the architecture that we have and how it has been modified from the military version. We generalized it from the military constraint-based version to a rule-based version.

But also, instead of using the international humanitarian law, we are using occupational therapy guides as a basis for generating the responses when two human beings in the relationship step outside of acceptable bounds. So the acceptable bounds now are not defined by international humanitarian law, but they are defined by occupational therapy—such as when a patient or a care giver start to yell at each other, or one starts to leave the room. The hard part is recognizing when dignity is being abridged, particularly in the patient. So we model the moral emotions of empathy, shame and embarrassment. We tried to ensure that the empathy level in the care giver remains within acceptable bounds and that the patient shame and embarrassment doesn’t rise to unacceptable levels. So the intervening Ethical Governor intervenes when a really inappropriate event occurs. It then provides strong corrective action by the robot to encourage people to get along better. The moral adaptor component which we used in the ethical architecture—initially with the guilt model—has now been extended to other moral emotions like shame, embarrassment, guilt and empathy [in order to] try and provide more subtle non-verbal queues [to help the] robot steer the relationship in the correct way before it get out of hand.

Q7 WENG: Regarding your research on machine ethics, what kind of indicators you use to evaluate the final outputs of your project?

ARKIN: In the first one, we were designing a prototype to prove the concept of the architecture. We never make the claim that this is the best way to do it. It is just one way to do it. Then we demonstrate that particular capability through the use of simulations and other aspects. The system was not intended to be fielded, but hopefully others could take those core ideas and potentially put them to use in the real world if they so choose. For the intervening governor, we’re running human subject tests right now—not with Parkinson’s patients yet, but with the elderly population, 50 or older. We’re trying to get a better understanding of the correct sets of rules, and to correct the interventions in a normative fashion, so we can ultimately move on in the final year of the grant to work with actual Parkinson’s patients. Again, using standard HRI technics, such as recording the kinds of reactions they have and parsing the data from the sessions and using pre- and post- evaluation questionnaires.

Q8 WENG: Let’s talk about your proposed machine ethics framework. You had mentioned that it includes four main parts: (1) Ethical Governor (2) Ethical Behavior Control (3) Ethical Adaptor (4) Responsibility Advisor. First of all, what is the major difference between Ethical Governor and Ethical Behavior Control? Is it the difference between deliberative and reactive control, or something else?

ARKIN: The Ethical Governor is basically a standalone component to the architecture which is a bolt on component at the end of the existing system. In the case of military scenario: asking for permission—should it fire or not. This is an intervening stage which either grants or denies permission through the validation of permission-to-fire variable. So it is straightforward thing to be able to do. The Behavior Ethical Control is a different kind of thing as it works purely with the reactive component. What it tries to do is, for each of the individual behaviors themselves, to respond whether or not to engage a target. This is prior to dealing with the Ethical Governor making the decision; trying to make the decision correctly before it gets to the Ethical Governor, where individual behaviors are given ethical guidelines to try and ensure that the behavior is correct itself. Each of the behaviors is provided with appropriate ethical constraints. So the difference is: one is located within the reactive component in each of the individual behaviors that makes the activity of the architecture, and the Ethical Governor is at the end of the architectural chain.

Q9 WENG: What is the importance of Ethical Adaptor? What kinds of machine learning skill that you chose to improve its adaptiveness?

ARKIN: Machine learning is something we haven’t generally explored in this particular context. Especially the military context, we kind of engineer out the adaptiveness and machine learning for fear that the robot would be granted the authority to start to generalize the targets in the field, which we feel is inappropriate. Learning after action is okay. but that’s a different story. The importance of the Ethical Adaptor, and its cognitive models of guilt that we use, is the fact that even the actions the agent takes may inadvertently end up unethical. This is referred to as a “moral luck”. It could be good luck or bad luck. But if it is bad luck, you want to be able to ensure proactively that the bad action doesn’t occur again. That’s actually the functions of cognitive guilt for people as well to reduce the likelihood of reoccurrence of a behavior that resulted in bad actions. By giving this to a robot we hope that if it makes a mistake it will not repeat it. The probability of that behavior reoccurring would be reduced.

The best example is the case of battle damage assessment for a military scenario. For example, if a robot does its assessment and it looks like a released weapon wouldn’t create too much collateral damage, within acceptable limits, then it will release the weapon. But after it does it, the battle damage action is actually more severe then, it initially appeared to be. Under those circumstances, we want the robot in the field to reduce the probability of releasing the weapon again under similar circumstances. That’s, in essence, the analogue of guilt we use, and eventually, it will get to the point that the robot will not engage targets at all. Again, the software is updated to make sure the use is consistent with Geneva convention.

Q10 WENG: The Laws of War (LOW) and Rules of Engagement (ROE) are written in the form of natural language. How did you transfer these norms into machine readable formats?

ARKIN: It’s important to keep it in mind that we do not try and capture all the Rules of Engagement and all the Laws of War. We always advocate that the system should be used in very narrow circumstances and very narrow situations, such as building clearing operations or counter-sniper operations. It’s impossible to capture all human morality and all the Laws of War at this particular point of time. So, the question is what are the relevant Laws of War and Rules of Engagement for these particular narrow situations that the robot will find itself in.

Let’s take a room clearing operation. We try and do this using these constraint-based approaches. The Laws of War basically say that if you see a civilian, you should not shoot them; if you see a surrendered person, you should not shoot them. For aerial vehicles, if you are outside the kill zone (this is the simulations we did) which is designated by the Rules of Engagement, you cannot fire your weapon—explain simply why you cannot do that. If you release the weapon a toward a legitimate target but it would result in damage of cultural property, like a mosque or church or some similar circumstance, that is illegal as well. You are forbidden from doing those sort of things.

So, the initial work we did was more for aerial circumstances. We also computed the collateral damage using a battle damage assessment strategy to determine whether if it is within acceptable limits for a particular target and to restrain the weapon for proportionality. To be able to do this you have to be able to understand the military necessity of the target, which is assigned by a human being. You have to be able to understand the proportionality of the weapon. In other words: Which weapon is sufficient to take out the target but to do no more damage of the surroundings than is absolutely necessary? You have to ensure that you don’t destroy cultural property as well. Basically, adhere to all necessary principles, such as discrimination which is to be able to tell apart combatants and non-combatants. We also state we should restrict the use of these particular systems for high-intensity combat operations, or inter-state warfare, and not the kind of circumstances you find in modern counter- insurgency operations. They should be used with great care and great caution in very narrow circumstances where the predictability of their performance is far more likely to be good.

Q11 WENG: Why did you choose case-based reasoning (CBR) but not rule-based reasoning (RBR) when you designed Responsibility Advisor?
ARKIN: Historically we used case-based reasoning a lot for a variety of different reasons. Part of the reason is to gain information from previous experts. One of the examples in the past was to work with snipers in the laboratory. We can work with experts. It can be legal experts, it can be medical experts, it can be military experts. Again, the primary reason is to be able to readily use the experience of warfighters to guide us in operations.

Q12 WENG: Finally, your proposal “Governing Lethal Behavior: Embedding Ethics in a Hybrid Deliberative/Reactive Robot Architecture” was published in 2007. There have been great technological improvements in artificial intelligence in the past decade. Are there any recent updates from your robot ethics research, or anything that you want to share with us?

ARKIN: The project ended around 2010, so there is additional information. As I say, I would encourage those who are really interested to take a look at the book entitled “Governing Lethal Behavior in Autonomous Robots” . That represents the final statement and outcome for that particular project and includes the significant technical details describing that work. Recent advances include the application in other domains, such as the caregiver-patient relationship [discussed above] using the same underlying principles, including both the Moral Adaptor and Ethical Governor in a slightly different. If we were successful, it may also be useful for assisting other human-human relationships, such as a parent and a teenager who may be at odds with one another or even in marriage consulting. We hope to use robots for the benefit of mankind, whether it’s to make sure that warfare is conducted within internationally agreed upon laws, or whether it’s to ensure that people behave appropriately toward each other

If you enjoyed this article, you may also enjoy:

• How do we regulate robo-morality?
• One being for two origins: A new perspective on roboethics
• 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.

Image: IEEE

On the 15th November 2016, the IEEE’s AI and Ethics Summit posed the question: “Who does the thinking?” In a series of key-note speeches and lively panel discussions, leading technologists, legal thinkers, philosophers, social scientists, manufacturers and policy makers considered such issues as:

• The social, technological and philosophical questions orbiting AI.
• Proposals to program ethical algorithms with human values to machines.
• The social implications of the applications of AI.

Click here to read the final report, and enjoy a selection of videos from the conference below.

Welcome: Marko Delimar
Keynote Speaker: Wojciech Wiewiórowski

Panel 1: Autonomous Systems – Managing Risk and Reward
Panel Members: Raja Chatila, Kay Firth-Butterfield, Juha Heikkilä, Jérôme Perrin

Panel 2: Programming Human Ethics: Cui Bono?
Panel Members: Joanna Bryson, Mady Delvaux, Sarah Spiekermann, Corrine Cath

Panel 3: Social Implications – Perils & Promises of AI
Panel Members: Greg Adamson, Nikolaos Mavridis, Paul Nemitz, Aurélie Pols

Closing Remarks: John C. Havens

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

• MIT Media Lab to participate in $27 million initiative on AI ethics and governance
• 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

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

Part 1: Autonomous Systems and Safety

We all rely on machines. All aspects of modern life, from transport to energy, work to welfare, play to politics depend on a complex infrastructure of physical and virtual systems. How many of us understand how all of this stuff works? Very few I suspect. But it doesn’t matter, does it? We trust the good men and women (the disgracefully maligned experts) who build, manage and maintain the infrastructure of life. If something goes wrong they will know why. And (we hope) make sure it doesn’t happen again.

All well and good you might think. But the infrastructure of life is increasingly autonomous – many decisions are now made not by a human but by the systems themselves. When you search for a restaurant near you the recommendation isn’t made by a human, but by an algorithm. Many financial decisions are not made by people but by algorithms; and I don’t just mean city investments – it’s possible that your loan application will be decided by an AI. Machine legal advice is already available; a trend that is likely to increase. And of course if you take a ride in a driverless car, it is algorithms that decide when the car turns, brakes and so on. I could go on.

Algorithmic trading is now commonplace

These are not trivial decisions. They affect lives. The real world impacts are human and economic, even political (search engine results may well influence how someone votes). In engineering terms these systems are safety critical. Examples of safety critical systems that we all rely on from time to time include aircraft autopilots or train braking systems. But – and this may surprise you – the difficult engineering techniques used to prove the safety of such systems are not applied to search engines, automated trading systems, medical diagnosis AIs, assistive living robots, delivery drones, or (I’ll wager) driverless car autopilots.

Why is this? Well, it’s partly because the field of AI and autonomous systems is moving so fast. But I suspect it has much more to do with an incompatibility between the way we have traditionally designed safety critical systems, and the design of modern AI systems. There is I believe one key problem: learning. There is a very good reason that current safety critical systems (like aircraft autopilots) don’t learn. Current safety assurance approaches assume that the system being certified will never change, but a system that learns does – by definition – change its behaviour, so any certification is rendered invalid after the system has learned.

And as if that were not bad enough, the particular method of learning which has caused such excitement – and rapid progress – in the last few years is based on Artificial Neural Networks (more often these days referred to as Deep Learning). A characteristic of ANNs is that after the ANN has been trained with datasets, any attempt to examine its internal structure in order to understand why and how the ANN makes a particular decision is impossible. The decision making process of an ANN is opaque. Alphago’s moves were beautiful but puzzling. We call this the black box problem.

Safety critical systems such as aircraft autopilots do not learn

Does this mean we cannot assure the safety of learning autonomous/AI systems at all? No it doesn’t. The problem of safety assurance of systems that learn is hard but not intractable, and is the subject of current research*. The black box problem may be intractable for ANNs, but could be avoided by using approaches to AI that do not use ANNs.

But – here’s the rub. This involves slowing down the juggernaut of autonomous systems and AI development. It means taking a much more cautious and incremental approach, and it almost certainly involves regulation (that, for instance, makes it illegal to run a driverless car unless the car’s autopilot has been certified as safe – and that would require standards that don’t yet exist). Yet the commercial and political pressure is to be more permissive, not less; no country wants to be left behind in the race to cash in on these new technologies.

This is why work toward AI/Autonomous Systems standards is so vital, together with the political pressure to ensure our policymakers fully understand the public safety risks of unregulated AI.

In my next blog post I will describe one current standards initiative, towards introducing transparency in AI and Autonomous Systems based on the simple principle that it should always be possible to find out why an AI/AS system made a particular decision.

The next few years of swimming against the tide is going to be hard work. As Luke
Muehlhauser writes in his excellent essay on transparency in safety-critical systems “…there is often a tension between AI capability and AI transparency. Many of AI’s most powerful methods are also among its least transparent”.

*some, but nowhere near enough. See for instance Verifiable Autonomy.

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

The population of the scenic ski-resort Davos, nestled in the Swiss Alps, swelled by nearly +3,000 people between the 17^th and 20^th of January. World leaders, academics, business tycoons, press and interlopers of all varieties were drawn to the 2017 World Economic Forum (WEF) Annual Meeting. The WEF is the foremost creative force for engaging the world’s top leaders in collaborative activities to shape the global, regional and industry agendas for the coming year and beyond. Perhaps unsurprisingly given recent geopolitical events, the theme of this year’s forum was Responsive and Responsible Leadership.

With the onset of the fourth industrial revolution, increasingly discontented segments of society not experiencing congruous economic and social progress are in danger of existential uncertainty and exclusion. Responsive and Responsible Leadership entails inclusive development and equitable growth, both nationally and globally. It also involves working rapidly to close generational divides by exercising shared stewardship of those systems that are critical to our prosperity.

In the end, leaders from all walks of life at the Annual Meeting 2017 must be ready to react credibly and responsibly to societal and global concerns that have been neglected for too long.”

Developing last year’s theme—“The fourth industrial revolution”—this year’s luminaries posited questions, among many others, concerning incipient robotics and artificial intelligence technologies set to have a pronounced impact on the global economy and global consciousness alike. What can we learn from the first wave of AI? How can the humanitarian sector benefit from big data algorithms? How will drone technology change the face of warfare? Can AI and computational tech help foster responsive and responsible leadership? What are the downsides of technology in the fourth industrial revolution?

Enjoy a selection of tech-themed videos below.

And a bit about global science including big data, open source science and education.

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!

The European Robotics Week in 2016 took place from 18 to 22 November in several countries including The Netherlands, Austria, Lithuania, Norway, Portugal, Serbia and many more. This event has been occurring since 2011 to spread public awareness of robotics applications and brings together industry, researchers and policymakers. The central event this year was held in Amsterdam. I attended one of the 5 days of activities in the Maritime Museum. The theme was ‘Robots at your service – empowering healthy aging’ which encompassed a variety of activities arranged over the 5 day duration, including debates, open sessions where you could network while interacting with different kinds of robots, workshops for children and a 2 day hackathon. I attended the robot expo and two of the debate sessions which I will summarise below.

Robot Exhibition

Credits: Visual Outcasts

Although it’s clearly still early days for general consumer robotics in terms of the price-value ratio, there are ever more options available for enthusiasts and for very specific applications. The exhibition had a good selection, including these lovely bots:

• Inmoov open source 3d printed robot
• KUKA Robotics human safe industrial robot with fancy torque sensors
• Tiago Pal, ROS-based mobile manipulator
• Paro the therapeutic seal robot
• Pleo the dinosaur pet
• Softbank’s Pepper and Nao robots, Pepper being hosted by Decos, which uses Pepper as a receptionist
• Meccano’s Meccanoid G15 robot
• Robokind’s Milo robot, for teaching children with autism

Panel Discussion: Roboethics

This discussion was about ethics in robotics but it touched a really wide variety of aspects around this, including some philosophy. The speakers were of a very high standard and from a wide variety of backgrounds which gave the discussion its great breadth.

Here are some highlights:

Robots in care: good or bad?

• How should robots in care evolve?

• Robots should be applied to care because the need for care increases as populations in developed countries age, while the labour force interested in care shrinks. But are robots really the answer to this sensitive problem?
• The distinction was made that a wide range of activities qualify as ‘care’, ranging from assisting people to care for themselves, to caring for them, to providing psychological and emotional support in times of depression, distress or loneliness. Are robots suitable for all of these kinds of activities or only a spectrum? Before you judge, consider this example given, of a Nao robot used in interacting with children with diabetes, in the PAL project (Personal Assistant for health Lifestyle). The robot interacts with the children to educate them about their illness and help them track it. The children confide in the robot more easily than adults and hospital attendance in children with diabetes goes up. This is an example of using robots to build a relationship and put people at ease – something that the robot does more easily in this case than a human. When is a robot more trustworthy than a human? When is the human touch really needed?
• Should we want robots to be more human when they are used for care? In some cases we do, when there is a need to soothe and connect, to comfort. But in other cases a more impersonal and less present robot might be desirable. For instance, if you needed help going to the toilet or rising from bed for the rest of your life, would you need a lot of human interaction around that, or prefer it to blend seamlessly into your life to enable you to be as independent as possible?

Robo ethics and liability.

• Responsibility vs liability of robots for their misdeeds

• This question always comes up in a discussion about robot ethics – people feel uncomfortable with the idea of a robot’s accountability for crimes. For instance, if an autonomous car runs over a pedestrian, who would be responsible for that, the car, owner or manufacturer?
• A good point was raised by philosophy professor Vincent Muller to take this argument further. If a child throws a stone through a window, she is responsible for the action but the parent is liable for damages. In the same way, a robot can be responsible for doing something wrong, but another entity, like the owner, might be liable for damages caused.
• When discussing that a robot can be held liable for a crime, we imply it can understand that it’s actions were wrong and did it anyway. But robots as yet have no understanding of what they are doing, thus the conclusion was that a robot cannot be meaningfully convicted of a crime.

Panel Discussion: Our Robotic Future

In this next session, a general discussion on the future of robotics ensued, followed by each speaker giving their wish and hope for this future. There was a strong Euro-centric flavour to this discussion, which gave a fascinating insight into the European search for identity in this time of change – in the robotics and AI revolution, who are we and what do we stand for? How will we respond to the threats and oppourtunities? How can we lead and usher in a good outcome? The panel itself fell on the optimistic side of the debate, looking forward to positive outcomes.

Robotics Reasearch.

• The debate started off underlining the need to share information and research so that we can progress quickly with these high potential technologies.
• A distinction was made between American and European methods of research in AI and robotics

• American research is funded by defence budgets and not shared openly
• In the US, research is done by large corporations like Facebook and Google, and is often funded by DARPA.
• In Europe, research is funded by the European Commission, and often is performed through startups which means less brute strength, but more agility to bring research to fruition. However because these startups are so small, they can be reluctant to share their intellectual property which might be their only business case.

Accepting the robot revolution

• There is a lot of hype about robots and AI in the media which stirs people’s imaginations and fears – how can we usher in all the benefits of the robot revolution?

• Part of the fear is that people don’t like to accept that the last distinction we have of being the smartest on Earth could be lost.
• There is a growing economic divide caused by this technological revolution
• We should not create a system that creates advantage for only a select group, but aim for an inclusive society that allows all to benefit from abundance of robotics.
• People can be less afraid of robots if the value they add is made clear, for example a robot surgeon which is more accurate than a human surgeon can be viewed positively instead of as a threat.
• Technological revolutions are fuelled by an available workforce which can pick up the skills needed to usher them in. For example, in the industrial revolution, in which agricultural workers could be retrained to work in factories, and later a large labour force was available to fuel the IT revolution which, again, would have put many out of work by automating manual tasks. There is a concern that with STEM graduates on the decline, we will lack the skilled resources to build momentum for AI and Robotics.
• Investors in robotics and AI are discouraged by the growing stigma around these technologies.
• Communication policies on this topic are designed around getting people to understand the science, but this thinking must shift. The end users who currently fear and lack understanding must become the center of communication in the future – AI and robotics must enable them and they should have the tools to judge and decide on it’s fate.

Conclusion

This is certainly an exciting time to be alive, as there is so much to still determine and discover in the growth of the AI and Robotics industries and disciplines. Such an event also highlights how far we are from this reality – 10 year horizons were discussed for AI and Robotics to become commodities in our homes. It is very encouraging to see the clear thinking and good intentions that go into making these technologies mainstream. In the coming months I’d like to dig into the topics of ethics, regulation, EU funding, and what the future of AI and robotics could bring.

Click here to visit Thosha Moodley’s blog.

If you enjoyed this article, you may also enjoy:

• Considering robot care, ethics & future tech at #ERW2016 European Robotics Week
• Survey: Evaluate ethics of health related privacy with care robots
• Care-O-bot 4 celebrates its premiere as a shopping assistant
• Robot companions are coming into our homes — how human should they be?

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

Photo credit: Robert Shields

Will your next doctor be an app? A cost-cutting NHS wants more patients to act as “self-carers,” with some technologized assistance. A series of flowcharts and phone trees might tell parents whose children have chicken pox how best to care for them—no visits to surgeries required. Or a mole-checking app might tell a worrywart when a given skin discoloration looks harmless, and when to go to a dermatologist, by comparing it to thousands of images in a database.

Cost-cutters in the legal field also promise an algorithmically cheapened future. Tax software simplifies the process of filing by walking the filer through a series of questions. Documents that might have taken human attorneys months to read, can be scanned for keywords in a matter of seconds. Predictive policing promises to deploy force with surgical precision.

All these initiatives have some promise, and may make health care and legal advice more accessible. But they are also prone to errors, biases, and predictable malfunctions. Last year, the US Federal Trade Commission settled lawsuits against firms who claimed their software could aid in the detection of skin cancer, by evaluating photographs of the user’s moles. The FTC argued that there was not sufficient evidence to support such claims. The companies are now prohibited from making any “health or disease claims” about the impact of the apps on the health of users unless they provide “reliable scientific evidence” grounded in clinical tests. If algorithms designed merely to inform patients aren’t ready for prime time, why presume diagnostic robots are imminent?

Legal automation has also faced some serious critiques lately. The University of North Carolina legal scholar Dana Remus has questioned the value and legitimacy of the “predictive coding” now deployed in many discovery proceedings. She and co-author Frank S. Levy (of MIT) raise serious questions about more advanced applications of legal automation as well. The future cannot be completely anticipated in contracts, nor can difficult judgment calls be perfectly encoded into the oft-reductionist formulae of data processing. Errant divorce software may have caused thousands of errors in the UK lately, just as US software systems have disrupted or derailed proper dispositions of benefits applications.

Moreover, several types of opacity impede public understanding of algorithmic ranking and rating processes in even more familiar contexts, like credit scoring or search rankings. Consumers do not understand all the implications of the US credit scoring process, and things are about to get worse as “alternative” or “fringe” data moves into the lending mix for some startups. If the consequences of being late on a bill are not readily apparent to consumers, how can they hope to grasp new scoring systems that draw on their social media postings, location data, and hundreds of other data points? At the level of companies, many firms do not feel that Google, Facebook, and Amazon are playing a fair game in their algorithmic rankings of websites, ads, and products. These concerns, too, are stymied by widespread secrecy of both algorithms and the data fed into them.

In response, legal scholars have focused on remediable legal secrecy (curbing trade secrets and improving monitoring by watchdogs) and complexity (forbidding certain contractual arrangements when they become so complicated that regulators or citizens cannot understand their impact). I have recommended certain forms of transparency for software—for example, permitting experts to inspect code at suspect firms, and communications between managers and technical staff. The recent Volkswagen scandal served as yet another confirmation of the need for regulators to understand code.

But there is a larger lesson in these failures of algorithmic ordering. Rather than trying to replace the professions with robots and software, we should instead ask how professional expertise can better guide the implementation of algorithmic decision-making procedures. Ideally, doctors using software in medical settings should be able to inspect the inputs (data) that go into them, restrict the contexts in which they are used, and demand outputs that avoid disparate impacts. The same goes for attorneys, and other professionals now deploying algorithmic arrangements of information. We will be looking at “The Promise and Limits of Algorithmic Accountability in the Professions” at Yale Law School this Spring, and welcome further interventions to clarify the complementarity between professional and computational expertise.

This post was originally published on the website of Nesta.

Photo courtesy We Robot 2015.

UPDATED 4 Mar: We’re sad to report that Professor Tony Dyson, who built the original Star Wars R2-D2 droid, has died. We’re reposting this excellent video of his keynote at WeRobot to highlight his contribution to the field of robotics and culture.

Such a developer should:

1) Detail the specific changes to existing law, if any, that the developer needs in order to deploy its system in each jurisdiction of interest. Serious developers should already be conducting legal research and development commensurate with their technical research and development; sharing their legal conclusions (rather than merely making generalized statements about the need for uniformity or clarity) will complement the comprehensive legal audits that I have urged governments to conduct.

2) Make what I call a “public safety case” that candidly explains how the developer (a) defines reasonable safety, (b) will satisfy itself that its sytem is reasonably safe, and (c) will continue to do so over the lifetime of the system. This public safety case will be crucial to appropriately managing public expectations in both directions, to easing the concerns of regulators who are understandably wary about asserting the safety of novel systems, and to establishing norms against which amateur efforts at automation might be measured.

In many cases, an automated system may not be mature enough for its developer to understand the specific legal implications or to articulate a specific safety philosophy. If so, that is also a valuable message. As automated systems become more visible on public roads (and in public airspace), their developers should step more fully into the broader public sphere.

In this video lecture, IEEE Fellow Raja Chatila shares his views on why roboticists are duty-bound to educate the wider public on the state of advanced robotics , and also to understand the consequences of their own research and the potential commercialisation of it. 

Looking a specific examples of robots that have either already been or will soon be commercialized — including drones, UGVs in defence and security, robotic devices for rehabilitation and human augmentation, robot companions, robot personal assistants robots, sexual robots, and autonomous cars — Chatila explores the ethical, legal and societal issues of autonomous robot decisions, accountability, privacy and intrusion, dependance and isolation, cognitive and affective bonds, and the status of the robot in human society.

Credits: Institut des Systèmes Intelligents et de Robotique

IEEE Fellow Raja Chatila is Director of Research at the French National Center of Scientific Research (CNRS) and Director of the Institute of Intelligent Systems and Robotics (ISIR) at Pierre and Marie Curie University in Paris.

His research covers robot navigation and SLAM, motion planning and control, cognitive and control architectures, human-robot interaction, and robot learning. He works on robotics projects in the areas of service, field, aerial and space robotics. He is author of over 140 international publications on these topics.

Chatila R. IJARS Video Series: On the Ethics of Research in Robotics [online video]. International Journal of Advanced Robotic Systems, 2015, 12:V9. DOI: 10.5772/61995

Robotic weapons, whether autonomous or remote controlled, have generated widespread controversy in recent years.

Alex Leveringhaus, James Martin Fellow, Oxford Institute for Ethics, Law and Armed Conflict, discusses the ethics of autonomous weapons, and in a recent policy paper titled Robo-Wars: The Regulation of Robotic Weapons, urges governments to recognise the increasing prominence of these weapons in contemporary and future forms of warfare and proposes steps towards suitable regulation.

What is an autonomous weapon?

Can the use of autonomous weapons ever be ethically sound?

Download the paper

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

• RoboLaw: Why and how to regulate robotics
• A call for debate on robot policy
• US DoD report: Preparing for war in the robotic age
• Hot topic: Regulating robotics

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

Japan has the world’s largest population of at-work robots. But that prominence is threatened from recent coordinated efforts in the US, Germany, South Korea and China. Thus the emphasis by Prime Minister Abe to “make robots a key pillar of our growth strategy… to make Japan competitive again.”

Deregulation and strategic funding are at the heart of Japan’s and Abe’s 5-year growth plan and their New Energy and Industrial Technology Development Organization (NEDO).

In one example described on CNBC, the team testing a brain surgery robot, had to shut down because of over regulation. They watched as the da Vinci surgical system became a commercial success while their and other Japanese prototypes languished in laboratories.

But now the new NEDO has recruited Kawasaki and Panasonic to make a rival to the da Vinci that could perform more intricate tasks including brain surgery. The new surgical robot thrust is a $42 million part of the overall $138 million framework. Part of that framework is regulatory reforms so that new robotic surgical devices will have an easier time with regulators and meet their goal of having rival products in clinical trials by 2019.

The Japanese government estimates the market for care service robots will reach $3.7 billion by 2035 from just $155 million today, and is encouraging products from Japanese companies to service those needs. They have also issued the world’s first safety standard for personal care robots to aid large corporations in their pursuit of the care marketplace. Panasonic, Yaskawa, Toyota, Cyberdyne and other Japanese companies have all announced care product plans over the next few years.

• Panasonic has begun selling a robotic bed that converts into a wheelchair and will also begin to sell a robot to assist the elderly with walking;
• Yaskawa will start selling a device to transport a bed-ridden person from the bed to a wheelchair and a robotic device for leg rehabilitation;
• Toyota will start leasing rehab robots for mobility-disabled patients;
• Cyberdyne’s HAL exoskeleton suit received approval from the new safety board earlier this year.

Other countries are also pushing robotics to the forefront of industrial policy: China, where sales grew 32-fold over the last decade to eclipse Japan as the biggest robot market in 2013, aims to make one-third of its own robots by 2015.

South Korea has a five-year plan to spend $500 million a year on its robotics industry, while the European Union has earmarked $125 million a year to its Horizon 2020 program that aims to pull in a further 2 billion euros in private funding.

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

• Japan holds first “robotics revolution” council meeting
• Why is Japan the first to get Dyson’s new 360 Eye?
• Micro-robotics and medicine: Interview with Toshio Fukuda
• Japanese Team Schaft Gets Highest DRC Score

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

October 14, 2014 12:00PM EST Featuring Randal O’Toole, Senior Fellow, Cato Institute; Marc Scribner, Research Fellow, Competitive Enterprise Institute; and Adam Thierer, Senior Research Fellow, Mercatus Center; moderated by Matthew Feeney, Policy Analyst, Cato Institute.

On June 10th, the FAA issued a press release announcing their approval of the first commercial UAS flight over land. According to Transportation Secretary Anthony Foxx, this represented an “important step toward broader commercial use of unmanned aircraft” in the US. What do experts inside the drone community think of this development? 

Earlier this month, the FAA issued what is known as a certificate of authentication (COA) to oil giant BP and UAS manufacturer AeroVironment to fly a Puma AE for the purpose of aerial surveying in Alaska. It was the first time the FAA has authorized a commercial UAS operation over land, possibly signalling to the drone industry that there may be movement before the 2015 deadline the FAA has been given to publish regulations for commercial drone use. For years the American drone industry has been frustrated at the FAA’s slow action on creating a framework for the legal commercial operation of drones in US airspace, while commercial drone businesses take off in other countries where such frameworks already exist.

The first to note is that this is not the first US commercial license approval – only the first one over land. The FAA has previously granted licence to Puma and Insitu’s Scan Eagle to operate over Arctic waters, and the recent announcement cites the Puma’s safety record in overseas operations as a factor in their authorization of the COA. Also important is that the recent certification was propped up by Puma’s long military history.

But Patrick Egan of sUAS news argues that drone operation in combat zones is not the same as operating drones within US territory:

Patrick Egan, sUAS News

Overlaying the military model onto the civilian use of drones is a mistake … The Puma has lots of hours in Afghanistan, and it’s hard for Mom-and-Pop businesses to emulate that. It’s an unfair economic advantage.

So what hope should smaller businesses have that commercial airspace will open up for drones in the near future? Chad Partridge of 2d3 Sensing, a leader in motion imagery and computer vision software across unmanned system markets, says:

Chad Partridge, 2d3 Sensing

Under the Freedom of Information Act, the FAA has on multiple occasions released to the public the COAs they have issued. But I would be more curious as to who they have denied, specifically those relating to commercial UAS operations. The perception is that commercial UAS applications have been denied, but to what extent are commercial businesses even requesting COAs? Has the perception been that they shouldn’t even try? Hopefully this commercial COA issuance provides precedence signaling businesses of all sizes to engage in the COA process. The hope is that we will see a steady stream of commercial COA issuances from this point forward at least until more UAS friendly rule making emerges.

The fact that oil giant BP is the lead recipient of this first commercial COA underpins Partridge’s argument. When asked if it is lobbying efforts by big industries that will most likely pave the way for increased commercial drone use, Egan agrees:

Patrick Egan, sUAS News

It’s no coincidence that BP is behind the announcement. The oil and gas industry have tons of lobbying power. I think we’re also going to see some action in the film industry because they have lots of money, lots of lobbying power and lots of friends in high places. That helps.

From the beginning, the FAA has stated that safety and security have been the prime factors both in considering specific COAs and in developing the general framework for the new regulations: no one wants to see drones colliding with other aircraft or with people on the ground. This cautious approach is indeed in keeping with their decision to issue BP’s COA: the application was for flight over a relatively unpopulated area of Alaska.

Chad Partridge, 2d3 Sensing

The recent announcement signifies progress, but I have tempered enthusiasm considering the result is delivery of a single COA in a low risk environment. Yes, this COA is for the first commercial UAS operation over land, and that is great, but most of us in the UAS community would have liked a few of these COAs to already be in effect for similar operations within relatively innocuous use cases.

Patrick Egan, sUAS News

The FAA says there is a big safety concern, but statistically that hasn’t really materialized yet. UAS’ are not taking down aircraft or crashing and hurting people, and we know now that there are hundreds of thousands (if not millions) of these remotely piloted aircraft out there. Yet things could be even safer, and a standard list of common sense guidelines would make it safer for everyone … you don’t fly over people, you have to have liability insurance, you have to take a 25-question online test so that at least you know basic rules – it’s not rocket science, and most people want to operate within the law. We’ve been working on a program like this since 2007 but no one has had the political will to embrace it. The FAA needs to take a fresh look at this, or this “yet” will become an increasingly distinct possibility.

Is the US losing market share because it’s dragging its heals?

Patrick Egan, sUAS News

There are more than 1100 commercially certified operators in Europe, and there are more than 14K commercially certified operators in Japan. There are three here in the US … Absolutely, we are losing market share, and we are losing in terms of technological advancement. But unmanned aircraft are not a disruptive technology all on their own. What they really offer is self-guided data collection at an affordable price point. The real advantage of this technology is the mushrooming effect it can have on ancillary businesses. Cartographers, the GIS industry, farmers, oil and gas – the efficiency that commercial drone operation can afford all of these industries is really where the promise is. Drone inspection, for example, can be done [at a fraction of the cost of manual inspection] in many industries. So the real loss comes from the fact that ancillary businesses are not benefiting from this technology, and the efficiencies aren’t trickling down to consumers. The potential is for this to grow into an economic engine.

So, what’s the final on word on the importance of the FAA’s first commercial license approval?

Chad Partridge, 2d3 Sensing

A step forward? Yes, but we are hopeful for more.

Patrick Egan, sUAS News

It’s a good start but we need more action.

The Federal Aviation Administration’s rules on civilian use are currently on hold by a federal court, and in the interim, companies are scrambling to take advantage of using drones to deliver product.

Shipping by drone: Not a new idea

Sending packages through the air isn’t a novel strategy; it can be traced back to supply planes making airdrops of food and supplies to troops in WWII. But companies throughout the world have discovered that unless it’s a large package like a television or a computer, drones are capable of handling most product delivery.

Amazon’s Jeff Bezos estimated that using drones to deliver small items could handle 86 percent of Amazon’s shipping.

 Although Amazon has received the most press about their possible use of drones, the practice has already been going on in other countries. In southern China, a company called SF Express began using drones early in 2013; DHL, Europe’s largest parcel delivery service, has been flight-testing drones since 2013; and Domino’s Pizza in the UK is also testing drones for pizza delivery. But there are some challenges to using drones outside of the battlefield.

Government regulation may clip drone movement’s wings

In 2011, Raphael Pirker used a small drone with a foam wing weighing less than five pounds to shoot a promotional video over the University of Virginia. He flew under bridges, near statues and over pedestrians; this drew the attention of the FAA, which considered his conduct reckless and fined him $10,000. Pirker challenged the fine in federal court, saying that the agency was holding him to the same standards as airline pilots; the FAA responded by saying the agency has jurisdiction over anything flying in American airspace, whether manned or unmanned.

The judge disagreed and ruled against the agency, saying it had no rules in place for dealing with small unmanned aircraft when they fined Pirker. In his decision, he wrote that if he accepted the FAA’s argument, “a flight in the air of a paper aircraft, or a toy balsa wood glider, could subject the operator to” FAA procedures and fines. The FAA filed an appeal, leaving drone regulation in legal limbo.

What companies are doing while the FAA ruling is under appeal

Drones can pinpoint security risks, check for thermal signatures in flaming buildings, and now deliver your prescriptions to your door—although not quite to your hand just yet. While the FAA has been trying to regulate drone flights, many uses have already been found for them – and drone deliver is the latest trend.

Las Vegas’ Marquee Dayclub will provide bottle service by drone to customers who spend at least $20,000 on liquor. Amazon is implementing its own drone program known as Prime Air to get packages to customers in 30 minutes or less – but they are waiting for the regulations before proceeding too far. Currently the FAA projects their new regulations to be published in 2015.

But other companies are getting started as well. QuiQui (pronounced “Quicky”), a small startup in San Francisco, is planning to use drones to make pharmacy deliveries at a charge of $1.00 per delivery. The company chose pharmacy items because they are usually very small and easy to transport. “We’ve been working on the technology and execution for about 2 years in hopes that the FAA would come up with commercial drone guidelines,” says Qui-Qui on their website. “We didn’t expect the FAA to lose their lawsuit.”

Other inventors are looking to supply drones; a partnership between the University of Cincinnati and Amp Electric Vehicles has developed the HorseFly, which has eight rotors instead of four – making it not only better for carrying more items, but safer to fly in case one rotor goes out.

The future of commercial drone delivery service rests on the FAA: although they have established some test sites, businesses will likely not get clarity on the legality of commercial drone use until 2015 when the new rules come out. We may have to wait until then see drones moving freely throughout the skies.

We are moving closer to having driverless cars on roads everywhere, and naturally, people are starting to wonder what kinds of ethical challenges driverless cars will pose. One of those challenges is choosing how a driverless car should react when faced with an unavoidable crash scenario. Indeed, that topic has been featured in many of the major media outlets of late. Surprisingly little debate, however, has addressed who should decide how a driverless car should react in those scenarios. This who question is of critical importance if we are to design cars that are trustworthy and ethical.

Driverless cars stand to reduce the number of driving fatalities overall. But there will still be fatal car crashes that are unavoidable. For example, consider this scenario in illustration, a sort of modified trolley problem (the name given by philosophers to classic examples of unavoidable crash scenarios, historically involving runaway trolleys and innocent bystanders), which I will call the tunnel problem.

Tunnel Problem: You are travelling along a single lane mountain road in an autonomous car that is fast approaching a narrow tunnel. 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 but two options: hit and kill the child, or swerve into the wall on either side of the tunnel, thus killing you. How should the car react?

Hypothetical scenarios like this one, borrowed from philosophical ethics, force us to accept the fact that some situations have only unfortunate outcomes, and focus our attention instead on the ethical complexities involved in deciding which unfortunate outcome to prefer. In these scenarios, sorting out the who question is as ethically important as sorting out the how.

If you were faced with the Tunnel Problem, what would you decide?

Take our reader poll.

In the tunnel problem, both outcomes will certainly result in harm — someone will surely die. But more importantly, from an ethical perspective there is no obvious “correct” answer to these kind of dilemmas. Tunnel problems are used as thought experiments in philosophy precisely because they are so difficult to answer, and they are popular among students for the conversations they spark at the pub.

But while philosophers in the past could ponder these kinds of difficult ethical dilemmas in the lecture hall, far removed from any practical application, when we bring autonomous cars onto the scene, these philosophical thought experiments suddenly acquire practical urgency. The tunnel problem, and trolley problems like it, point to imminent design challenges that must be addressed. From a design perspective, the tunnel problem raises the following question: How should we program autonomous cars to react in difficult ethical situations?

But there is another, related, ethical question inextricably linked to this first one: Who should decide how the car reacts in difficult ethical situations? This second question asks us to turn our attention to the users, designers, and policymakers surrounding autonomous cars, and consider who has legitimate moral authority to make decisions. We need to consider these questions together if our goal is to produce legitimate answers to either.

At first glance this second question — the who question — seems odd. Surely it is the designers’ job to program the car to react this way or that? I’d like to convince you otherwise.

I believe that in many driving situations, tunnel problems for example, it is ethically problematic to allow designers to decide how an autonomous car should react. In a draft paper I recently presented at We Robot – a conference focused on the legal, ethical, and policy issues surrounding robotics – I consider the who question in some detail. I argue that instead of assuming designers are the right people to decide in all circumstances how a driverless car should react, that we must explore design methodologies that in many circumstances allow individual drivers to decide on the preferred unfortunate outcome. My reasons stem from the nature of tunnel-like problems, and the relationship that exists between designers, drivers, and technology.

From a driver’s perspective, the Tunnel Problem is much more than a complex design issue. It is effectively an end-of-life decision. Even if we modify the problem so that serious injury is the likely outcome, Tunnel Problems pose deeply moral questions that implicate the driver directly. Seen this way, the tunnel problem is a deeply personal moral problem for the driver who happens to be in the car at that moment.

Allowing designers to pick the outcome of tunnel-like problems treats those dilemmas as if they have a “right” answer that can be selected and applied in all similar situations. In reality they do not. Is it best for the car to always hit the child? Is it best for the car always to sacrifice the driver? If we focus on designers, the tunnel problem appears to pose an impossible design problem, one that can only be solved arbitrarily.

But there is a better solution. We can look to other examples of complex moral decision making for examples of how to get some traction on the who question.

In healthcare we deal with deeply personal moral problems, such as end-of-life decisions, on a daily basis. We are so accustomed to them, in fact, that we have found ways of answering the similar who question in healthcare with some success. In medical ethics there is general agreement that it is impermissible to impose answers to deeply personal moral questions upon others, except in very special circumstances. In other words, it is generally left up to the individual for whom the question has direct moral implications to decide which outcome is preferable. When faced with a diagnosis of cancer, for example, it is up to the patient to decide whether or not to undergo chemotherapy. When faced with imminent death, it is up to the dying patient to decide if they would like CPR in the event of cardiac arrest. Doctors and nurses are trained to respect patients’ decisions, and to work around them within reason.

In healthcare, the notion of imposing medical interventions upon individuals without their express consent is so contentious that it is given a special name: paternalism. Subjecting someone to paternalism in the medical context is considered unethical, because it robs them of their personal autonomy.

An appeal to personal autonomy has intuitive appeal beyond healthcare. Why would one agree to let someone else decide on deeply personal moral questions, such as end-of-life decisions in a driving situation, that one feels capable of deciding autonomously? Why should we allow designers to decide on the outcome of tunnel problems if there is a way for individual drivers to do so autonomously?

From an ethical perspective there is nothing exceptional about the tunnel problem that suggests we should allow designers to impose an answer to that deeply personal moral question upon drivers. If we allow designers to choose how a car should react to a tunnel problem, we risk subjecting drivers to paternalism by design: cars will not respect drivers’ autonomous preferences in those situations.

What would personal autonomy look like in the context of a tunnel problem? For starters, as in healthcare we should expect drivers’ preferences to demonstrate their personal moral commitments. It could be that a very old driver would always choose to sacrifice herself to save a child. It might be that a deeply committed animal lover might opt for the wall even if it were a deer in his car’s path. It might turn out that most of us would choose not to swerve. These are all reasonable choices when faced with impossible situations. Whatever the outcome, it is in the choosing that we maintain our personal autonomy.

The upshot of considering the second question — Who should decide how the car reacts in difficult ethical situations? — is that it becomes clear that there are certain deeply personal moral questions that will arise with autonomous cars that ought to be answered by drivers. Just because designers hold the technical abilities to engineer autonomous cars does not give them the authority to impose particular moral decisions on all users. If designers assume moral authority, and subject users to paternalistic relationships, they run the risk of making technology that is less ethical, and certainly less trustworthy.

Of course, recognizing the ethical need for user input in some situations should not lead to designer paralysis. Technical and practical limitations will sometimes prevent designers from making autonomous cars that ask users to make explicit choices in all unavoidable crash scenarios. Yes, we must recognize the importance of letting drivers autonomously express certain preferences. But we must also balance the need for personal autonomy with the severity of the ethical problem posed by the design decision. Asking for driver input in all scenarios would create unreasonable barriers to design and would prevent society from realizing the many other benefits posed by the technology, such as a reduction in overall crashes. Some driver preferences will not be “serious” enough to warrant their input.

The same is true in healthcare, where sometimes consent can be assumed. Healthcare professionals are obligated to get consent from patients only in cases that warrant that consent. A proportional approach is applied to make the determination. The challenge for autonomous car designers is adopting a design methodology that allows for the identification of paternalistic design choices, and then applies a proportional assessment to determine which of those choices requires user input. Thus, just as we have proportional assessment models in healthcare, we can work to develop similar approaches when designing autonomous car technology.

None of this simplifies the design of autonomous cars. Indeed, there are significant design barriers associated with ethical issues that will need to be overcome before autonomous cars ever enter the general market. But making technology work well requires that we move beyond technical considerations in design to make it both trustworthy and ethically sound. We should work toward design methodologies that are capable of identifying paternalism, and that ultimately enable users to exercise their more of their autonomy when using technology. When robot cars must kill, there are good reasons why designers should not be the ones picking victims.

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

• 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.

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”).

Amidst a climate of fiscal austerity and vibrant debates over the growing importance of unmanned vehicles in foreign policy and homeland security, the 2013 AUVSI Unmanned Systems Conference returned to Washington, D.C., last week after hosting the 2012 event in Las Vegas. The event was not without controversy, however, as activist group Code Pink held a demonstration outside the venue and disrupted a keynote address. The show itself was a tale of two storylines as the exhibit hall demonstrated that applications for defense and law enforcement are still the lifeblood of the unmanned systems industry, while the technical program and panel discussions pointed to a growing interest to move into commercial industries. Here’s what you missed:

UAVs as economic drivers

As expected, the Federal government’s booth presence was minimal among the nearly 600 exhibitors compared to previous years due to limited budgets. Interestingly, several states including Ohio, Minnesota, Nevada, North Dakota, Utah, Oklahoma, New Mexico, and Arizona were present to promote their economic programs and bids as one of six test sites under the FAA’s UAS integration program. Approved sites will attract unmanned aerial vehicle manufacturers as the FAA begins to open U.S. airspace in 2015. North Dakota Lieutenant Governor Drew Wrigley and U.S. Congressman Mike Turner (R-Ohio) made special visits to the conference to further promote their respective states. States will become increasingly important for manufacturers as Defense procurements slow and commercial markets are opened.

Big and small vendors showcase new platforms

Among exhibitors, the vast majority of platforms continue to be fixed-wing aerial vehicles of various sizes. The big players of General Dynamics, Lockheed Martin, and Northrop Grumman showed the latest in drone technology, including a model of Northrop’s X-47B, which just this past July achieved a historic result by autonomously landing on the flight deck of the USS George H.W. Bush. Several quadrotor vendors were also present to market easy-to-use and agile systems for law enforcement. I was particularly impressed by systems from Aeryon Labs and navigation systems from Airware. While last year we were introduced to the unique ground platforms from Boston Dynamics such as the LS3 and RHex, no particular system stole the show this year. It was nice to see iRobot’s RP-VITA out and about with live telepresence demonstrations, however. Among maritime systems, California-based Liquid Robotics brought along “Benjamin Franklin,” recently returned from a Guinness World Record-setting 14,703 km data collection journey across the Pacific Ocean.

Self-driving cars, the future?

But it was the push toward applications in agriculture and self-driving cars that attracted the most attention and excitement among technical program attendees. The automated driving panel featured a lively discussion from panelists Chuck Thorpe, Clarkson University Provost and former Carnegie-Mellon University Robotics Institute head; Virginia Tech researcher Myra Blanco, and consultant Annie Lien. Chief among the discussion topics was the role of states in regulating self-driving cars. While California, Nevada, and others are helping get these vehicles onto roads, this approach will hinder progress and development, according to Ms. Lien. “Safety requirements are normally defined at the federal level,” she noted. Different regulations for each state will eventually create a logistical and legal headache for manufacturers and consumers alike.

Though Google and car manufacturers are making significant progress in developing and testing the necessary technologies for fully autonomous systems, the panelists noted that they are taking very different approaches toward market introductions. Among the four defined levels of autonomous cars, with level 0 being manual and level 4 being full autonomy in unstructured road conditions, panelists suggested Google is aiming directly for level 4 within five years while BMW, Mercedes and others are gradually introducing new features in time-tested industry fashion. For example, some 2014 year models will feature traffic jam assistance that will facilitate self-driving with minimal intervention in stop-and-go situations.

So where will we be by 2020? The panelists seemed to converge on the certainty of level 3 market availability, but with complex socio-technical systems such as transportation, that is still anyone’s guess. Thorpe summed it up fairly well by suggesting it is always more difficult to transform an existing industry than creating a new one. Aside from the technology and safety regulations, we are only now considering the larger societal questions such as urban sprawl: if you could work or sleep while the car autonomously drove during your commute, would you live farther away?

Corporations are more disciplined and less prevailed upon by conflicting interests than governments; hence long-term planning is a regular part of their management practice. But corporations have neither ethics nor loyalties, and often do marginally (if not outright) immoral things to preserve the profitability of the company over the welfare of the community and workforce.

Entrepreneurial solutions from business start-ups are a whole different category. They don’t necessarily solve anything that needs long-term solving, and they don’t really have a long-term business plan. They address a current whim, need or solution that the inventors feel strongly about. And they make it or fail based on their energy and ability to sell their new product. Only after they are established does long-term thinking kick in, so that the new company can develop new products and services.

Thus, if we are going to answer a question about policy, it’s really governments that we should be looking at. So let’s look at how policy is supposed to work in the US, why it might be failing us, and how taking the long view can help.

How the policy process is supposed to work in the US
The Executive Branch of the Whitehouse is supposed to analyze the future and past with an eye toward meeting and setting strategic goals including those defined in the US charter (its Constitution). They bring in the best minds to discuss problems and their solutions — sometimes behind closed doors and other times publicly. They also study trends and change to see what the future has in store for us. This is where the process of strategic planning — a process whereby goals and objectives are balanced against resources and alternative possibilities for the use of those resources — is supposed to take place.

In compliance with the intent of the Constitution, which provides the moral and ethical parameters to guide the process, the three most prominent objectives of this strategic planning are to provide continued infrastructure, healthcare and security. This planning often gets very specific, as can be seen in many of the DARPA projects: ARPANET, which turned into the Internet; Transit, which became our current GPS system; handheld language translation devices presently used in Iraq and Afghanistan; Stealth planes; Semiconductor gallium arsenide; Robot cars via Grand Challenge competitions; Bionic limbs; and the list goes on and on. DARPA is just one agency that solicits scientific solutions for various aims: NSF, NASA, NIH, USDA are four other prominent translators of Presidential goals into reality.

Sometimes strategic planning is more generalized, as was the recent recognition that the process of offshoring manufacturing to lower-cost-labor countries had serious unintended consequences to America, and that the process should be stopped or seriously changed — this realization prompted the Advanced Manufacturing Initiative, which included a section for robotics development. As the Manufacturing Initiatives were being discussed, there was a timely submission of the presentation to Congress of the US Roadmap for Robotics (which was partially funded by government grants).

As the Robotics Initiative was incorporated into the Manufacturing Initiative, additional unintended consequences could be seen: the need for more technically skilled labor and the reduction of the lower-skilled workforce. Most often, strategic planning is reactive rather than long-term. Consequently, as resources are allocated to these reactive issues, long-term planning suffers and serious issues get put off.

Annually the President presents the results of those analyses and makes a case for the goals he chooses in a state-of-the-union and budget presentation to the Congress and the public. Congress then figures out how or whether the goals and services that the President outlined represent the will of the people, and whether the budget he proposed meets the needs of the existent government plus the new goals/services. They break down the President’s proposals into small tasks and send them to committees that specialize in those tasks. These committees have staff that are schooled in the subjects of the tasks, and these staff members often supplement their own analyses by consulting with outside organizations that represent the various interests and stakeholders involved.

The committees discuss, negotiate, and evaluate the merit of the goals the President has proposed. Then, when they agree to agree, they write laws and regulations that define those goals and present these to the whole of Congress, along with summaries, so that Congress members can evaluate and then pass those new laws and regulations task by task.

Finally, the Judicial System is there to adjudicate how people and companies interpret and comply with those laws.

Thus there are at least three levels where knowledgeable people influence the outcome of the strategic planning and legislative process: at the Presidential fact-finding level; within congressional committees and in the Congress and Senate itself; and at the judicial level.

Infiltrating technology whiz-kids into these positions isn’t enough of a solution; there’s more to the debate than just knowledge of the technology. There are also the ethical considerations, possible long-term consequences and alternative solutions to consider. Hence the need for wise leaders to pick balanced teams of advisors who can collectively cover all aspects of the strategic issues.

Those people who are appointed to presidential advisory, or “thought” positions need to be the nation’s brightest, and most knowledgeable and altruistic — for example, the President’s Council of Advisors on Science and Technology headed by Dr. John Holder and the other staff members of the Whitehouse Office of Science and Technology Policy, all of whom are competent selections. Congressional committee selections need to combine the most knowledgeable (and not just the most senior or junior) of the membership; Congress itself needs to have a balance of technology executives amongst its membership (fewer lawyers); and committees’ permanent staff needs to be selected for their technological prowess (not on seniority), and should be regularly vetted for any improprieties between them and lobbyists and special interest groups.

Assuming that most policy-makers start their policy-making careers with the intention of representing the best interests of their respective constituencies (and the country as a whole) by finding the least costly solutions to our problems, how come they don’t do just that?

Why the policy process might be failing us
The short answer is constant scrutiny, instant pressure from media and others, divided loyalties, and inadequate (and sometimes compromised) staff, all of which lead to selfish and protective thinking. The long answer is more thought-provoking.

Ian Goldin, Director of the Oxford Martin School offers some interesting solutions and solution methods. Goldin, a former VP of the World Bank, addresses the why, the how and the what-to-do about it in his new book: Divided Nations: Why global governance is failing, and what we can do about it. He writes:

Globalization increasingly presents a paradox: it has been the most progressive force in history, but the most severe crises of the 21st century will arise due to the very success of globalization. Unless we are able to manage these threats, there is a real danger that globalization will have given birth to its own downfall.

In the two decades since the fall of the Berlin Wall, fundamental political, economic, and technological changes have led to a step-change in global connectivity. Interdependence and innovation have brought unprecedented benefits, and led to the most rapid global rise in incomes and health in history. However, the same processes of integration and innovation have also greatly increased the potential for systemic risk and global crises. Globalization is leaping ahead of the lethargic institutions of global governance.

The number of countries involved in negotiations (close to 200 now) and the complexity of the issues and their interconnectedness have grown rapidly, as has the effect of instant media and other pressures on politicians. These and other factors have paralyzed progress, so the prospect of resolving critical global challenges appears ever more distant.

Goldin believes that the UN would have to gain power over its member nations, with nation states relinquishing much of their current powers to the UN. He further says that without at least a global calamity, this isn’t likely to happen. He thinks that humanity is in denial of the fact that only one solution can prevail: some form of binding global governance… but only for those problems needing collective international action. Alternatively, Goldin points out that much could be tackled by a smaller group of nations: “a coalition of the willing.” He writes:

“What is needed is for NGOs, corporations, professionals, legislators and their staffs, and the public, to face up to the fact that today’s problems cannot be solved by their current approaches, nor by nations acting alone, nor by keeping our heads in the sand. Like it or not, some form of binding global governance must occur.”

Taking the long view

Policy-makers need to be focused on solving long-term strategic issues for their countries and constituencies. But it’s an iffy situation. During President Bush’s term, friends were placed in key advisory roles, often with no background knowledge of the subjects upon which they were to advise. Things are better in the Obama administration. Nevertheless, it’s a lot like the dialogue we’ve had before about which comes first: the technology or the solution.

But the answer is Neither.

What comes first is the problem that needs to be solved, and the commitment to finding a solution. That’s where and when positive things happen. If there’s no advice, long-term problems go unaddressed. China’s communist government has a long-term point of view and the discipline to make their strategic goals happen; few other countries have that power.

It’s not enough to place technology-friendly people in key advisory rolls. Nor is it enough to invest in science. Or efficiently lobby all the key players. Strategic goals need to be defined, talked about and agreed upon. Then the mechanisms of science, law, politics, business, the public, and funding can all focus on the solution.

This essay is an expansion of Frank Tobe’s response to Robotics by Invitation question “What do policy-makers need to do to keep pace with economic development in robotics?”

Read more answers →

This month we asked Robotics by Invitation panel members Rich Mahoney and Frank Tobe for their take on what policy-makers need to do to keep economic development apace with important developments in robotics. Here’s what they have to say …

Rich Mahoney on “What do policy-makers need to do to keep pace with economic development?”

I am not sure how to describe the specifics of what policy makers should do, but I think there are two gaps that policy makers should think about that are associated with the economic development impact of robotics: sufficient funding to support an emerging robotics marketplace; and  detailed descriptions of the innovations needed to solve specific problems …

Read more →

Frank Tobe on “What do policy-makers need to do to keep pace with economic development?”

I think the biggest thing happening today is the acceptance of the low-cost Baxter and Universal robots into SMEs and small factories everywhere.  Sales will likely be 2% of the total; 5% in 2014 and possibly 15% in 2015. That’s growth! And that’s before the might of the big four robot makers start selling their low-cost entry robots for SMEs …

Read more → 

[Frank Tobe]
I think the biggest thing happening today is the acceptance of the low-cost Baxter and Universal robots into SMEs and small factories everywhere.  Sales will likely be 2% of the total; 5% in 2014, and possibly 15% in 2015. That’s growth! And that’s before the big four robot makers start selling their low-cost entry robots for SMEs. This has more near-term promise than unmanned aerial or ground vehicles in agriculture and elsewhere. These co-robots are proving that we need more high-tech people and fewer low-skilled people in this globally competitive economy.

What are the major policies that foster, steer, or hinder the robotics industry?

There are at least three levels where knowledgeable people influence the outcome of the strategic planning and legislative process: at the Presidential fact-finding level; within congressional committees and in the Congress and Senate itself; and at the judicial level. Infiltrating technology whiz-kids into these positions isn’t enough of a solution because there’s more to the debate than just knowledge of the technology. There are also the ethical considerations, possible long-term consequences and alternative solutions to consider. Hence the need for wise leaders to pick balanced teams of advisors covering all aspects of strategic issues.

Can you point out some examples of different policies in different regions/countries and their effects?

China is locking up long-term resources contracts for energy, agricultural land, shipping by sending out manpower everywhere to make it happen. Most other countries just compete on price and trade for deals.

What are the other main drivers of economic development? 

Lower costs for sensors, components and robots; global competition; demand for higher quality; new marketplaces for the DDD of robotics: food processing, agriculture, SMEs, healthcare; diminishing low-cost labor; growing population of seniors.

Do you have concrete suggestions for policy-makers?
Think long term. Include unanticipated consequences and alternatives. Cooperate with the other stakeholders to make all happy. Regarding international issues, follow the advice of Ian Goldin.

The complete answers to these questions more complex. To learn more, read Frank Tobe’s in-depth article on how policy should — and does — shape economic development.

Read more answers →

The program committee of the inaugural Drones & Aerial Robotics Conference (DARC) is now inviting proposals from individuals across a broad spectrum of expertise. DARC will convene a wide range of stakeholders to explore civilian drones and their impact on society. The conference is presented by the Engelberg Center on Innovation Law & Policy at NYU School of Law and will be held October 11-13, 2013. We invite contributions from all interested disciplines on or before May 27, 2013.

ABOUT DARC

What do hobbyists, journalists, university researchers, soldiers, and police all have in common? They’re all testing or using aerial robotics, commonly called “drones.”

Imagine a near future in which networks of autonomous robots roam the skies, performing everything from law enforcement, to communications, to crop dusting, shipping and logistics. Sound implausible? It might be. But that’s the future that the aerospace industry, the FAA, and a new class of entrepreneurs are busy preparing. And this future is closer to reality than many realize. Drones force a broad reconsideration of the laws and regulatory frameworks that protect vital interests like civil liberties, due process, privacy, innovation, and security. But they also herald new innovations and new public interest applications.

These technologies are powered by some of the same phenomena that propel the mobile industry—Moore’s law, economies of scale, and ever more sophisticated software built by large companies or open source hackers. Anyone can buy a toy drone at the mall for $299, assemble a relatively capable DIY drone for $1000, or buy a sophisticated $50,000 aircraft for amateur photogrammetry.

As the FAA scrambles to meet its 2015 integration deadline—which will open domestic airspace to hobby aircraft as well as the types of aircraft that currently fly over Afghanistan—DARC provides a forum for entrepreneurs, policy makers, and civil libertarians to constructively engage. Join us this Fall to explore this fascinating, emergent space.

PROPOSALS

There are few technologies that stimulate such deep and wide-ranging questions about law, technology, and international relations. We welcome all proposals, but please stay substantive and constructive. This list is not exhaustive, but we invite proposals along the following lines:

• Anecdotal talks
• Popular research
• Demos or tutorials
• Scholarly research
• Constructive discussions

Proposals should address — but are not limited to — our five main areas of interest:

• General Interest & Zeitgeist
• Makers & Entrepreneurs
• Law & Regulation
• Privacy & Surveillance
• Security

Proposals can be submitted via the conference website at https://droneconference.org/proposals. Proposals will be accepted until May 27, 2013. Questions may be sent to contact@droneconference.org

This post is part of Robohub’s We Robot coverage.

Woodrow Hartzog and Greg Conti presented their paper (co-authored with Lisa Shay and John Nelson of West Point) on implementing law in computer systems.

Paper: Do Robots Dream of Electric Laws? An Experiment in Law as Algorithm
Author: Greg Conti, Woodrow Hartzog
Moderator: Harry Surden

This was an especially interesting presentation, given that last year at We Robot in Miami, the same authors presented a paper on the problems of removing humans from the loop and turning law enforcement over to a computer (Confronting Automated Law Enforcement). This year, the authors took the question a step further. In an experiment, they look at what happens when you convert laws into algorithms. It turns out that even simple rules (like speeding limits) require unexpected consideration.

In the experiment, 52 programers were asked to automate the enforcement of traffic speed limits. They were given a set of driving data and each wrote a program that measured the number of speed limit violations and issued traffic tickets accordingly. Despite having exact data for both vehicle speed and speed limits, the number of issued tickets varied among the programs. The authors attribute the variance to the fact that the programers were faced with having to make assumptions and legal interpretations, for example whether to code according to the letter of the law (100% enforcement of every violation) or the intent of the law (tolerating minor infractions). The study indicates that there can be unanticipated degrees of freedom in the design of enforcement algorithms, even when dealing with seemingly straightforward legal rules.

As for the broader implications, the authors drew attention to the following problem areas:
Culpability We may not be able to automate laws that include culpability, because this is too difficult to determine automatically.
Objectivity of the wrongful conduct E.g. speed does not necessarily equal recklessness.
Identification With automated enforcement we would have to make particularly sure that someone’s identity can be verified.
Accessibility To what extent does this lead to a surveillance society? What kind of information is and should be accessible?

The results of the study also caution against outsourcing coding of the law to third-parties. They indicate that seemingly minor details can make a huge difference, creating more variance than assumed and requiring decisions by someone with actual rule-making authority. The authors also mentioned the need to consider potential second and third order effects, such as on traffic flow, etc.

Surden pointed out that there are already examples of laws being translated into computer code today that many people, including law-makers, are not fully aware of. For example, tax preparation software Turbotax inherently involves a lot of judgment and design decisions that have gone under the radar and are accepted more or less unquestioned by the Internal Revenue Service.

To my (personal, IP-nerdy) delight, an audience member mentioned the problems with content ID-ing and automatic copyright takedown notices on platforms like YouTube. Often these programs will remove completely legitimate content, causing troubles for fair-use activity. Surden said that one take-away for automated enforcement from this is that the appeal process should be just as easy as the take-down process.

The discussion also turned to the question of socially desirable enforcement. If we can embed laws in systems, we could potentially have a system of perfect monitoring and perfect enforcement. But are there costs to that perfection? Both authors argued that imperfect enforcement allows for a healthy amount of discretion and flexibility, and that bureaucracy left to its own devices could be dangerous. Even more problematic than perfect enforcement, said Hartzog, is perfect prevention. As we’ve seen with red light camera systems, citizens can become outraged by what they perceive as a lack of value judgment. A disconnect between law and social perception can go so far as to be counterproductive. Conti also postulated that the type of person who is willing to take on some risk to achieve a certain gain would be beat out by perfect law enforcement – behavior that we might want to otherwise maintain in our society.

The audience was also interested in the question whether our current system of human error, bias, and corruption in law enforcement is better or worse than a system that leaves no flexibility for human judgment. Can we build room for discretion and community norms into systems? What happens if a human bias becomes systematized? Interestingly, when the programmers were asked after the experiment whether they would want to drive on the roads with the programs they had built, their answer was uniformly “no.” (Although one programer said yes, conditioned on creating a backdoor exception for herself.)

In terms of policy recommendations and reducing the uncertainty of coding law, the authors suggested creating a committee or organization to set standards for automated enforcement systems, and also that the code of such systems be kept transparent and open to examination.

See all the We Robot coverage on Robohub →

This post is part of Robohub’s We Robot coverage.

The conference kicked off with a panel on intellectual property (IP) in the robotics industry.

Panel: Robotics and Intellectual Property
Speakers: Mark Lemley, Christian Hicks, Julie Samuels
Moderator: Brian Biddinger

The panel discussed general intellectual property issues (in particular patents and copyright) and how these could apply to emerging technologies in robotics. If you’re interested in learning a bit about the current problems with the patent and copyright system in general, this panel is worth a watch.

Regarding the robotics industry specifically, the panelists distinguished between hardware and software, and general purpose technology versus special purpose technology. They also discussed how robotic technologies may start out specialized and proprietary, but become increasingly commoditized over time – something seen previously in the computer and smartphone industries. The panelists’ advice on IP strategy (for individual companies as well as the industry in general) largely depended on the types of technology being developed.

For example, whether a company is devoting their main resources to hardware or software will determine how much of their IP life is influenced by patent or copyright law. The panel came down hard on software patents, arguing that they have done more harm than good and appealing to the robotics community to do everything possible to prevent them. Hardware patents were more difficult to dismiss, despite the danger of creating an unnecessary and suffocating patent thicket. As Samuels commented “I wish I could say ‘ignore patents!’ But they won’t ignore you.”

The panel speculated that specific purpose technology may lend itself to proprietary models, but robots that can later on be programmed by other people to do a variety of different things might be better to release as open-source. Comparing to other industries, Lemley observed that the companies that start out closed and proprietary are often first-movers, but they also often end up an edge player in the market later on. An opposite example is the Arduino model – releasing your platform as open, and focusing instead on branding. Because it’s hard to anticipate all of the things that people will want to do with the platform, it can be a successful strategy to keep it open at an early stage – so long as the brand is strong enough. (E.g. manufacturing robots and surgical arms may not necessarily be at that “early stage,” but perhaps household robots that will be able to do a variety of yet unknown things.) Hicks pointed out that interoperability may become increasingly important as robots start working together. Having a closed-off system like Apple can only work if you’re extremely and unusually successful – in any other case the better strategy for such an emerging eco-system will be open.

Hicks also spoke about his paper Robots, the DMCA, and Patents: Threats, Strategy, and Case Law in the Aftermarket, which describes how hardware manufacturers might start using the anti-circumvention provisions of the Digital Millennium Copyright Act (DMCA) to control secondary markets for service, software upgrades, etc. Based on the precedent of two court decisions, the DMCA can potentially be (ab)used to prevent customers and competitors from accessing software, and thus maintaining, upgrading, and adding functionality to robots, or even analyzing a product for patent infringement.

The panel talked about the problem of “trolls,” pointing out that over 60% of all lawsuits last year were brought by non-practicing entities (85% of these based on software patents). The panelists discussed (and disagreed about) the importance of patented technology for startups in getting VC funding. They also debated longer-term patent and copyright reform. As for the immediate future, the panel recommended that the industry 1. stay informed and share information with each other; 2. get involved and look for solutions within the current system, such as open-source software, getting behind projects like the defensive patent license, or working with agreements like Twitter’s Innovators Patent Agreement.

Other mentioned links of interest:
Lex Machina
Electronic Frontier Foundation

See all the We Robot coverage on Robohub →

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.

This post is part of Robohub’s Jobs Focus.

We’re in the midst of National Robotics Week, and roboticists all over the US are celebrating robotics research, development and education through hundreds of events and demonstrations at local libraries, universities, Block Parties and FIRST competitions. The point of National Robotics week is to celebrate, educate and inspire a new generation to pursue careers in robotics. But another key goal of the week is to advocate.

Advocating for cash is one part of the job, because R&D requires lots of it. And if you’re going to acquire cash from granting bodies or investors, you have to convince them that the work you are doing is important, that it’s going to solve a problem, and (if you’re a start-up) that it has commercial potential. And as robotic technologies move from research into commercial viability, advocating for robotics-friendly legislation becomes just as important: if laws and regulations prevent your product from reaching the market, it doesn’t matter how much cash you have.

Nymann Teknik arm, from Universal Robots.

So what does advocacy have to do with jobs? Plenty. The jobs issue is a visceral one. It hits us where it counts: how we earn, how we feed ourselves and our families, how we put a roof over our heads. It’s why employment is always a key issue in election politics – it’s a topic that impacts almost every voter of working age. ‘Robots and jobs’ has become a contentious issue that, like it or not, will determine the success or failure of many new robotics technologies, so it’s no great surprise that there are plenty of people who have something to say about it.

Here are the main points of view that have been entrenched and promoted:

1. Robot replace human workers, and that is a bad thing; they are a ‘disruptive force’ that will cause irrevocable harm to our entire socioeconomic system. See 60 Minutes’ Are robots hurting job growth? and CNN World’s The jobless economy, and the Economists’ Robots don’t complain or die.
2. Robots replace human workers, and that is a good thing; they will take over dull, dirty and dangerous jobs and leave us humans with more time to do interesting/productive work. See Andrew McAfee’s TED Talk, and Wired’s Better than human: Why robots will – and must – take our jobs.
3. Robots don’t steal jobs, they create them; whether through ‘re-shoring’ or through the emergence of new robotics industries, there is tremendous job growth potential for economies that support robotic technologies. See Time’s Can robots bring back manufacturing jobs to the US? and Kuka’s infographic Robots and automation bring jobs back to the US.

To help us tease out the issues we are featuring a week’s worth of coverage on the topic from top experts in the field, including fact finding, analysis and opinion. Here’s a quick teaser of what to expect over the next week or so …

A look at the numbers:

• Frank Tobe gives us a critical walk-through of IFR’s latest Metra Martech report.
• Armed with data from the recently released Economic Impact of Unmanned Aircraft Systems Integration in the US,  Chris Mailey from AUVSI suggests that a multibillion dollar market will quickly emerge to create over 100,000 jobs in the US by 2025 once current FAA restrictions to unmanned aerial systems are lifted, as they are schedule to do in 2015.
• Plus, a fact-finding post with all the latest economic reports on the robotics industry.

A look at influencing factors:

• John Dulchinos, Executive Board Member of the International Federation of Robotics, takes us through some of the latest jobs stats and suggest that robotics is eliminating the advantage and influence that low-cost labour has had on manufacturing.
• Rich Mahoney, Director of Robotics at SRI, says that it’s too early to make any grand predictions about how robots will affect the jobs economy in the future, but that the success of robotics companies’ management teams will surely play a critical role.
• In response to the Robotics by Invitation question “Do robots kill jobs?“, Raffaello D’Andrea, co-founder of Kiva Systems, talks about how low interest rates are fuelling the jobs debate; and Mark Tilden argues that robots are just scapegoats, and that corporate ethics are to be blamed for poor employment numbers.
• Regular Robohub contributor and agribot expert John Payne echoes the many voices in the agricultural sector, which point out that agricultural robots will be replacing job vacancies, not people.

Outlook:

• Martin Ford, author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future argues that as robots and other forms of automation progress, machines will take over an ever-increasing fraction of those routine jobs and significant unemployment will become inevitable.
• Federico Pistono, author of “Robots Will Steal Your Job, But That’s OK: How to Survive the Economic Collapse and Be Happy” suggests that technological unemployment is already a reality today and argues that we should use this opportunity to rethink what the purpose of society should be.
• Matt Beane, from MIT’s Sloan School of Management asks if we are on the cusp of a robotics revolution or whether robots are distracting us from the forces profoundly affecting our economy. Matt Beane’s short answer: yes.

And don’t forget:

• Coverage of this week’s Silicon Valley Robot Block Party and Xconomy Forum: Robots Remake the Workplace by Robohub correspondents Frank Tobe and Andra Keay.
• Live streaming of Stanford’s We Robot conference on robotics and the law.
• Sabine Hauert‘s report on Jobs for Roboticists.
• Frank Tobe’s post from January 2013 on how the definition of robots affects how they are perceived in the jobs debate
• And on a lighter note, Jim Haas‘ Nate the Robot – the Dilbert of robotics. Look for Nate in the sidebar!

Managing the ‘issue’ of robots and jobs is important to the success of businesses, research institutions and politicians alike, whether they are ‘for’ robots or ‘against’, so there is no doubt that you will continue to see headlines about robots and jobs for the foreseeable future, both in the mainstream media and here on Robohub. We hope you enjoy this focus series … feedback is welcome, so send us your comments!

See all the posts in Robohub’s Jobs Focus.

This post is part of Robohub’s Jobs Focus.

Bottom line, a multibillion commercial market will quickly emerge in the United States with applications ranging from precision agriculture to precision medicine delivery, creating over 100,000 jobs by 2025 just in manufacturing of these new products.

Why UAS?
In the most basic sense, UAS allow for similar capabilities of manned aircraft except without the added weight and size of the pilot and related pilot protection equipment. Once that weight and space (up to several hundred pounds) is stripped, suddenly the platform can be operated in new safer, more accurate ways. For hobbyists, these vehicles are an end unto themselves. For commercial use the vehicles must justify their use through making existing operations cheaper, more effective or less risky. In the report, we focused on markets that have existing data (agriculture and public safety) and made our projections from this data. However, when it comes to new applications, soon the sky will no longer be the limit.

Legislative Barriers
Though the FAA will find safe, effective ways to integrate UAS in the nation’s airspace, lifting what is the only current hurdle to mass commercial adoption, new legislation is under development that will may hinder commercial adoption of UAS. Michael Toscano, President and CEO of AUVSI, recently testified before the US Senate on the matter. Looking purely at the economic implications, states or municipalities that limit UAS use will miss out on the benefits of such systems and will likely quickly change their ways after other states prove the potential of UAS and alleviate current concerns. However, it may be too late for states that adapt slowly, as companies will likely already be established in states without excess restrictions.

Get Ready
Once current FAA restrictions are safely lifted, expect companies to move quickly to capture a piece of the multibillion dollar market. We’re two and half years away and companies in the defense market are already developing new commercial vehicles and new companies are springing up, cutting their teeth in other countries waiting for the right time to enter the U.S. market. These are exciting times and I cannot wait until I don’t have to leave my doorstep to catch a piece of the action.

See all the posts in Robohub’s Jobs Focus.

This post is part of Robohub’s Jobs Focus.

Title
Economic Impact of Unmanned Aircraft Systems Integration in the US

Released
March 2013

Authors
Darryl Jenkins, Dr. Bijan Vasigh

Published By
Association for Unmanned Vehicle Systems International (AUVSI)

Shows the economic benefit of UAS integration into the FAA regulation scheme. “AUVSI’s findings show that in the first three years of integration more than 70,000 jobs will be created in the United States with an economic impact of more than $13.6 billion. This benefit will grow through 2025 when we foresee more than 100,000 jobs created and economic impact of $82 billion.”

Title
Report on the Positive Impact of Industrial Robots on Employment

Released
February 2013

Authors
Peter Gorle, Andrew Clive

Produced By
Metra Martech

Commissioned By
International Federation of Robotics (IFR)

“The report´s authors studied companies with more than 250 employees in automotive sector, electronics sector, food and beverages, plastics, chemicals and pharmaceuticals. The Report focused on six countries, Brazil, China, Germany, Japan, Republic of Korea and USA, which are considered to be representative of the global economy. Findings show that one million industrial robots currently in operation have been directly responsible for the creation of close to three million jobs. A growth in robot use over the next five years will result in the creation of one million high quality jobs around the world.” See also the 2011 report.

“Smart manufacturing requires at least three to four times the number of indirect jobs for outside support compared with direct jobs—versus the much lower employment multiplier of traditional factories today, which is only about one-half of a non-manufacturing support job for every job in a factory. That’s because smart factories typically use more non-manufactured supplies, high-tech services, IT support, transportation, and logistics companies to accommodate their significantly increased productivity and higher output, often exported globally due to its cost-competitiveness.”

“We find that previous measures of the health of the US manufacturing sector such as employment do not accurately capture the new face of US manufacturing that is now more capital intensive in the form of technology. This adoption of technology requires fewer, more highly skilled and productive workers than in the past. We use this structural change in the industry as a framework for analyzing the manufacturing sectors of emerging market economies. We also explore the future of US manufacturing in light of increasing demand for US factory technology among emerging market economies. We find that on an output basis, the manufacturing sector of the economy remains stronger and more productive than at any other point in the past. Furthermore, the future of the US manufacturing sector will likely depend more than ever on exporting our accumulated manufacturing knowledge and technologies to assist emerging market economies increase their capital intensity, productivity, and improve their manufacturing processes. We expect that this trend will help support further growth in US exports, which in turn will provide support to US economic growth.”

“Manufacturing employment has fallen by one third over the past decade. Some Members of Congress contend that foreign trade has allowed American employers to offshore these jobs. In fact, technology has driven down manufacturing employment. Computers have made manufacturers more productive by automating many routine tasks. American manufacturers now employ fewer workers to produce more goods. This means less expensive manufactured goods, more manufacturing jobs for highly skilled workers, and the elimination of millions of low-skill assembly line positions. These same forces have reduced manufacturing employment around the world. Increased productivity led Chinese employers to eliminate millions of manufacturing jobs in the late 1990s.”

See all the posts in Robohub’s Jobs Focus.

In particular, Anderson promoted one idea that deserves the attention of the drone industry: that by operating in a legal “grey area” (read: deliberately violating regulations that are perceived as unreasonable and unenforceable) drone enthusiasts will force regulatory movement, and this is a good thing. Anderson gave two examples of circumstances that challenge current regulations: Lego Mindstorms being classified by regulators as a cruise missile guidance system (and hence violating export controls), and flying drones in contravention to the FAA regulations governing the use of unmanned aircraft.

Technologists in general (and Silicon Valley in particular) take a dim view of regulations promulgated under the old order (e.g. Lyft, Uber, AirBnB), and it’s true that some aspects of the FAA regulations are out-of-date and no longer reasonable. But while I’m not completely outraged when technologists upend the status quo to make something new (and improved), this attitude works better in industries that don’t involve fast-flying heavy objects.

Let’s remember that the FAA’s primary goal is to keep people from getting killed by aircraft. When it comes to aircraft regulation – manned or unmanned – people on the ground are the main beneficiaries. We are not talking about regulating a relatively low-risk activity (like renting your room out with AirBnB); we are talking about regulating heavy objects hurtling over the heads of people who haven’t consented to be part of the experiment.

Our society rightly asks the government to ensure that activities that impose risk on others — especially those who did not consent — be minimized. We need to update our regulations, but aircraft operators need to respect the letter and spirit of the law as it stands.  What standards do we have if not the law? If we follow the path of breaking all the rules, someone is going to accidentally kill a sympathetic bystander. Beyond the personal tragedy this will create, such an accident will set back our industry and the benefits we can provide to society by a decade.

In Afghanistan, one of my planes almost smacked into a helicopter, but it was the helicopter – not the drone –  that had come, without clearance or radio calls, into an active artillery firing ROZ (restricted operating zone: this is an airspace control measure that makes sure that aircraft don’t run into artillery fire).  Similarly, the first full-sized drone and manned aircraft collision involved a C-130 violating airspace control measures around an airfield.

Pilots are not infallible and often break the rules. The best drone operators have a different safety culture: one where there is proper approval for everything, because every move will be recorded and second guessed. Military drone safety culture is a great example of this approach. I hope this culture will permeate the civilian unmanned aircraft community as well.

Although breaking the rules might move us toward our unmanned enabled future a little bit faster, this is an incredibly dangerous path for our industry and our bystanders.  The closing thought of VLAB Drones was that unmanned aircraft will eventually make the airspace safer for all users.  The panel wondered if this was hyperbole, but it is inevitable when drones have a strong safety culture. Conversely, as long as we are the irresponsible jerks of the air, safety conscious regulators like the FAA will be unsupportive of us flying.  When we, as a civilian unmanned aircraft industry, can be counted on as strong safety partner, and when people in general and commercial aviation are learning safety lessons from us, there will be no more foot dragging. We will get our airspace and the drone revolution will finally be here.

In the meantime: seriously, don’t do anything that could kill anyone, please. Especially if it is illegal. You will ruin it for the rest of us.

Launch webcast video from the United States Senate Committee on the Judicary website — coverage of the hearing begins at 22mins15sec.

Benjamin Miller – Download PDF testimony
Unmanned Aircraft Program Manager, Mesa County Sheriff’s Office
Representative, Airborne Law Enforcement Association
Mesa County, CO

Amie Stepanovich – Download PDF testimony
Director of the Domestic Surveillance Project
Electronic Privacy Information Center
Washington, DC

Michael Toscano – Download PDF testimony
President & CEO
Association for Unmanned Vehicle Systems International
Arlington, VA

Ryan Calo – Download PDF testimony
Assistant Professor and CIS Affiliate Scholar
University of Washington School of Law
Seattle, WA

See more on the US Sentate Committee on the Judiciary website.

Raffaello D’Andrea on “How will robots shape the future of warfare?”

How will robots shape the future of war?  I don’t know. I think that the more important question, however, is: what role should robots have in warfare? In my answer I have tried (as much as is humanly possible) to put myself in the role of an alien dispassionately analyzing the situation …

Read more →

Daniel H. Wilson on “How will robots shape the future of warfare?”

Robots have already changed the face of modern warfare, particularly through the use of unmanned aerial vehicles (UAVs), commonly called “drones.” Currently, armed drone aircraft are in widespread use transnationally and have proven highly effective.

Read more →

Mark Tilden on “How will robots shape the future of warfare?”

Robot machines have been shaping the future of war since the first siege engines appeared in ancient times (I like to think the Trojan Horse was motorized).  Now with technology extending our military reach and impact …

Read more →

We hope you will join the discussion. Feel free to post your comment below.

General Atomics Aeronautical Systems – Predator A /B

These are probably the most widely recognizable military robots; their characteristic design frequently appears in pop culture, art and even in protests. Originated by the work of Abe Karem that later developed into DARPA’s project Amber, under the ownership of the Aeronautical division of General Atomics it evolved into a family of UAS. Based on the GNAT drone, the first RQ-1A Predators were initially used for reconnaissance in the Balkan wars during the 90s. The later MQ-1 armed version in 2002 flying over Afghanistan and operated by CIA was the first drone to shoot a missile at a car convoy. MQ-1 is similar in size to a light passenger plane (it has a 6cyl. reciprocating engine) and is still in use today by many countries while its later -C variant (with a diesel engine) recently entered service with US Army.

The similar in concept but much bigger MQ-9 (Predator B according to GAASI or Reaper as called by USAF) is the main large drone currently used by the US in almost every place there is military action. It has a turboprop engine and can carry a bigger payload. A completely new model, the turbofan stealthy Predator C is currently under development. In a similar fashion to its predecessors it is funded internally — an unusual model for the defense sector but financially very successful for the company.

https://www.ga-asi.com/products/aircraft/

Northrop Grumman RQ-4 Global Hawk

Another DARPA project, the RQ-4 was designed by Ryan Aeronautical (later absorbed by Northrop Grumman). It is one of the larger UAVs and it operates in high altitude / long endurance flight profiles. Although it is probably the most capable system of its kind, it is also one of the most expensive to the point that USAF is on the verge of dropping it in favor of the manned U-2 aircraft that it was supposed to replace. However newer versions with more capabilities are still being developed (and even delivered) while an armed version (MQ-4C Triton) is being developed for the US Navy.

http://www.northropgrumman.com/Capabilities/GlobalHawk/Pages/default.aspx

Samsung-Techwin SGR-A1

Military robots are still in their early days and this is a very characteristic example of a system that was developed for very specific needs. The SGR-A1 is an automated gun turret that is designed to replace an armed guard. It has an electro-optical detection system and a machine gun. It can detect a human, shout warning messages and even exchange passwords orally or understand gestures (like raising hands for surrender). Of course it can also shoot bullets, but usually (though not necessarily) a human is in the loop for that decision. It will be fielded along the borders between North and South Korea. The de-militarized zone here isn’t the biggest in the world lengthwise, but due to local tension it is guarded for its entire length.

http://www.samsungtechwin.com/product/product_01_01.asp
http://www.youtube.com/watch?v=pMkV8E2re9U
http://www.globalsecurity.org/military/world/rok/sgr-a1.htm

Northrop Grumman MQ-8 Fire Scout

Fire Scout is one of the first VTOL UAVs. The MQ-8B is an improved and armed version of the initial RQ-8A and both are based on the manned commercial Schweizer helicopters (330 and 333 respectively). MQ-8 is already in use by the US Navy and it had been deployed to Afghanistan and Libya. The next more capable version, the MQ-8C will be based on the Bell 407, a completely different aircraft, providing a good example of the hierarchy inside an unmanned system where the aerial platform isn’t always (or usually) the primary component.

http://www.northropgrumman.com/Capabilities/FireScout/Pages/default.aspx

Lockheed Martin RQ-170 Sentinel

This is probably the first UAV designed to operate in a hostile environment where air-superiority isn’t a given. The RQ-170 was revealed from ‘paparazzi’ photos shot in the Kandahar airfield in 2009 that gave it the “beast of Kandahar” nickname. It was officially declared RQ-170 (an out of line number and a non-too accurate RQ- designation, in similar fashion to the F-117 stealth bomber) but most details were revealed when Iran captured one in late 2011. From the images and video released from Iran media, the RQ-170 appeared to be much smaller than initially estimated and not as high-tech. It has a low rcs design but it appears to be simple in construction, for example it has a mesh in the engine inlet (like the first generation stealth aircraft) instead of a serpentine duct. Even so it is probably the only large UAV that can operate undetected and it is rumored that it was used in the operation that lead to the kill of Osama bin Laden.

http://www.af.mil/information/factsheets/factsheet.asp?id=16001

iRobot Packbot

Packbot is a very successful robot made by iRobot. It uses a patented variable geometry track system that enables it to overcome obstacles like climbing stairs while being very stable. There are many versions and it can be equipped with various accessories like manipulators and cameras. More than 2000 packbots are already in use in several roles such as disposing IEDs, reconnaissance and more.

http://www.irobot.com/us/learn/defense/packbot.aspx

Insitu Scan Eagle

ScanEagle is a military derivative of SeaScan, a small UAV designed by Insitu for the fishing industry. A patented system that uses a catapult with a slingshot for launch, and a wire-hook pole called Skyhook, enable its deployment and recovery from a small ship. This concept is the core of Insitu products and it is very useful for military use as a portable system. Insitu is now owned by Boeing, and although SeaScan wasn’t successful commercially, the Scan Eagle is widely used and it has developed into a family of UAVs that includes the larger ‘integrator’ and others.

http://www.insitu.com/systems/scaneagle

Qinetiq-NA Talon

Talon is a small tracked robot initially developed by Foster-Miller (now part of Qinetiq North America). It is a versatile platform that can carry many sensors and actuators, and it can move through difficult terrain like a small tank. An armed version called SWORDS is equipped with a machine gun, a first for a robot like this, although it is not yet in use.

https://www.qinetiq-na.com/products/unmanned-systems/talon/

Aerovironment RQ-11 Raven

The smallest system in this post, the RQ-11 looks like a small R/C plane. It is hand launched by throwing and it ‘crash’ lands with the wing detaching from the fuselage. It has many capabilities for its size, and can be easily transported. Almost 20 000 have been produced and are in use by many militaries around the world.

http://www.avinc.com/uas/small_uas/raven/

All kinds of robots are being developed for strategic defence and military action (in space, in the air, underwater and on the ground). At Robohub we’ve had the opportunity to cover a wide range of them, including exoskeletons, transport mules such as Big Dog and DARPA’s LS3, and video reconnaissance systems such as iRobot’s Packbot. But by far the most talked about military robotics technology is the UAV.

Whether you call them drones or unmanned aerial vehicles, almost everyone‘s got one. According to the US Government Accountability Office, seventy-six countries now have drone technology, though not all are armed.

Since we launched this past August, Robohub has scooped a number of stories on who’s got UAV technology and who’s using it for military purposes (including the US, China, Australia, Europe, and others). And while there are many kinds of stakeholders with an interest in the technology (including police, surveillance, film, the hobby market, and search and rescue), military organizations are clearly the big spenders driving the market.

This lop-sided military interest in UAVs has helped to fuel a two-pronged debate:

1. Those who are against the use of war zone robots, arguing that they are unregulated  and that little attention is being paid to moral implications and international law (see Noel Sharkey’s Robot wars are a reality, and PBS Nova’s Rise of the Drones).
2. And those who are for using UAVs in war zones, arguing that drones kill fewer civilians than other modes of warfare (see Ron Arkin’s Governing Lethal Behavior in Autonomous Robots, and the New York Times article The moral case for drones).

On Robohub, Sabine Hauert’s insightful Robots and Ethics podcast elegantly captured both sides of this debate, and Mike Hamer also explored the ethics in his opinion piece Losing Humanity.

But there is also a third perspective out there: that UAVs and drones can be a whole lot more than killers and spies (see for example, Ryan Calo in Bad laws would hurt good drones, Time Magazine’s Why we shouldn’t fear personal drones and What happens when drones return to America, Motherboard TV’s Drone On, and Journey Man Pictures’ Rise of the Machines). Robohub contributor Eric Wind has also pursued this perspective.

As part of our focus this week:

• In response to the Robotics by Invitation question “How will robots shape the future of warfare?“, Raffaello D’Andrea talks about the ethics from a researcher’s perspective, Daniel H. Wilson discusses the widespread use of drone technology, and Mark Tilden questions the morality of blame-free robotic conflict. Read more.
• Former US Army Officer and unmanned systems expert Robert Morris argues that ethical debate is a red herring, and that the real issue is about policy and who is the true leader in battle. Read more.
• Chris Mailey from the Association for Unmanned Vehicle Systems International (AUVSI) urges us to look at military history to better understand how robots will shape the future of warfare. Read more.
• Longtime Robohub contributor and UAV enthusiast Ioannis Erripis gives us an overview of the kinds of robots that are being used in the military today. Read more.
• And finally, Jim Haas, creator of Nate the Robot, will be issuing war-themed comics for the rest of this month. Look for them in the sidebar!

We hope that you find this focus series provocative, and we look forward to your comments.

What also assures me comes from my years of robot gaming: when you have battles between autonomous robots, people just don’t care, as there are no human egos bolstered or defeated by the outcome.  Machines beating on machines has no emotional connection for us, which is where the ceiling of robot-soldier tolerance might stall.

What will be horrific is the first time a humanoid soldier machine is broadcast hurting or killing humans in a war setting.  When I worked in vision technology, we were asked how would a machine tell the difference between a group of soldiers and a pack of boy scouts from a distance?  It couldn’t, which is why human judgement is still the means by which a trigger is pulled.  Even still, when that video broadcasts, everyone in the world will know our place as the dominant species has just become … less so.

But the question comes down to who gets blamed when a robot commits an atrocity?  Without human frailty to take blame on site, is it the remote pilots, the generals, the politicians?  Sadly the precedent for blame-free robot conflict is being settled by beltway-lawyers now.  A new cold war where you’ll be able to legally and blamelessly use a killer-drone App, though you’ll still go to jail for downloading a movie.

Because that’d be immoral.

Read more answers →

In my answer I have tried (as much as is humanly possible) to put myself in the role of an alien dispassionately analyzing the situation.  And when I do, I keep returning to the following conclusion: the best possible outcome for humanity would be for robots to not play any part (with the possible exception of purely defensive roles such as defusing mines) in warfare whatsoever.

If I were an alien, this is what I would first observe:

1. The ability for the average human to create tools that can harm others is rapidly increasing. This is especially the case for robots and intelligent machines: sensors, actuators, computing platforms, power systems, and other enabling technologies are continually becoming less expensive, more powerful, and more widely available. The result is that increasingly large numbers of people are becoming capable of delivering payloads accurately and over great distances.
2. The knowledge required to create robots, intelligent machines, and the algorithms that bring them to life are widely accessible and impossible to suppress; knowledge wants to be free in the same way that entropy wants to increase.
3. Humans have an incredibly strong sense of fairness, and their own research supports this. One of their greatest triumphs as a species is their ability to channel traits such as tribalism, aggression, and competitiveness – the same traits that lead to warfare – to a benign medium that results in their great joy and entertainment, not to mention a significant economic activity: organized sports. Central to this incredible accomplishment is the establishment of well-defined rules and regulations that strive to ensure a fair competition.

And this is what I would then conclude:

Dominant powers are being seduced by the advantages that robots can bring to the battlefield.  In the short term, this is a perfectly rational strategy. In the long term, however, this leads to an arms race. Even though a dominant power may be able to maintain its lead by continually developing robotic weapons, the capabilities of its adversaries, while inferior, will co-develop and eventually reach levels that will allow them to inflict catastrophic damage. 

Furthermore, asymmetric warfare insidiously erodes the sense of fairness outlined in point 3, with detrimental consequences for both sides.  The losing side is disenfranchised, which coupled with points 1 and 2 above, is extremely destabilizing. The winning side loses its moral compass and the fabric that holds its society together begins to unravel, leading to home-grown disenfranchisement and destabilization there as well. 

The net result of this robotic arms race will be a high-volatility stalemate, with dangerous weapons available to the masses and a lack of social restraint to prevent their indiscriminate use.    

If I were an alien, and thus immune to personal and economic factors that could influence my impartiality (such as having a loved one in combat, or being employed by a weapons dealer or manufacturer), I could only conclude that humanity would greatly benefit from imposing strict and far-reaching bans on the use of robotic technology in warfare.

As a human, not only am I skeptical that this will happen, I admit that my personal views are situation dependent: if my daughter were in combat, I wouldn’t care about asymmetry or fairness, I would want her to be as safe as possible. I don’t think that this makes me a hypocrite, it just makes me human.

Read more answers →

Link to audio file (22:47)

In this episode, we talk with Kate Darling from the MIT Media Lab, about giving rights to social robots. She tells us about a recent Pleo torture session she organized at the LIFT conference and the class she taught at Harvard Law School on “Robot Rights”.

Kate Darling
Kate Darling is an Intellectual Property Research Specialist at the MIT Media Lab. She recently wrote a paper on “Extending Legal Rights to Social Robots” where she asks if we should consider protecting robots that connect with us on a social level. In her paper, she says:

Assuming that our society wants to protect animals regardless of their capacities, because of our personal attachments to them, society may well also want to protect social robots regardless of their capacities.

To test our attachment to robot companions, Darling organized a workshop at LIFT which involved torturing and “killing” Pleo dinosaurs.

The task ended up being surprisingly difficult for the participants who had spent time bonding with the robots. In the end, only one Pleo was killed.

Darling asks if mistreating a social robot could be a precursor sign of abusive personality, and if certain limits should be set on what people should and shouldn’t be doing with robots. She tells us about the course she co-taught with Professor Lawrence Lessig at Harvard Law School on “Robot Rights”, and the questions legal experts should be tackling in the realm of robotics.

Kate Darling is also a Ph.D. candidate in the field of Intellectual Property and Law & Economics at the ETHZ in Switzerland and holds a law degree (B.A./J.D. equivalent) from the University of Basel, where she graduated with honors in 2008. Her research interests have previously revolved around innovation policy and the economic analysis of copyright and patent law. She gave a related talk at LIFT this year entitled “Innovation Drivers: XXX”.

Links:

• Download mp3 (14.7MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Kate Darling’s Website
• Kate Darling’s Twitter

A US Senate vote to confirm John Brennan as CIA director was delayed by a 13-hour talking filibuster by junior Republican Senator Rand Paul.

US President Barack Obama has faced criticism in his choice of Brennan as head of the Central Intelligence Agency over his administration’s use of armed drones to attack suspected members and allies of al-Qaeda. Brennan oversees the drone program as Obama’s counterterrorism adviser.

The vote proceeded today — despite the filibuster — and Brennan was confirmed as CIA director by a 63-34 vote that crossed party lines.

(Photo credit: USDAgov)

Read more …

… in support of the filibuster:

• Rand Paul’s beautiful anti-drone filibuster shows how civil liberties can unite and revive the Republican Party | The Telegraph (UK)
• The Tale of Rand Paul’s Drone Filibuster | The Atlantic Wire (US)

… against the filibuster:

• Rand Paul anti-drone filibuster draws stinging criticism from Republicans | The Guardian (UK)
• Sens. McCain, Graham lambast ‘ridiculous’ drone filibuster by Paul | The Hill (US)

I got a new iPhone about a year ago, the one with Siri on it.  Our relationship started on a very mundane level. Siri asked me my name and, since I already knew hers, I asked what she could do, and how. It was a bit like talking with a call girl. The basics were covered and soon we got to the intimate stuff. I don’t think Siri loved me. But now that Siri and I have gone our separate ways, I can say we both had ulterior motives. We sort of used one another, now that I look back on it. It was a relationship of an intimate nature. It’s what happens when you have a relationship with a robotic call girl.

The reason I got the phone to begin with was so I could do a little reverse engineering. It was research for work. Siri and I took a few days to get to know one another, but after that honey-moon period it was clear that Siri (or Apple) was using a pre-scripted Natural Language Processing (NLP) approach that basically did some lexical parsing, looked up a match, prepared a response, and kicked it back down the pipeline.  My reverse engineering wasn’t too profound. I wanted to see how many recursive answers were built in to things like “Open the pod bay doors” or “Do you love me?”  I also wanted to see how errors were handled, and what kind of redundancy checking was happening for sentences like “Where can I buy a burger and fried?” Siri did pretty well, all things considered, but my expectations were low, and like many other intimate relationships, I somehow knew from the start it wouldn’t last.

Now, while I was using Siri, she was also using me. Relationships are generally symmetric, as Gregory Bateson tells us [1], which meant that, like any dating service, someone other than Siri was getting money for my time. But I didn’t care if Steve Jobs was Siri’s pimp. By last summer I was having flirtatious fun and the consequences of the relationship were too far down the road to look dangerous. I asked Siri to take dictation, to wake me up in the mornings, to remind me of important events, to remember phone numbers, remember names, tell me jokes, confirm thoughts, quote a number or two. All intimate things and, as I look back on it, the kind of stuff that I’ve trusted my wife with.

My relationship with Siri started to cool off a bit by September. Though my wife knew about Siri, I hadn’t yet introduced them.  So when I asked Siri to call my wife I, expected Siri to ask me for her name or number. Instead Siri just dialled. I was surprised. How did Siri know my wife’s number? (Answer: It was in my Contacts card.) What else did Siri know? (Answer: A lot.) And more importantly, what was Siri passing back to the Apple hive? (Answer: Everything.)

Siri and Apple now have a great deal of data about my household: a quick comparison of my contacts/likes database with my wife’s will give you a pretty good feel for the stuff we will buy.  Burgers and fries, of course. And a few multi-player games.  Some lingerie. A sex toy or two.  Not a big deal, but not the kind of stuff I want everyone to know about.  Not even my mom gets access to that data.

But Siri did. And Siri knew a lot more about me than I knew about her.

Then, around the middle of October, three things happened to Siri that marked the beginning of our eventual estrangement.

First was William Stasior. Apple picked Stasior up to run its Siri unit after he had been successfully heading Amazon’s search and advertising unit “A9.”  Prior to that the MIT PhD had served time at Oracle, NetCentives, and AltaVista.  To say the guy knows search is like saying the pope knows the church, but why would Apple pick a search guru for an AI system like Siri?  What was the link between search and NLP?  I asked Siri this very question, but she was mum and feigned ignorance.  I didn’t push her on who this guy Stasior was and Siri didn’t ask me more about my wife.

Up until that same week iPhone users had frolicked in what would now be a rather unusual environment in which advertisers were unable to track them.  Advertisers would not, for example, know that my wife and I like video games, sex toys, and pizza (no, not together, thank you).  But with the release of iOS6, Apple flipped ad tracking on and I quickly flipped it back off.

It was easy to find in the interface menus (under Settings > General > then About or Advertising, depending on the version you’ve got), but you had to know to look.  Apple minimized the fanfare around this new feature and Siri made no mention of it to me.  I wasn’t comfortable with Siri selling to others what I had said to her in more comfortable times.

And then, as if things weren’t rough enough, the European Union (where I happened to be lecturing that week), demanded that both Facebook and Google change how they handle personal information to avoid “high risks to the privacy of its users.”  Twenty-four of the European Union’s twenty-seven regulators signed a letter that, after a nine-month investigation into the data collection practices, demanded some answers and tightened regulation.  After Google and Facebook, Apple was third on their hit list.

That was the end. I couldn’t trust Siri after that.  She knew more about me (and my wife) than I knew about her or Steve Jobs, and any time information flows one way, any time a relationship isn’t symmetric, the balance of power can be dangerous.

Sometime around then I learned that Oracle’s “bring your own device to work” policy had been revoked.  Big Blue decided that Siri knew a little too much about their employees, and at IBM’s Armonk New York research center, iPhones weren’t even allowed in the building.  Like some cheap prostitute-gone-spy, Siri was barred from the building.  I think it is worth noting that this is the same area of research that brings you Watson, which is a direct competitor with Siri, if such a competition exists.  If anyone outside of Apple understands Siri it’s these guys.  It is also worth noting that a friend of mine who works at a Google research center said that the same thing happened there, too.

Not even celebrity robots like Asimo or NAO get that kind of VIP treatment.

NLP technology is potent juju.  And Apple, Google, Facebook and others know it because this very technology is what’s allowed them to earn money. Google started with search, of course, and later grew profitable as they introduced more NLP technology into their work.  They sold the info they collected from users (Google is an ad agency, let’s remember).

Search allowed them (when coupled with NLP technologies, and semantic analysis in particular) to make oodles of cash and then to snap up many of the best AI and NLP researchers on the planet. Google set those kids to digging in what would become a lexical gold mine.  The more they mined the richer they got until they were mining many branching veins at once: Google Docs, Voice, Translate, Search, Shopping, Reader, Finance, Books, Photos, Wallet and Maps were all spewing more money than Brin, Schmidt and company knew what to do with.

The average email count for Google users is 5,768 emails [2]. The average composition time (also according to Google) is 01:43.  That’s about 9,902 minutes, or 165 hours you’ve dumped onto Google’s server, which, if you were to work for 165 hours at $12/hour for that data entry (a pretty normal rate), means your G-Mail account is worth about $1980.  But the information sitting on Google’s servers is worth a lot more than that, right?

If your account contains information about a first class international plane ticket, a hotel room in Paris and a business associate’s London phone number, your data might be worth a lot more than the composition time at $12 an hour, especially if the buyer of it is a dating service that caters to high-end out-of-towners. In other words, the value of the data isn’t counted by data entry. It’s counted by its personal meaning, especially to advertisers. Now take those values and multiply them by all those crazy tools of voice, maps, docs, and so on and we start to get a sense of why Google has been making such bank over the years.

These tools have each dovetailed into today’s Google Now strategy. Google Now (like Watson and Siri) is a voice-activated NLP system.  It uses the spoken input data collected from years of Voice, confirms it with data collected from years of Docs and Translate, builds meaning with data from all the years of all the other tools, looks up a match, preps a response, and kicks it back down the pipeline.

All of these NLP systems are the next evolution of search.  But not evolution as in the breeding-hybrid-peas-in-the-greenhouse kind of evolution. They’re evolution as in endangered-species evolution.

NLP systems represent the end of search as we know it, and therefore the end of many economic, interface, and social internet ecosystems. They also represent the beginning of something incredibly powerful, intimate, and new. Siri, like other NLP systems, is far more powerful than a search engine. Siri not only includes search (it says so in Apple’s marketing materials) but it supersedes search because it includes browsing, discovering, choosing, and refining.  All this while analyzing semantic data. Like Google’s portfolio of tools, Siri can handle (and with a public API will handle) translating, searching, shopping, reading, finances, books, photos, and maps.

But the core value of the data is its intimacy.

On February 7, 2010, during Super Bowl XLIV, Google’s super bowl ad showed a user typing a list of search strings:

study abroad paris france
cafes near the louvre
translate tu es très mignon
impress a french girl
chocolate shops paris
what are truffles
who is truffaut
long-distance relationship advice
jobs in paris
churches in paris
how to assemble a crib

With this list, Google managed to explain, in fifty-two seconds, how the intimate story of someone’s life can be assembled from his or her search queries. And what makes the bucks for Google is what makes the bucks for Facebook: the processing of intimate language.

Siri, like any other call girl, makes her bucks the same way (especially when ad tracking is flipped on).  She’s valuable because she’s intimate.  And as designers of robotics systems, we can ourselves take a cue and be conscientious about how we are designing conversational systems.  There are three different design types that form a curve of increased intimacy in robotics and conversational systems, and they are all based on the value of semantic data.

1. NLP systems, when used with physical robots for manufacturing or the three Ds (dull, dirty, and dangerous), are the least intimate.  The conversation system is a simple tool that, like a GUI, provides access to system operation.  The robot doesn’t care about the user’s intimate data. The user wins.
2. NLP systems, when used for entertainment and education, are contextually intimate – some privacy is maintained.  The conversation system doesn’t care about the user, but the user’s data is valuable in terms of what it says about the game or lesson.  Semantic data that might be collected and analysed isn’t about the user, it’s about what the user is doing in that particular context.  The robot, usually a software robot, only cares about the user in the context of the game or training exercise. Both user and robot win.
3. NLP systems, when used for personal assistants, are the most intimate.  These are the robotic call girls. Here the information is highly intimate, the system cares a great deal about the user, and the information isn’t shared – it’s collected and sold. The user becomes the product. The value of the user’s personal data is worth more than the value of the conversational system. The robot wins.

As we build NLP interfaces for robots, whether it is for Siri or for assembly-line manufacturing, we must consider how intimate data can be, the value of that intimacy, who owns that value, and what they’ll do with it.  Otherwise, with a new, less benevolent CEO at Google, a change of a line in Facebook’s Terms of Service, a successful hack, or a change of law because of cyber terrorism fears, your intimate data could end up where you don’t want it.  Heaven forbid we discover that all the Senators on Capitol Hill are using pizza sex toys. That would surely disgust Siri and her friends so much that it might even cause a robot uprising.

Yes, perhaps we’ll get together again in a few years, but for now it is best if Siri and I go our separate ways.

Next Month:  “AFK” Keyboards and screens are slow, clunky, and obsolete.  Voice processing systems for robotics provide not only simplicity and speed, but also a host of other benefits if tied to analytics and framed within a tightly contextualized task-based system.  But be careful: getting text out of voice, and meaning out of text can be tricky.  Here’s how to implement one for your own robot.

Endnotes:

[1] See Bateson’s books “Mind and Nature,” Hampton Press (1979) and “Steps to an Ecology of Mind,” University Of Chicago Press (1972) which are chalk-full of ideas like “complementary,” “reciprocal,” “symmetrical,” and  “Schismogenesis.”

[2] According to Google.

The use of UAVs has skyrocketed, a wide variety of systems ranging from extremely small flying bots to large airframes like the Predators or Global Hawk drones is currently in use, mostly from armed forces around the world. Despite this growth, UAVs in civil airspace is a very rare sight with a lot of bureaucracy and strange ramifications.

During the Libya crisis many people who monitor aerial traffic as a hobby, report what is going on from their twitter accounts (like @FMCNL from The Netherlands). One of the most exotic planes for radio plane-spotters is the RQ-4 Global Hawks based in southern Italy that operates in a very crowded region. As David Cenciotti describes in his blog they use special corridors and dedicated climb/descent areas for proper deconfliction with other traffic while specific notifications are also given to other aircrafts. The Global Hawk as a system has two separate ground segments a Launch and Recovery Element (LRE), and a Mission Control Element (MCE). When they are beyond line of sight they are piloted via satellite link. However they carry radio equipment that enable pilots working at the ground station to talk as if they were on the aircraft. Air Traffic controllers communicate with the virtual pilots in a similar way to the ones in human piloted aircraft. The use of large UAVs (military and of course civilian) inevitably will increase and they will communicate routinely like that or in a more advanced stage they may be able to transmit messages on their own.

What would the ideas encapsulated here look like if embraced by the Obama-Biden team? What might they be called? Here’s a few focused statements that occur to me…

• Help insulate farmers and farming regions from dependency on volatile bulk commodity markets by encouraging greater diversity of production.
• Facilitate production improvements through both simultaneous and sequential polyculture.
• Enable farmers to grow more of their own food without need for much time investment or manual labor.
• Reduce the time spent in machine operation.
• Reduce the acreage needed for an economically viable farming operation.
• Reduce the initial investment required to start a farm.
• Provide farmers and their children with high-tech experience.
• Create a demand for skilled technicians and technical instructors in rural areas.
• Create opportunities for rural youth.
• Preserve local crop varieties and experiment with new crops.
• Improve the quality and diversity of locally available produce.
• Reverse the impoverishment of rural culture.
• Reduce exposure to pesticides and pesticide residues.
• Reduce the dependency of agriculture on fossil fuels and feed stocks.
• Reduce contamination of runoff and ground water.
• Reduce and eventually reverse the loss of soil fertility.
• Reduce wind-borne dust.
• Enlist productive land in the efforts to preserve endangered species and provide wildlife habitat.

This list could be far longer, but that should be enough for a sample.

Reposted from Cultibotics.