Machines of Loving Grace (17 page)

As part of that effort he created a laboratory that was a
paradise for researchers who wanted to mimic humans in machine form.
At the same time it would also create a cultural chasm that resulted in a computing world with two separate research communities—those who worked to replace the human and those who wanted to use the same technologies to augment the human mind.
As a consequence, for the past half century an underlying tension between artificial intelligence and intelligence augmentation—AI versus IA—has been at the heart of progress in computing science as the field has produced a series of ever more powerful technologies that are transforming the world.

It is easy to argue that AI and IA are simply two sides of the same coin.
There is a fundamental distinction, however, between approaches to designing technology to benefit humans and designing technology as an end in itself.
Today, that distinction is expressed in whether increasingly capable computers, software, and robots are designed to assist human users or to replace them.
Early on some of the researchers who passed through SAIL rebelled against McCarthy-style AI.
Alan Kay, who pioneered the concept of the modern personal computer at Xerox during the 1970s, spent a year at SAIL, and would later say it was one of the least productive years of his career.
He already had fashioned his Dynabook idea—“a personal computer for children of all ages”
²⁷
—that would serve as the spark for a generation of computing, but he remained an outsider in the SAIL hacker culture.
For others at SAIL, however, the vision was clear: machines would soon match and even replace humans.
They were the coolest things around and in the future they would meet and then exceed the capabilities of their human designers.

Y
ou must drive several miles from the Carnegie Mellon University campus to reach a pleasantly obscure Pittsburgh residential neighborhood to find Hans Moravec.
His office is
tucked away in a tiny apartment at the top of a flight of stairs around the corner from a small shopping street.
Inside, Moravec, who retains his childhood Austrian accent, has converted a two-room apartment into a hideaway office where he can concentrate without interruption.
The apartment opens into a cramped sitting room housing a small refrigerator.
At the back is an even smaller office, with curtains down, dominated by large computer displays.

Several decades ago, when he captured the public’s attention as one of the world’s best-known robot designers, magazines often described him as “robotic.”
In person, he is anything but, breaking out in laughter frequently and with a self-deprecating sense of humor.
Still an adjunct professor at the Robotics Institute at Carnegie Mellon, where he taught for many years, Moravec, one of John McCarthy’s best-known graduate students, has largely vanished from the world he helped create.

When Robert M.
Geraci, a religious studies professor at Manhattan College and author of
Apocalyptic AI: Visions of Heaven in Robotics, Artificial Intelligence, and Virtual Reality
(2010), came to Pittsburgh to conduct his research several years ago, Moravec politely declined to see him, citing his work on a recent start-up.
Geraci is one of a number of authors who have painted Moravec as the intellectual cofounder, with Ray Kurzweil, of a techno-religious movement that argues that humanity will inevitably be subsumed as a species by the AIs and robots we are now creating.
In 2014 this movement gained generous exposure as high-profile technological and scientific luminaries such as Elon Musk and Stephen Hawking issued tersely worded warnings about the potential threat that futuristic AI systems hold for the human species.

Geraci’s argument is that there is a generation of computer technologists who, in looking forward to the consequences of their inventions, have not escaped Western society’s religious roots but rather recapitulated them.
“Ultimately, the promises
of Apocalyptic AI are almost identical to those of Jewish and Christian apocalyptic traditions.
Should they come true, the world will be, once again, a place of magic,”
²⁸
Geraci wrote.
For the professor of religion, the movement could in fact be reduced to the concept of alienation, which in his framing is mainly about the overriding human fear of dying.

Geraci’s conception of alienation isn’t simply a 1950s James Dean–like disconnect from society.
Yet it is just as hard to pin Moravec on the more abstract concept of fear of death.
The robotics pioneer became legendary for taking up residence in the attic of McCarthy’s SAIL lab during the 1970s, when it was a perfect counterculture world for the first generation of computer hackers who discovered that the machines they had privileged access to could be used as “fantasy amplifiers.”

During the 1970s, McCarthy continued to believe that artificial intelligence was within reach even with the meager computing resources then at hand, famously noting that a working AI would require: “1.8 Einsteins and one-tenth the resources of the Manhattan Project.”
²⁹
In contrast, Moravec’s perspective was rooted in the rapidly accelerating evolution of computing technology.
He quickly grasped the implications of Moore’s law—the assertion that over time computing power would increase exponentially—and extended that observation to what he believed would be the logical conclusion: machine intelligence was inevitable and moreover it would happen relatively soon.
He summed up the obstacles faced by the AI field in the late 1970s succinctly:

He first outlined his disagreement with McCarthy in 1975 in the SAIL report “The Role of Raw Power in Intelligence.”
³¹
It was a powerful manifesto that steeled his faith in the exponential increase in processing power and simultaneously convinced him that the current limits were merely a temporary state of affairs.
The lesson he drew early on, and to which he would return throughout his career, was that if you were stymied as an AI designer, just wait a decade and your problems would be solved by the inexorable increase in computing performance.
In a 1978 essay for the science-fiction magazine
Analog,
he laid out his argument for a wider public.
Indeed in the
Analog
essay he still retained much of McCarthy’s original faith that machines would cross the level of human intelligence in about a decade: “Suppose my projections are correct, and the hardware requirements for human equivalence are available in 10 years for about the current price of a medium large computer,” he asked.
“What then?”
³²
The answer was obvious.
Humans would be “outclassed” by the new species we were helping to evolve.

After leaving Stanford in 1980, Moravec would go on to write two popular books sketching out the coming age of intelligent machines.
Mind Children: The Future of Robot and Human Intelligence
(1988) contains an early detailed argument that the robots that he has loved since childhood are in the process of evolving into an independent intelligent species.
A decade later he refined the argument in
Robot: Mere Machine to Transcendent Mind
(1998).

Significantly, although it is not widely known, Doug Engelbart
had made the same observation, that computers would increase in power exponentially, at the dawn of the interactive computing age in 1960.
³³
He used this insight to launch the SRI-based augmentation research project that would help lead ultimately to both personal computing and the Internet.
In contrast, Moravec built on his lifelong romance with robots.
Though he has tempered his optimism, his overall faith never wavered.
During the 1990s, in addition to writing his second book, he took two sabbaticals in an effort to hurry the process of perfecting the ability to permit machines to see and understand their environments so they could navigate and move freely.

The first sabbatical he spent in Cambridge, Massachusetts, at Danny Hillis’s Thinking Machines Corporation, where Moravec hoped to take advantage of a supercomputer.
But the new supercomputer, the CM-5, wasn’t ready.
So he contented himself with refining his code on a workstation while waiting for the machine.
By the end of his stay, he realized that he only needed to wait for the power of a supercomputer to come to his desktop rather than struggle to restructure his code so it would run on a special-purpose machine.
A half decade later, on a second sabbatical at a Mercedes-Benz research lab in Berlin, he again had the same realization.

Moravec still wasn’t quite willing to give up and so after coming back from Germany he took a DARPA contract to continue work on autonomous mobile robotic software.
But after writing two best-selling books over a decade arguing for a technological promised land, he decided it was really time to settle down and do something about it.
The idea that the exponential increase of computing power would inevitably lead to artificially intelligent machines was becoming more deeply ingrained in Silicon Valley, and a slick packaging of the underlying argument was delivered in 2005 by Ray Kurzweil’s
The Singularity Is Near
.
“It was becoming a spectacle and it was interfering with real work,” he decided.
By now he had taken
to heart Alan Kay’s dictum that “the best way to predict the future is to invent it.”

His computer cave is miles from the offices of Seegrid, the robotic forklift company he founded in 2003, but within walking distance of his Pittsburgh home.
For the past decade he has given up his role as futurist and became a hermit.
In a way, it is the continuation of the project he originally began as a child.
Growing up in Canada, at age ten Moravec had built his first robot from tin cans, batteries, lights, and a motor.
Later, in high school, he went on to build a robotic turtle capable of following a light and a robotic hand.
At Stanford, he became the force behind the Stanford Cart project, a mobile robot with a TV camera that could negotiate obstacle courses.
He had inherited the Cart system when he arrived at Stanford in 1971 and then gradually rebuilt the entire system.

Shakey was the first autonomous robot, but the Stanford Cart, with a long and colorful history of its own, is the true predecessor of the autonomous car.
It had first come to life as a NASA-funded project in the mechanical engineering department in 1960, based on the idea that someday a vehicle would be remotely driven on the surface of the moon.
The challenge was how to control such a vehicle given the 2.7-second propagation delay defining the round-trip radio signal between the Earth and the moon.

Funding for the initial project was rejected because the logic of keeping a human in the loop had won out.
When in 1962 President Kennedy committed the nation to the manned exploration of the moon, the original Cart was shelved
³⁴
as unnecessary.
The robot, about the size of a card table with four bicycle wheels, sat unused until in 1966 SAIL’s deputy director Les Earnest rediscovered it.
He persuaded the mechanical engineering department to lend it to SAIL to experiment in making an autonomous vehicle.
Eventually, using the computing power of the SAIL mainframe, a graduate student was able to program the robot to follow a white line on the floor
at a speed of less than one mile per hour.
A radio control link enabled remote operation.
Tracking would have been simpler with two photocell sensors, but a video camera connected to a computer was seen as a tour de force at the time.

Moravec would modify and hack the system for a decade so that ultimately it would be able to make it across a room, correctly navigating an obstacle course about half the time.
The Cart failed in many ways.
Attempting to simultaneously map and locate using only single camera data, Moravec had undertaken one of the hardest problems in AI.
His goal was to build an accurate three-dimensional model of the world as a key step toward understanding it.

At the time the only feedback came from seeing how far the Cart had moved.
It didn’t have true stereoscopic vision, so the Cart lacked depth perception.
As a cost-saving measure, he would move the camera back and forth along a bar at right angles to the field of view, making it possible for the software to calculate a stereo view from a single camera.
It was an early predecessor of the software approach taken decades later by the Israeli computer vision company Mobileye.