Machines of Loving Grace (2 page)

Recent experiments that guaranteed a “basic income” in the poorest part of the world may also offer a profound insight into the future of work in the face of encroaching, brilliant machines.
The results of these experiments were striking because they ran counter to the popular idea that economic security undercuts the will to work.
An experiment in an impoverished village in India in 2013 guaranteeing basic needs had just the opposite effect.
The poor did not rest easy on their government subsidies; instead, they became more responsible and productive.
It is quite likely that we will soon have the opportunity to conduct a parallel experiment in the First World.
The idea of a basic income is already on the political agenda in Europe.
Raised by the Nixon administration in the form of a negative income tax in 1969, the idea is currently not politically acceptable in the United States.
However, that will change quickly if technological unemployment becomes widespread.

What will happen if our labor is no longer needed?
If jobs for warehouse workers, garbage collectors, doctors, lawyers, and journalists are displaced by technology?
It is of course impossible to know this future, but I suspect society will find that humans are hardwired to work or find an equivalent way to produce something of value in the future.
A new economy will create jobs that we are unable to conceive of today.
Science-fiction writers, of course, have already covered this ground well.
Read John Barnes’s
Mother of Storms
or Charlie Stross’s
Accelerando
for a compelling window into what a future economy might look like.
The simple answer is that human creativity is limitless, and if our basic needs are looked after by robots and AIs, we will find ways to entertain, educate, and care for one another in new ways.
The answers may be murky but the questions are increasingly sharp.
Will these intelligent machines that interact with and care for us be our allies or will they enslave us?

In the pages that follow I portray a diverse set of computer scientists, hackers, roboticists, and neuroscientists.
They share
a growing sense that we are approaching an inflection point where humans will live in a world of machines that mimic, and even surpass, some human capabilities.
They offer a rainbow of sensibilities about our place in this new world.

During the first half of this century, society will be tasked with making hard decisions about the smart machines that have the potential to be our servants, partners, or masters.
At the very dawn of the computer era in the middle of the last century, Norbert Wiener issued a warning about the potential of automation: “We can be humble and live a good life with the aid of the machines,” he wrote, “or we can be arrogant and die.”

It is still a fair warning.

John Markoff
                     

San Francisco, California
 

January 2015
                     

B
ill 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 “electronic person.”
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 wasn’t the world’s 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 “a hostile environment.”

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 Apple’s 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 bank’s 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 Duvall’s 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 Kepler’s, a bookstore near the Stanford Campus.
Sandperl had also been Joan Baez’s 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 rare—a 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 “play” with.
The mainframe computer providing the intelligence was nearby.
Shakey’s sensors would capture the world around it and then “think”—standing motionless for minutes on end—before 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 “probabilistic decision tree” to refine the robot’s 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.
Shakey’s 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.

Duvall’s manager believed in structuring his team so that
“science” would only be done by “scientists.”
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 didn’t sit well with the young computer hacker.

Robots seemed like a cool idea to him, but before Star Wars there weren’t 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 didn’t 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.
Engelbart’s 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 world’s 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 people—scientists, engineers, educators—to 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 Engelbart’s contrarian idea, deemed “intelligence augmentation”—he referred to it as “IA”—was 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, “This is not computer science.”
And then he would go on to sketch a vision of using computers to permit people to “bootstrap” their projects by making learning and innovation more powerful.

Even if it wasn’t 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 Engelbart’s 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 Engelbart’s 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.

S
ignificantly, what started in the 1960s was then accelerated in the 1970s at a third laboratory also located near Stanford.
Xerox’s Palo Alto Research Center extended ideas originally incubated at McCarthy’s and Engelbart’s 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 “largest legal accumulation of wealth in history.”
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