Bill Duvall was already a computer hacker when he dropped out of college. Not long afterward he found himself face-to-face with Shakey, a six-foot-tall wheeled robot. Shakey would have its moment in the sun in 1970 when Life magazine dubbed it the first âelectronic person.â As a robot, Shakey fell more into the R2-D2 category of mobile robots than the more humanoid C-3PO of Star Wars lore. It was basically a stack of electronic gear equipped with sensors and motorized wheels, first tethered, then later wirelessly connected to a nearby mainframe computer.
Shakey wasnât the worldâs first mobile robot, but it was the first one that was designed to be truly autonomous. An early experiment in artificial intelligence (AI), Shakey was intended to reason about the world around it, plan its own actions, and perform tasks. It could find and push objects and move around in a planned way in its highly structured world. Moreover, as a harbinger of things to come, it was a prototype for much more ambitious machines that were intended to live, in military parlance, in âa hostile environment.â
Although the project has now largely been forgotten, the Shakey designers pioneered computing technologies today used by more than one billion people. The mapping software in everything from cars to smartphones is based on techniques that were first developed by the Shakey team. Their A* algorithm is the best-known way to find the shortest path between two locations. Toward the end of the project, speech control was added as a research task, and today Appleâs Siri speech service is a distant descendant of the machine that began life as a stack of rolling actuators and sensors.
Duvall had grown up on the Peninsula south of San Francisco, the son of a physicist who was involved in classified research at Stanford Research Institute, the military-oriented think tank where Shakey resided. At UC Berkeley he took all the computer programming courses the university offered in the mid-1960s. After two years he dropped out to join the think tank where his father worked, just miles from the Stanford campus, entering a cloistered priesthood where the mainframe computer was the equivalent of a primitive god.
For the young computer hacker, Stanford Research Institute, soon after renamed SRI International, was an entry point into a world that allowed skilled programmers to create elegant and elaborate software machines. During the 1950s SRI pioneered the first check-processing computers. Duvall arrived to work on an SRI contract to automate an English bankâs operations, but the bank had been merged into a larger bank, and the project was put on an indefinite hold. He used the time for his first European vacation and then headed back to Menlo Park to renew his romance with computing, joining the team of artificial intelligence researchers building Shakey.
Like many hackers, Duvall was something of a loner. In high school, a decade before the movie Breaking Away, he joined a local cycling club and rode his bike in the hills behind Stanford. In the 1970s the movie would transform the American perception of bike racing, but in the 1960s cycling was still a bohemian sport, attracting a ragtag assortment of individualists, loners, and outsiders. That image fit Duvallâs worldview well. Before high school he attended the Peninsula School, an alternative elementary and middle school that adhered to the philosophy that children should learn by doing and at their own pace. One of his teachers had been Ira Sandperl, a Gandhi scholar who was a permanent fixture behind the cash register at Keplerâs, a bookstore near the Stanford Campus. Sandperl had also been Joan Baezâs mentor and had imbued Duvall with an independent take on knowledge, learning, and the world.
Duvall was one of the first generation of computer hackers, a small subculture that had originally emerged at MIT, where computing was an end in itself and where the knowledge and code needed to animate the machines were both freely shared. The culture had quickly spread to the West Coast, where it had taken root at computing design centers like Stanford and the University of California at Berkeley.
It was an era in which computers were impossibly rareâa few giant machines were hidden away in banks, universities, and government-funded research centers. At SRI, Duvall had unfettered access to a room-sized machine first acquired for an elite military-funded project and then used to run the software controlling Shakey. At both SRI and at the nearby Stanford Artificial Intelligence Laboratory (SAIL), tucked away in the hills behind Stanford University, there was a tightly knit group of researchers who already believed in the possibility of building a machine that mimicked human capabilities. To this group, Shakey was a striking portent of the future, and they believed that the scientific breakthrough to enable machines to act like humans would come in just a few short years.
Indeed, during the mid-sixties there was virtually boundless optimism among the small community of artificial intelligence researchers on both coasts. In 1966, when SRI and SAIL were beginning to build robots and AI programs in California, another artificial intelligence pioneer, Marvin Minsky, assigned an undergraduate to work on the problem of computer vision on the other side of the country, at MIT. He envisioned it as a summer project. The reality was disappointing. Although AI might be destined to transform the world, Duvall, who worked on several SRI projects before transferring to the Shakey project to work in the trenches as a young programmer, immediately saw that the robot was barely taking baby steps.
Shakey lived in a large open room with linoleum floors and a couple of racks of electronics. Boxlike objects were scattered around for the robot to âplayâ with. The mainframe computer providing the intelligence was nearby. Shakeyâs sensors would capture the world around it and then âthinkââstanding motionless for minutes on endâbefore resuming its journey, even in its closed and controlled world. It was like watching grass grow. Moreover, it frequently broke down or would drain its batteries after just minutes of operation.
For a few months Duvall made the most of his situation. He could see that the project was light-years away from the stated goal of an automated military sentry or reconnaissance agent. He tried to amuse himself by programming the rangefinder, a clunky device based on a rotating mirror. Unfortunately it was prone to mechanical failure, making software development a highly unsatisfying exercise in error prediction and recovery. One of the managers told him that the project was in need of a âprobabilistic decision treeâ to refine the robotâs vision system. So rather than working on that special-purpose mechanism, he spent his time writing a programming tool that could generate such trees programmatically. Shakeyâs vision system worked better than the rangefinder. Even with the simplest machine vision processing, it could identify both edges and basic shapes, essential primitives to understand and travel in its surroundings.
Duvallâs manager believed in structuring his team so that âscienceâ would only be done by âscientists.â Programmers were low-status grunt workers who implemented the design ideas of their superiors. While some of the leaders of the group appeared to have a high-level vision to pursue, the project was organized in a military fashion, making work uninspiring for a low-level programmer like Duvall, stuck writing device drivers and other software interfaces. That didnât sit well with the young computer hacker.
Robots seemed like a cool idea to him, but before Star Wars there werenât a lot of inspiring models. There was Robby the Robot from Forbidden Planet in the 1950s, but it was hard to find inspiration in a broader vision. Shakey simply didnât work very well. Fortunately Stanford Research Institute was a big place and Duvall was soon attracted by a more intriguing project.
Just down the hall from the Shakey laboratory he would frequently encounter another research group that was building a computer to run a program called NLS, the oN-Line System. While Shakey was managed hierarchically, the group run by computer scientist Doug Engelbart was anything but. Engelbartâs researchers, an eclectic collection of buttoned-down white-shirted engineers and long-haired computer hackers, were taking computing in a direction so different it was not even in the same coordinate system. The Shakey project was struggling to mimic the human mind and body. Engelbart had a very different goal. During World War II he had stumbled across an article by Vannevar Bush, who had proposed a microfiche-based information retrieval system called Memex to manage all of the worldâs knowledge. Engelbart later decided that such a system could be assembled based on the then newly available computers. He thought the time was right to build an interactive system to capture knowledge and organize information in such a way that it would now be possible for a small group of peopleâscientists, engineers, educatorsâto create and collaborate more effectively. By this time Engelbart had already invented the computer mouse as a control device and had also conceived of the idea of hypertext links that would decades later become the foundation for the modern World Wide Web. Moreover, like Duvall, he was an outsider within the insular computer science world that worshipped theory and abstraction as fundamental to science.
Artificial intelligence pioneer Charles Rosen with Shakey, the first autonomous robot. The Pentagon funded the project to research the idea of a future robotic sentry. (Image courtesy of SRI International)
The cultural gulf between the worlds defined by artificial intelligence and Engelbartâs contrarian idea, deemed âintelligence augmentationââhe referred to it as âIAââwas already palpable. Indeed, when Engelbart paid a visit to MIT during the 1960s to demonstrate his project, Marvin Minsky complained that it was a waste of research dollars on something that would create nothing more than a glorified word processor.
Despite earning no respect from establishment computer scientists, Engelbart was comfortable with being viewed as outside the mainstream academic world. When attending the Pentagon DARPA review meetings that were held regularly to bring funded researchers together to share their work, he would always begin his presentations by saying, âThis is not computer science.â And then he would go on to sketch a vision of using computers to permit people to âbootstrapâ their projects by making learning and innovation more powerful.
Even if it wasnât in the mainstream of computer science, the ideas captivated Bill Duvall. Before long he switched his allegiance and moved down the hall to work in Engelbartâs lab. In the space of less than a year he went from struggling to program the first useful robot to writing the software code for the two computers that first connected over a network to demonstrate what would evolve to become the Internet. Late in the evening on October 29, 1969, Duvall connected Engelbartâs NLS software in Menlo Park to a computer in Los Angeles controlled by another young hacker via a data line leased from the phone company. Bill Duvall would become the first to make the leap from research to replace humans with computers to using computing to augment the human intellect, and one of the first to stand on both sides of an invisible line that even today divides two rival, insular engineering communities.
Significantly, what started in the 1960s was then accelerated in the 1970s at a third laboratory also located near Stanford. Xeroxâs Palo Alto Research Center extended ideas originally incubated at McCarthyâs and Engelbartâs labs, in the form of the personal computer and computer networking, which were in turn successfully commercialized by Apple and Microsoft. Among other things, the personal computing industry touched off what venture capitalist John Doerr identified during the 1990s as the âlargest legal accumulation of wealth in history.â1
Most people know Doug Engelbart as the inventor of the mouse, but his more encompassing idea was to use a set of computer technologies to make it possible for small groups to âbootstrapâ their projects by employing an array of ever more powerful software tools to organize their activities, creating what he described as the âcollective IQâ that outstripped the capabilities of any single individual. The mouse was simply a gadget to improve our ability to interact with computers.
In creating SAIL, McCarthyâs impact upon the world was equal to Engelbartâs in many ways. People like Alan Kay and Larry Tesler, who were both instrumental in the design of the modern personal computer, passed through his lab on their way to Xerox and subsequently to Apple Computer. Whitfield Diffie took away ideas that would lead to the cryptographic technology that secures modern electronic commerce.
There were, however, two other technologies being developed simultaneously at SRI and SAIL that are only now beginning to have a substantial impact: robotics and artificial intelligence software. Both of these are not only in the process of transforming economies; they are fostering a new era of intelligent machines that is fundamentally changing the way we live.
The impact of both computing and robotics had been forecast before these laboratories were established. Norbert Wiener invented the concept of cybernetics at the very dawn of the computing era in 1948. In his book Cybernetics, he outlined a new engineering science of control and communication that foreshadowed both technologies. He also foresaw the implications of these new engineering disciplines, and two years after he wrote Cybernetics, his companion book, The Human Use of Human Beings, explored both the value and the danger of automation.
He was one of the first to foresee the twin possibilities that information technology might both escape human control and come to control human beings. More significantly he posed an early critique of the arrival of machine intelligence: the danger of passing decisions on to systems that, incapable of thinking abstractly, would make decisions in purely utilitarian terms rather than in consideration of richer human values.
Engelbart worked as an electronics technician at NASAâs Ames Research Center during the 1950s, and he had watched as aeronautical engineers first built small models to test in a wind tunnel and then scaled them up into full-sized airplanes. He quickly realized that the new silicon computer circuits could be scaled in the opposite directionâdown into what would become known as the âmicrocosm.â By shrinking the circuitry it would be possible to place more circuits in the same space for the same cost. And dramatically, each time the circuit density increased, performance improvement would not be additive, but rather multiplicative. For Engelbart, this was a crucial insight. Within a year after the invention of the modern computer chip in the late 1950s he understood that there would ultimately be enough cheap and plentiful computing power to change the face of humanity.
This notion of exponential changeâMooreâs law, for exampleâis one of the fundamental contributions of Silicon Valley. Computers, Engelbart and Moore saw, would become more powerful ever more quickly. Equally dramatically, their cost would continue falling, not incrementally, but also at an accelerating rate, to the point where soon remarkably powerful computers would be affordable by even the worldâs poorest people. During the past half decade that acceleration has led to rapid improvement in technologies that are necessary components for artificial intelligence: computer vision, speech recognition, and robotic touch and manipulation. Machines now also taste and smell, but recently more significant innovations have come from modeling human neurons in electronic circuits, which has begun to yield advances in pattern recognitionâmimicking human cognition.
The quickening pace of AI innovation has led some, such as Rice University computer scientist Moshe Vardi, to proclaim the imminent end of a very significant fraction of all tasks performed by humans, perhaps as soon as 2045.2 Even more radical voices argue that computers are evolving at such a rapid pace that they will outstrip the intellectual capabilities of humans in one, or at the most two more generations. The science-fiction author and computer scientist Vernor Vinge posed the notion of a computing âsingularityâ in which machine intelligence will make such rapid progress that it will cross a threshold and then in some as yet unspecified leap, become superhuman.
It is a provocative claim, but far too early to answer definitively. Indeed, it is worthwhile recalling the point made by longtime Silicon Valley observer Paul Saffo when thinking about the compounding impact of computing. âNever mistake a clear view for a short distance,â he has frequently reminded the Valleyâs digerati. For those who believe that human labor will be obsolete in the space of a few decades, itâs worth remembering that even against the background of globalization and automation, between 1980 and 2010, the U.S. labor force actually continued to expand. Economists Frank Levy and Richard J. Murnane recently pointed out that since 1964 the economy has actually added seventy-four million jobs.3
MIT economist David Autor has offered a detailed explanation ...
