John Markoff filing story from airport. Image credit: Joi via Wikimedia Commons

If you are working in the field of robotics or AI, you may be used to fielding calls from journalists wanting to better understand the technology. But not all journalists are created equal. Pulitzer-Prize-winning John Markoff (@markoff) has been covering the technology beat at the New York Times for almost three decades, and recently published Machines of Loving Grace – a book that chronicles the evolution of computer science, robotics and AI. In this interview we turn the lens around and ask Markoff about what motivates his interest to report on robotics, and how he sees trends in robotics today being informed by people and events from the past.

This interview has been edited for length and clarity.

[HS] Can you tell us about your early days writing about the fields of AI and robotics?

[JM] I began writing about Silicon Valley in 1977 and spent most of my time writing about personal computing and the Internet. In the ‘80s there was a lot of controversy around the Strategic Defense Initiative (SDI) and many computer scientists and AI researchers were opposed to it – it was the first big AI issue in the news. Then in 2004 there was the DARPA autonomous vehicle challenge, and I began covering those events.

Engelbart’s prototype of a computer mouse, as designed by Bill English from Engelbart’s sketches. Image: Wikipedia via Macworld

It wasn’t until a bit later that I really made AI and Robotics my first interest, though. I’d covered computer security for the New York Times forever, but I began feeling that I’d written the same story just too many times. I needed to do something different, and it seemed like AI and robotics were making more progress.

I’ve always loved the social history of the Valley, and trying to understand how things are connected there. Often technologies will bubble around for decades before they actually gain broad consumer acceptance. Look at the mouse, for example. Engelbart invented it in ’64 but it really didn’t become a mass consumer product until Microsoft Windows and Mac adopted it 20 years later. I’m interested in what causes things to gain acceptance even though there were people who believed in them for years beforehand.

There are other examples … In 2010, the historian David Brock came across a 1951 memo written by William Shockley describing an “Automatic Trainable Robot”. Shockley had always been known for his work on transistors, but what the memo showed was that he had really set out to build a robotics company. To discover that early ideas in robotics were at the core of creating Silicon Valley was a bit of a revelation that nobody had really noticed until then.

Shockley’s 1951 memo to president of Bell Labs Mervin Kelly described an “automatic trainable robot” that sounds eerily similar to trainable products on the market today, such as Rethink’s Baxter. For more details, see the IEEE Spectrum article by David Brock How William Shockley’s Robot Dream Helped Launch Silicon Valley.

Your book describes a funny anecdote around that revelation … when Rod Brooks shared that memo with his employees and asked them to guess when it had been written…

Rod gave the memo to his employees, and nobody could figure out the timing of it, because if you just read the memo and don’t think about the date, it reads like a product description of Baxter. So here we have an idea for a “trainable robot” from 1951 … and 65 years later it looks like the timing is finally right.

Machines of Loving Grace starts out describing the tension between two researchers doing early work in computer science – John McCarthy and Douglas Engelbart – whose work eventually led to the creation of two philosophical “camps” in AI research. What was that tension about?

In the ‘60s McCarthy was involved in setting up the Stanford AI Laboratory, and Engelbart set up the Augmentation Research Center at SRI. They were each were about a mile from Stanford, but they had very different approaches. Whereas McCarthy had set out to build a working “artificial intelligence” that could simulate human capabilities (he thought this could be done within a decade), Engelbart was going in the opposite direction – he wanted to use technology to augment intellectual workers.

I came to realize that these two approaches – artificial intelligence (AI) and intelligence augmentation (IA) – went in two philosophically different directions … and that two distinct research communities emerged from those early laboratories – communities that don’t really speak to each other.

The paradox we see now is that the same technologies that extend our abilities can also displace us – and that was the puzzle I wanted to solve in my book.

There were several key figures in your book – Norbert Wiener and McCarthy come to mind – who really broke over differences in their philosophical approach to AI … Can you describe what was at the root of their polarization?

Read Frank Tobe’s review: New book by John Markoff explores common ground between humans and robots

Wiener was an interesting character – an outlier in his day, and rather eccentric.

In 1948 Wiener wrote ‘Cybernetics’, a book that outlined his approach to control and communication engineering. That work led him to believe that it was possible that humans could one day be designed out of the future, and so two years later he wrote a second more philosophical book called the ‘Human Use of Human Beings‘ about the AI/IA dichotomy, where he attempted to lay out the choice we have in terms of how we use technology.

At that point, technological unemployment was a new concern. Industrial automation had already been happening for decades, but Wiener was the first one to really understand the potential of software-controlled machines and he brought that alarm to the US labour movement. He actually wrote letters to many labour leaders to warn them that the technology was going to have an impact on the workforce, saying “This may end up destroying much of your union membership’s jobs.”

We know Wiener was a very controversial character within the engineering and academic communities; he had lots of enemies and his ideals were never mainstream. He was seen as a radical, going all the way back to his opposition to the technical community designing weapons in the wake of World War II.

On the other hand, McCarthy was very clear about saying that he deliberately coined the term “artificial intelligence” in order to set his ideas apart from Wiener. He felt that Cybernetics leaned too far towards the analogue. On a personal level, McCarthy really disliked Wiener, too; he thought that Wiener was bombastic and a bore, and he wanted nothing to do with him.

So there was this tension right at the root of artificial intelligence, and it has all kinds of significance for the field.

For the most part your book chronicles events that take place in the US. Was the same tension between AI and IA happening in other places, too?   

That’s an interesting question. Cybernetics was more appealing to the Europeans, and there are Departments of Cybernetics in universities across Europe to this day. I am fascinated by that, even though I really did focus on the US in my book.

Sir James Lighthill. Image via Wikipedia. Watch the BBC Lighthouse Debates on YouTube.

AI actually had its first big failure not in the US but in England as a result of Lighthill Report, which assessed the claims made by the AI researchers in the early 1970s and then cut off government funding for their research, causing what we now call the “AI Winter”. That collapse of funding had a big impact on many people’s careers. Geoffrey Hinton for example is now a well-known Google researcher, and is one of the key figures in development of advance neural net technologies, but early in his career he really was an outcast as a result of that report.

Then there was Joseph Weizenbaum, who had a similar outlook to Wiener. He ran the famous ELIZA experiment at MIT and was aghast that a simple text bot was able to convince his students that they were having real conversations with it. In his book ‘Computer Power and Human Reason’ he was very critical of AI research on a philosophical and ethical level for ignoring human values. He left the US disgusted, and ended up being much more widely accepted in Europe. 

What about Japan? Fast forwarding to the present, your book mentions Toyota’s current corporate philosophy of kaizen (or “good change”) as a shift that suggests there are limits to automation. Can you describe that philosophy and how it’s influenced Toyota’s policies?

While Toyota had at one time been pushing towards fully automated assembly lines, more recently they have begun to systematically put humans back into their manufacturing processes. They have come to see that if you fully automate a production line, it might be extremely reliable, but it’s frozen … an automated assembly line doesn’t really improve.

But skilled workers who are on the production line are intimately familiar with the manufacturing process, and can suggest ways to improve efficiency and productivity. So Toyota is rebalancing automation with craft in order to get a more cooperative relationship between humans and robots.

In September 2015 Toyota announced a substantial investment in robotics and AI research to develop “advanced driving support” technology, with former Program Manager of DARPA’s DRC Gill Pratt directing the overall project as Executive Technical Advisor. Toyota will allocate USD$50M over the next five years in a partnership with MIT’s CSAIL (headed by Daniela Rus) and Stanford’s SAIL (headed by Fei-Fei Li) to develop research facilities in Stanford and Cambridge. Photo: Kathryn Rapier

What’s interesting is that just this past fall Toyota invested in the AI departments of both MIT and Stanford to do research on an intelligent car that they clearly describe as being on the IA side of the AI-IA debate. They are not looking to build pure self-driving cars, but instead want to give you a kind of guardian angel that will watch over you as you drive. They really want to design humans “in” rather than design them “out”.

I spend a lot time with the AI community in my research, and I think half of the field really feels strongly that you should use AI technologies in an IA format, keeping humans in the loop. People like Adam Cheyer, Eric Horvitz and Tom Gruber are all well-known AI researchers who see Engelbart as their hero. Horvitz in particular feels strongly about approaching things from that direction.

In 2009 after the AAAI Meeting on Long Term AI Futures you wrote an article for the New York Times with the headline ‘Scientists Worry Machines May Outsmart Man‘. More recently, covering the DARPA challenge, your headline was ‘Relax, The Terminator is Far Away’. Has your perspective on robotics and AI changed in that time period?

The AAAI Alisomar meeting was really motivated by Eric Horwitz in response to WIRED article the founder of Sun Microsystems Bill Joy wrote in 2000 about Why the Future Doesn’t Need Us, where he raised concerns about AI and robotics as threats to human survival.

Horvitz felt that he needed to respond to Joy’s concerns, so in 2009 he called together a group of the best AI researchers in the country to explore the issue of how fast AI technologies were developing and whether they indeed posed a serious threat to humanity. That was where the first headline came from, and I was really a messenger in that case.

Funny enough, the final report from the meeting was somewhat anti-climactic: they basically came to a consensus of that the kind of scenario Joy had sketched out was not an immediate worry.

Now fast-forward to last year, when my article about the DAPRA Robotic Challenge came out. This was toward the end of the renewed AI debate that had just been touched off by Stephen Hawking, Elon Musk, Stuart Russell, Nick Bostrum, and others at the Future of Life Institute who were arguing that, based on half a decade of success in the neural network community, they foresee an exponential increase in the capability of machines coming in the near future.

But many computer scientists think that the possibility of self-aware thinking machines is vastly overstated, and my experience watching the DARPA Robotics Challenge supported that view. You just had to look at the falling robots, and the fact most of them couldn’t even open a door. That’s the state of the art.

I guess it’s still an open debate, but as for my own feelings, I’m sceptical about some of the claims being made about AI.

Douglas Hofstadter was one of the philosophers who originally called out the AI researchers in 1960s and 1970s for over-promising and under-delivering. He argued that the assertions about AI programs and their progress is a little bit like someone who climbs to the top of the tree, saying he is making steady progress on the way to the moon. But at some point the tree stops. I feel like that statement still holds.

I thought it funny when Elon Musk was quoted last year as saying “We will be like a pet Labrador if we’re lucky” and how close that was to Marvin Minsky’s famous in the 1970s saying “If we are lucky they will treat us like pets.” But you seem to be saying that these kinds of statements aren’t just attention-grabbing or click bait – they are also over-promising what AI can do, albeit in a negative way … 

Elon has this wonderful ability to say evocative things like “we are summoning the demon”.

Some people have criticized the media for their reporting of the Future of Life Institute’s activities, but I felt that the Institute may have brought this on themselves to some degree. They talk about the “existential risks” of AI, so it’s no surprise that some of the media picked up on this and jumped immediately to The Terminator. Afterall, what is The Terminator if it’s not an existential threat?

I don’t think that existential threat is a bad motif for people’s concerns, but I also think this is a field that routinely over-promises. It’s true that we have seen significant progress in terms of machines that can see, listen and understand natural language. But cognition reasoning systems are still making baby steps.

That said, I’m supportive of the efforts of Elon Musk and his colleagues at the Future of Life Institute because I do believe that machine autonomy is increasingly becoming a reality in everything from the workplace to weapons, and it’s worth talking about these issues whether autonomous machines are self-aware or not.

As a journalist following the field, you’ve had a unique opportunity to watch a whole new crop of roboticists and AI experts mature. Is this next generation continuing to fuel the polarization between AI and IA, or are the two camps starting to merge?

It’s hard to predict what will become of this current debate. Looking at the issue of technological unemployment in particular, I’ve come to feel that the actual impact of automation technologies on the workforce is a much murkier question than either the press or the science community seems to believe.

Once you start reading the economists, you realize there is a multiplicity of issues going on, including things like tax policy and changing demography, and picking it apart is very difficult. It’s a huge debate, and I’ve come away feeling I know less than when I started.

But I’ve spent a lot of time talking to people working in this field – mostly around Stanford and Berkeley – and it makes me hopeful because there is a generation of young scientists and engineers who are actually exposed to some of the issues we’ve been talking about and are really thinking about them. Ultimately, these machines are being built by humans, so it comes down to individuals having to make decisions about how to design their machines, and their values become really important.

Thank you! It was such a pleasure to read your book and to have a chance to talk to you today.

It was great talking to you – I enjoyed it.

Machines of Loving Grace was released in August 2015, and is available in hardcover, softcover and e-book formats. 

If you liked this post, you may also enjoy:

• New book by John Markoff explores common ground between humans and robots

• Talking Machines: History of machine learning, w. Geoffrey Hinton, Yoshua Bengio, Yann LeCun
• Funding high risk proposals at the National Science Foundation: A brief history
• Passion for utility drove Engelberger’s vision for robotics
• Should cars be fully driverless? No, says MIT engineer and historian David Mindell
• DARPA’s Gill Pratt on Google’s robotics investments
• From pencil and paper to hands-on making, a brief history of MIT’s legendary MechE 2.007

An excited crowd cheers for students in 2.70 (the precursor of 2.007) as they compete in the final competition in 1979. Photo courtesy of the MIT Museum.

Alissa Mallinson | Department of Mechanical Engineering

It’s hard to ignore the fact that a worldwide maker movement is well underway. Over the past 10 or so years, community Maker Faires have become all the rage; fabrication shops have popped up around the world for both professionals and hobbyists; and websites, tools, and toys catering to do-it-yourselfers are on the rise.

It’s easy to appreciate how a love for making became wildly popular again, especially as STEAM (science, technology, engineering, art, and math) is increasingly and passionately promoted and embraced around the world.

Of course, at MIT — particularly in the Department of Mechanical Engineering (MechE) — it’s been this way since 1865.

It was around that time that MIT was founded by scientist and educator William Barton Rogers, who had a different idea about how to educate and learn. He founded MIT to teach not only the ability to think critically but also how to apply that thinking to real-world problems — to teach craftsmen and farmers as well as engineers and academics. From that moment on, it’s been in MechE DNA to upend traditional ways of teaching and to democratize science and technology for the betterment of all.

So the motto was coined (“mens et manus,” or “mind and hand”), the seal was drawn (the scholar and the smith), and by the 1970s, when Professor Emeritus Woodie Flowers was transforming course 2.70 — now 2.007 (Design and Manufacturing) — into a project-based, get-your-hands-dirty, build-competition experience, MechE’s reputation for innovative education was already solidified. Yet the magnitude of transforming a design and manufacturing class from a mostly pencil-and-paper experience to one of fun and hands-on building was a profound paradigm shift in engineering education.

Knowledge is of course essential, Flowers says, because uninformed imagination can be quite dangerous, but at the same time, “nobody is getting hired to solve the multiple-choice problems at the end of the chapter.”

He created a class to prepare students not only to design an object but also to build it. From the beginning, 2.007 was meant to develop students’ competence and self-confidence as design engineers, while emphasizing the creative design process and the application of physical laws.

“I learned from my father that doing things in a different way was often fruitful, and the underpinnings of all my educational efforts is to allow people a path to change their self-image,” Flowers says. “Students might struggle with equations and other rigorous elements of an MIT education, but in 2.007 they can be superstars.”

The first challenges were purely mechanical traps and contraptions, using a universal set of materials pre-determined by Flowers, and the students loved it. Their creations went head-to-head at end-of-year competitions that became the most attended events at the Institute.

Since then, several faculty members have followed in Flowers’ footsteps as instructor of 2.70/2.007, including Professor Emeritus David Gordon; Wilson; former Professor Harry West; Professor Alex Slocum; and Professor Dan Frey, each imbuing the class with a bit of their own style and personality. Along the way, the contraption competition became a robot competition, mechanical components became electromechanical ones, wires became remote controllers, and autonomous challenges were introduced.

And yet, says Assistant Professor Amos Winter, “The fundamental principles of 2.007 haven’t changed. Because core mechanical principles like forces, energy, bearings, and shafts work the same as they always have and haven’t gone out of style. Whether a car uses internal combustion or is a hybrid, it still comes down to transferring power to the road.”

In 2013, Professor Dan Frey passed the torch to Associate Professor Sangbae Kim and Winter, who are co-instructing the class. Kim is a renowned expert in biomimetics and robotics, and Winter is a leader in designing technologies for developing and emerging markets. Together the two have made several curriculum updates to the class, including eliminating exams and adding weekly written homework, weekly physical homework, and an oral design review.

As is the tradition now, the class ends in a final robot competition in which students compete against each other to see whose robot can win the most points. Each student is required to enter the competition, but only 32 finalists will enter the ring on competition day.

“The most exciting thing about 2.007 is that the students get to build their own personal robot and compete in front of an audience of more than 500 people,” Kim says. “We create a new theme every year, having in mind a particular physical task that will require the students to apply the theories they’ve learned to specific engineering functions and transfer their knowledge from paper to working robot.”

This spring’s competition was called “Hack to the Future,” a nod to the classic film “Back to the Future,” which had its 30th anniversary this fall. Using a universal kit of tools and materials, students were challenged to build a robot that could collect plutonium, climb the Clock Tower, slide Doc Brown down a cable, and open a DeLorean door. As always students each developed their own strategies for gaining points, and the student whose robot earned the most points at the end of each duel progressed to the next round until there was only one champion left standing: Alison Edwards, whose robot was efficient and reliable.

“I hope students in 2.007 walk away from the class with engineering intuition,” Winter says. “I want them to go out into the world around them and almost have a kind of superpower — to see what’s going on behind face value, like forces, and stresses, and energy transfer. It’s that kind of intuition that we try to build by bringing real-world examples into the classroom and showing them how to match theory with what actually happens.”

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

• Talking Machines: History of machine learning, w. Geoffrey Hinton, Yoshua Bengio, Yann LeCun
• NSF’s 40-year history supporting US robotics research
• The evolution of assembly lines: A brief history
• Funding high risk proposals at the National Science Foundation: A brief history
• Father of robotics Joseph F. Engelberger dies at age 90

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

Joseph F. Engelberger, Ars Electronica Symposium 1996. Image courtesy of Ars Electronica.

Robotics Industry Association | Joseph F. Engelberger, an engineer and entrepreneur who pioneered the robotics field, died peacefully at his home this morning, December 1, 2015, in Newtown, Connecticut. Engelberger – widely known as the “Father of Robotics” and creator of the world’s first industrial robot – revolutionized modern industrial and automotive manufacturing processes and went on to establish robotics in human services. Engelberger was 90 years old.

Engelberger Legacy: Using Robotics to Automate Manufacturing Industry

Engelberger, an industry advocate, author, and international ambassador for robotics, founded Unimation, Inc., in 1956, the world’s first industrial robotics manufacturer. Working closely with inventor George Devol, he developed the first industrial robot in the U.S., called “Unimate”, which was installed for industrial use in a General Motors plant in 1961. Since then, approximately three million industrial robots have been installed in manufacturing facilities around the world.

“Joe made some of the most important contributions to technological advancement in the history of the world,” said Jeff Burnstein, President of the Robotic Industries Association (RIA), the first and only robotics trade association and an organization Engelberger was instrumental in founding. “Because of Joe, robotics became a global industry. He was years ahead of his time, envisioning robots based on insects and birds decades ago –– developments that we’re finally seeing today. His question, ‘Do you think a robot could do that?’ inspired researchers to answer ‘yes’ and develop the amazing robotics applications found worldwide today.”

After selling Unimation to Westinghouse, Engelberger’s focus shifted from industrial robotics to robotics in human services. Through HelpMate Robotics, Engelberger developed HelpMate, a robot hospital courier currently used in hospitals worldwide as well as spearheading development of robotic applications to assist in care for elderly and disabled individuals.

Engelberger’s industrial applications fundamentally changed the automotive manufacturing sector, introducing robotics that enabled manufacturers to achieve greater efficiency and precision with the use of robotic arms on assembly lines. The innovations Engelberger introduced were a major factor in the rise of the Japanese auto industry, where the use of robotics was enthusiastically embraced in the post-war era.

Engelberger’s Many Accolades

Engelberger was inducted into the U.S. Manufacturers Hall of Fame in 2009. The RIA named its prestigious annual award the Joseph F. Engelberger Award in recognition of his outstanding contributions to the field of robotics. Other honors Engelberger received over the course of his career include induction into the National Academy of Engineering and the Connecticut Academy of Science and Engineering. Engelberger’s books, Robotics in Practice and Robotics in Service, are considered seminal texts on robotics and have been translated into multiple languages and distributed worldwide.

Engelberger won numerous major awards honoring his pioneering efforts in the robotics, including the Society of Manufacturing Engineers’ Progress Award, the Nyselius Award from the American Die Casting Institution, the Leonardo da Vinci Award from the American Society of Mechanical Engineers, the American Machinist Award, the Golden Omega Award at the Electrical Electronics Insulation Conference, the McKechnie Award from the University of Liverpool, the Egleston Medal from Columbia University, the Beckman Award at the LabAutomation Conference, and the Japan Prize.

Profiled in the London Sunday Times as one of the “1000 Makers of the 20th Century”, Engelberger has received honorary doctorates from the University of Bridgeport, Briarwood College, Spring Garden College, Trinity College, and Carnegie Mellon University.

“Joe was the Henry Ford for the robotics business and a tremendous international ambassador,” said Don Vincent, past RIA President. “It was Joe’s personal drive and commitment to make forming Robotics Industries Association a reality along with his pioneering talents that convinced his competitors that RIA was needed for the future of manufacturing.”

Read RIA’s Tribute to Joseph Engelberger.

Read the RIA obituary listing.

Read the SVR tribute on the occasion of Engelberger’s 90th birthday.

Born July 26, 1925 in Brooklyn, New York, Engelberger earned a bachelor’s degree in physics and a master’s degree in electrical engineering from Columbia University. 

About Robotic Industries Association (RIA)

Founded in 1974, RIA is a not-for-profit trade association dedicated to improving the regional, national and global competitiveness of the North American manufacturing and service sectors through promotion and enhancement of robotics and related automation. RIA represents over 350 robot manufacturers, system integrators, component suppliers, end users, consulting firms, research groups, and educational institutions. The association hosts a number of events including the International Collaborative Robots Workshop, the National Robot Safety Conference, the A3 Business Forum (February 3-5, 2016 in Orlando, FL) and the biennial Automate Show & Conference (April 3-6, 2017 in Chicago). RIA also provides quarterly robotics statistics and has a content-rich website, Robotics Online. For more details on RIA, visit Robotics Online or call 734/994-6088.

About Association for Advancing Automation (A3)

The Association for Advancing Automation is the global advocate for the benefits of automating. A3 promotes automation technologies and ideas that transform the way business is done. A3 is the umbrella group for Robotic Industries Association (RIA), AIA – Advancing Vision + Imaging, and Motion Control and Motor Association (MCMA). RIA, AIA, and MCMA combined represent some 900 automation manufacturers, component suppliers, system integrators, end users, research groups and consulting firms from throughout the world that drive automation forward. For more information, please visit our websites: A3 – www.A3automate.org. RIA – www.robotics.org. AIA –www.visiononline.org. MCMA –www.motioncontrolonline.org.

Learn more about Joseph Engelberger and the history of robotics:

• New book by John Markoff explores common ground between humans and robots
• Industrial robotics pioneer Joe Engelberger turns 90
•  NSF’s 40-year history supporting US robotics research
•  The evolution of assembly lines: A brief history
•  Funding high risk proposals at the National Science Foundation: A brief history
•  Case study shows new roles for robots in today’s economy

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