Machines of Loving Grace

by John Markoff

  While Moravec considered simple robots the baseline for his model of the evolution of artificial intelligence, Brooks wasn’t convinced. In Britain in the early fifties, Grey Walter had built surprisingly intelligent robots—a species zoologically named Machina speculatrix—costing a mere handful of British pounds. Now more than two decades later, “A robot relying on millions of dollars of equipment did not operate nearly as well,” Brooks observed. He noticed that many U.S. developers used Moravec’s sophisticated algorithms, but he wondered what they were using them for. “Were the internal models truly useless, or were they a down payment on better performance in future generations of the Cart?”3

  After receiving his Ph.D. in 1981, Brooks left McCarthy’s “logic palace” for MIT. Here, in effect, he would turn the telescope around and peer through it from the other end. Brooks fleshed out his “bottom-up” approach to robotics in 1986. If the computing requirements for modeling human intelligence dwarfed the limits of human-engineered computers, he reasoned, why not build intelligent behavior as ensembles of simple behaviors that would eventually scale into more powerful symphonies of computing in robots as well as other AI applications? He argued that if AI researchers ever wanted to realize their goal of mimicking biological intelligence, they should start at the lowest level by building artificial insects. The approach precipitated a break with McCarthy and fomented a new wave in AI: Brooks argued in favor of a design that mimicked the simplest biological systems, rather than attempting to match the capability of humans. Since that time the bottom-up view has gradually come to dominate the world of artificial intelligence, ranging from Minsky’s The Society of Mind to the more recent work of electrical engineers such as Jeff Hawkins and Ray Kurzweil, who both have declared that the path to human-level AI is to be found by aggregating the simple algorithms they see underlying cognition in the human brain.

  Brooks circulated his critique in a 1990 paper titled “Elephants Don’t Play Chess,”4 arguing that mainstream symbolic AI had failed during the previous thirty years and a new approach was necessary. “Nouvelle AI relies on the emergence of more global behavior from the interaction of smaller behavioral units. As with heuristics there is no a priori guarantee that this will always work,” he wrote. “However, careful design of the simple behaviors and their interactions can often produce systems with useful and interesting emergent properties.”5

  Brooks did not win over the AI establishment overnight. At roughly the same time that he started designing his robotic insects, Red Whittaker at Carnegie Mellon was envisioning walking on the surface of Mars with Ambler, a sixteen-foot-tall six-legged robot weighing 5,500 pounds. In contrast, Brooks’s Genghis robot was a hexapod weighing just over two pounds. Genghis became a poster child for the new style of AI: “fast, cheap, and out of control”—as the title read of a 1989 article that Brooks cowrote with his grad student Anita M. Flynn. Brooks and Flynn proposed that the most practical way to explore space was by sending out his low-cost insect-like robots in swarms rather than deploying a monolithic overengineered and expensive system.

  Predictably, NASA was initially dismissive of the idea of building robotic explorers that were “fast, cheap, and out of control.” When Brooks presented his ideas at the Jet Propulsion Laboratory, engineers who had been working on costly scientific instruments rejected the idea of a tiny inexpensive robot with limited capabilities. He was undeterred. In the late 1980s and early 1990s, Brooks’s ideas resonated with the design principles underpinning the Internet. A bottom-up ideology, with components assembling themselves into more powerful and complex systems, had captured the popular imagination. With two of his students, Brooks started a company and set out to sell investors on the idea of privately sending small robots into space, first to the moon and later to Mars.6 For $22 million, Brooks proposed, you would not only get your logo on a rover; you could also promote your company with media coverage of the launch. Movies, cartoons, toys, advertising in moondust, a theme park, and remote teleoperation—these were all part of one of the more extravagant marketing campaigns ever conceived. Brooks was aiming for a moon launch in 1990, the first one since 1978, and then planned to send another rocket to Mars just three years later. By 2010, the scheme called for sending micro-robots to Mars, Neptune, its moon Triton, and the asteroids.

  What the plan lacked was a private rocket to carry the robots. The trio spoke with six private rocket launch companies, none of which at the time had made a successful launch. All Brooks needed was funding. He didn’t find any investors in the private sector, so the company pitched another space organization called the Ballistic Missile Defense Organization, which was the Pentagon agency previously tasked to build the Strategic Defense Initiative, a feared and ridiculed Star Wars–style missile defense shield. The project, however, had stalled after the fall of the Soviet Union. For a while, however, the BMDO considered competing with NASA by organizing its own moon launch. The MIT trio built a convincing moon launch rover prototype christened Grendel, intended to hitchhike to the moon aboard a converted “Brilliant Pebble,” the Star Wars launch vehicle originally created to destroy ICBMs by colliding with them in space. Grendel was built in accordance to Brooks’s bottom-up behavior approach, and it had a successful trial, but that was as far as it got.

  The Pentagon’s missile division lost its turf war with NASA. The nation was unwilling to pay for two spacefaring organizations. Ironically enough, years later the developers of the NASA Sojourner, which landed on Mars in 1997, borrowed heavily from the ideas that Brooks had been proposing. Although he never made it into space, a little more than a decade later, Brooks’s bottom-up approach found a commercial niche. iRobot, successor of Brooks’s spacefaring company, gained success by selling an autonomous vacuum cleaner for the civilian market, while a modified mil-spec version toured the Afghanistan and Iraq terrain sniffing out improvised explosive devices.

  Eventually, Brooks would win the battle with the old guard. He found an audience for his ideas about robotics at MIT, and won accolades for what he liked to call nouvelle AI. A new generation of MIT grad students started following him and not Minsky. Nouvelle AI had a widespread impact beyond the United States and especially in Europe, where attention had shifted from the construction of human-level AIs to systems that would exhibit emergent behaviors in which more powerful or intelligent capabilities would be formed from the combination of many simpler ones.

  Brooks’s own interests shifted away from autonomous insects and toward social interactions with humans. With graduate students, he began designing socializing robots. Robots like Cog and Kismet, designed with graduate student Cynthia Breazeal, were used to explore human-robot interaction as well as the capabilities of the robots themselves. In 2014 Breazeal announced that she planned to commercialize a home robot growing out of that original research. She has created a plucky Siri-style family companion that remains stationary on a kitchen counter, hopefully assisting with a variety of household tasks.

  In 2008, Brooks retired from the MIT AI Lab and started a low-profile company with a high-profile name, Heartland Robotics. The name evoked the problem Brooks was trying to solve: the disappearance of manufacturing from the United States as a consequence of lower overseas wages and production costs. As energy and transportation costs skyrocket, however, manufacturing robots offer a potential way to level the playing field between the United States and low-wage nations. For several years there were tantalizing rumors about what Brooks had in mind. He had been working on humanoid robots for almost a decade, but at that point the robotics industry hadn’t even managed to successfully commercialize toy humanoid robots, let alone robots capable of practical applications.

  When Baxter was finally unveiled in 2012, Heartland had changed its name to Rethink, with the humanoid robot receiving mixed reviews. Not everyone understood or agreed with Brooks’s deliberate choice of approximating the human anatomy. Today many of his competitors sell robot arms that make no effort to mimic a human counterpart, opting
for simplicity and function. Brooks, however, is undeterred. His intent is to build a robot that is ready to collaborate with rather than replace human workers. Baxter is one of a generation of robots intended to work in proximity to flesh-and-blood coworkers. The technical term for this relationship is “compliance,” and there is widespread belief among roboticists that over the next half decade these machines will be widely used in manufacturing, distribution, and even retail positions. Baxter is designed to be programmed easily by nontechnical workers. To teach the robot a new repetitive task, humans only have to guide the robot’s arms through the requisite motions and Baxter will automatically memorize the routine. When the robot was introduced, Rethink Robotics demonstrated Baxter’s capability to slowly pick up items on a conveyor belt and place them in new locations. This seemed like a relatively limited contribution to the workplace, but Brooks argues that the system will develop a library of capabilities over time and will increase its speed as new versions of its software become available.

  Rodney Brooks rejected early artificial intelligence in favor of a new approach he described as “fast, cheap, and out of control.” Later he designed Baxter, an inexpensive manufacturing robot intended to work with, rather than replace, human workers. (Photo courtesy of Evan McGlinn/New York Times/Redux)

  It is perhaps telling that one of Rethink’s early venture investors was Jeff Bezos, the chief executive of Amazon. Amazon has increasingly had problems with its nonunionized warehouse workers, who frequently complain about poor working conditions and low wages. When Amazon acquired Kiva Systems, Bezos signaled that he was intent on displacing as much human labor from his warehouses as possible. In modern consumer goods logistics there are two levels of distribution: storing and moving whole cases of goods, and retrieving individual products from those cases. The Kiva system consists of a fleet of mobile robots that are intended to save human workers the time of walking through the warehouse to gather individual products to be shipped together in a composite order. While the humans work in one location, the Kiva robots maneuver bins of individual items at just the right time in the shipping process, and the humans pick out and assemble the products to be shipped. Yet Kiva is clearly an interim solution toward the ultimate goal of building completely automated warehouses. Today’s automation systems cannot yet replace human hands and eyes. The ability to quickly recognize objects among dozens of possibilities and pick them up from different positions remains a uniquely human skill. But for how long? It doesn’t take much imagination to see Baxter, or a competitor from similar companies like Universal Robots or Kuka, working in an Amazon warehouse alongside teams of mobile Kiva robots. Such lights-out warehouses are clearly on the horizon, whether they are made possible by “friendly” robots like Baxter or by more impersonal systems like the ones Google’s new robotics division is allegedly designing.

  As the debates over technology and jobs reemerged in 2012 in the United States, many people were eager to criticize Brooks’s Baxter and its humanoid design. Automation fears have ebbed and flowed in the United States for decades, but because Rethink built a robot in the human form, many thought that Rethink was building machines that should be—and now are—capable of replacing human labor. Today, Brooks argues vociferously that robots don’t simply kill jobs. Instead, by lowering the cost of manufacturing in the United States, robots will contribute to rebuilding the nation’s manufacturing base in new factories with jobs for more skilled, albeit perhaps fewer, workers.

  The debate over humans and machines continues dogging Brooks wherever he travels. At the end of the school year in 2013, he spoke to the parents of graduating students at Brown University. The ideas in his Baxter pitch were straightforward and ones that he assumed would be palatable to an Ivy League audience. He was creating a generation of more intelligent tools for workers, he argued, and Baxter in particular was an example of the future of the factory floor, designed to be used and programmed by average workers. But the mother of one of the students would have none of it. She put up her hand and indignantly asked, “But what about jobs? Aren’t these robots going to take away jobs?” Patiently, Brooks explained himself again. This was about collaborating with workers, not replacing them outright. As of 2006 the United States was sending vast sums annually to China to pay for manufacturing there. That money could provide more jobs for U.S. workers, he pointed out. You’re just speaking locally, she retorted. What about globally? Brooks threw up his hands. China, he contended, needs robots even more than the United States does. Because of their demographics and particularly the one-child policy, the Chinese will soon face a shortage of manufacturing workers. The deeper point that Brooks felt he couldn’t get across to a group of highly educated upper-middle-class parents was that the repetitive jobs Baxter will destroy are not high-quality ones that should be preserved. When the Rethink engineers went into factories, they asked the workers whether they wanted their children to have similar jobs. “Not one of them said yes,” he noted.

  In his office, Brooks keeps photos of the factory manufacturing line of Foxconn, the world’s largest contract maker of consumer electronics products. They are haunting evidence of the kinds of drudgery he wants Baxter to replace. Yet despite his obvious passion for automation and robotics, Brooks has remained more of a realist than many of his robotics and AI brethren in Silicon Valley. Although robots are indeed sprouting legs and moving around in the world among us, they are still very much machines, in Brooks’s view. Despite the deeply ingrained tendency of humans to interact with robots as if they have human qualities, Brooks believes that we have a long way to go before intelligent machines can realistically match humans. “I’ll know they have gotten there,” he said, “when my graduate students feel bad about switching off the robot.”

  He likes to torment his longtime friend and MIT colleague Ray Kurzweil, who is now chartered to build a Google-scale artificially intelligent mega-machine, after having previously gained notoriety for an impassioned and detailed argument that immortality is within the reach of the current human generation through computing, AI, and extraordinary dietary supplements. “Ray, we are both going to die,” he has told Kurzweil. Brooks merely hopes that a future iteration of Baxter will be refined enough to provide his elder care when the day comes.

  The idea that we may be on the verge of an economy running largely without human intervention or participation (or accidents) isn’t new. Almost all of the arguments in play today harken back to earlier disputes. Lee Felsenstein is the product of this eclectic mix of politics and technology. He grew up in Philadelphia, the son of a mother who was an engineer and a father who was a commercial artist employed in a locomotive factory. Growing up in a tech-centric home was complicated by the fact that he was a “red diaper baby.” His father was a member of the U.S. Communist Party, committed enough to the cause that he named Lee’s brother Joe after Stalin.7 However, like many children of Party members, Lee wouldn’t learn that his parents were Communists until he was a young adult—he abruptly lost his summer college work-study position at Edwards Air Force Base, having failed a background investigation.

  Lee’s family was secularly Jewish, and books and learning were an essential part of their childhood. This would mean that bits and pieces of Jewish culture found their way into Lee’s worldview. He grew up aware of the golem legend, Jewish lore that would come to influence his approach to the personal computing world that he in turn would help create. The idea of the golem can be dated back to the earliest days of Judaism. In the Torah, it connotes an unfinished human before God’s eyes. Later it came to represent an animated humanoid creature made from inanimate matter, usually dust, clay, or mud. The golem, animated using kabbalistic methods, would became a fully living, obedient, but only partially human creation of the holy or particularly blessed. In some versions of the tale, the golem is animated by putting a parchment in its mouth, not unlike programming using paper tape. The first modern robot in literature was conceived by Czech writer Karel Čapek in his pl
ay R. U. R. (Rossum’s Universal Robots) in 1921, and so the golem precedes it by several thousand years.

  “Is there a warning for us today in this ancient fable?” wonders R. H. MacMillan, the author of Automation: Friend or Foe?, a 1956 caution about the dangers of computerization of the workplace. “The perils of unrestricted ‘push-button warfare’ are apparent enough, but I also believe that the rapidly increasing part that automatic devices are playing in the peace-time industrial life of all civilized countries will in time influence their economic life in a way that is equally profound.”8

  Felsenstein’s interpretation of the golem fable was perhaps more optimistic than most. Influenced by Jewish folklore and the premonitions of Norbert Wiener, he was inspired to sketch his own vision for robotics. In Felsenstein’s worldview, when robots were sufficiently sophisticated, they would be neither servants nor masters, but human partners. It was a perspective in harmony with Engelbart’s augmentation ideas.

  Felsenstein arrived in Berkeley roughly a decade after Engelbart had studied there as a graduate student in the fifties. Felsenstein became a student during the frenetic days of the Free Speech Movement. In 1973, as the Vietnam War wound down, he set out alongside a small collective of radicals to create a computing utility that offered the power of mainframe computers to the community. They found warehouse space in San Francisco and assembled a clever computing system from a cast-off SDS 940 mainframe discarded by Engelbart’s laboratory at Stanford Research Institute. To offer “computing power to the people,” they set up free terminals in public places in Berkeley and San Francisco, allowing for anonymous access.