Machines of Loving Grace (7 page)

Unlike laboratories of the previous era that emphasized basic science, such as IBM Research and Bell Labs, Google’s X Lab was closer in style to PARC, which had been established to vault the copier giant, restyled “the Document Company,” into the computer industry—to compete directly with IBM.
The X Lab was intended to push Google into new markets.
Google
felt secure in its Web search monopoly so, with a profit stream that by the end of 2013 was more than $1 billion a month, the search company funded ambitious R & D projects that might have nothing to do with the company’s core business.
Google was famous for its 70-20-10 rule, which gave its engineers free time to pursue their own side projects.
Employees are supposed to spend 10 percent of their time on projects entirely unrelated to the company’s core business.
Its founders Sergey Brin and Larry Page believed deeply in thinking big.
They called their efforts “moon shots”: not pure science, but research projects that were hopefully destined to have commercial rather than purely scientific impact.

It was a perfect environment for Thrun.
His first project in 2008 had been to create the company’s fleet of Street View cars that systematically captured digital images of homes and businesses on every street in the nation.
The next year he began an even more ambitious effort: a self-driving car that would travel on public streets and highways.
He was both cautious and bold in the car project.
A single accident might destroy the Google car, so at the outset he ensured that a detailed safety regime was in place.
He was acutely aware that if there was any indication in the program that Google had not been incredibly careful, it would be a disaster.
He never let an untrained driver near the wheel of the small Toyota Prius fleet on which the system was being developed.
The cars would eventually drive more than a half-million miles without an accident, but Thrun understood that even a single error every fifty thousand to a hundred thousand miles was too high an error rate.
At the same time he believed that there was a path forward that would allow Google to redefine what it meant to be in a car.

Like the automotive industry, Thrun and his team believed in the price/volume curve, which suggested that costs would go down the more a company manufactured a particular thing.
Sure, today a single experimental lidar laser radar might cost tens of thousands of dollars, but the Google engineers had faith
that in a few years it would be so cheap that it would not be a showstopper in the bill of materials of some future car.
In the trade-off between cost and durability, Thrun always felt it would make sense to design and build more reliable systems now and depend on mass manufacturing technologies for price reductions to kick in later.
The pricey laser guidance systems didn’t actually contain that many parts, so there was little reason to believe that prices couldn’t come down rapidly.
It had already happened with radar, which had once been an esoteric military and aviation technology but in recent years had begun showing up in motion detectors and premium automobiles.

Thrun evinced an engineer’s worldview and tended toward a libertarian outlook.
He held a pro-business point of view that the global corporation was an evolutionary step beyond the nation-state.
He also subscribed to the belief, commonplace in the Valley, that within three decades as much as 90 percent of all jobs will be made obsolete by advancing AI and robotic technologies.
Indeed, Thrun believed that most people’s jobs are actually pretty useless and unfulfilling.
There are countless manual labor jobs—everything from loading and unloading trucks to driving them—that could vanish over the coming decade.
He also believed that much of the bureaucratic labor force is actively counterproductive.
Those people make other people’s work harder.
Thrun had a similar contempt for what he perceived as Detroit’s hidebound car industry that could have easily used technology to radically reshape transportation systems and make them safer, but did little and was content to focus on changing the shape of a car’s tail fins each year.
By 2010 he had a deep surprise in store for an industry that did not change easily and was largely unfamiliar with Silicon Valley culture.
⁵

T
he DARPA races created ripples in Detroit, the cradle of the American automotive industry, but the industry kept
to its traditional position that cars were meant to be driven by people and should not operate autonomously.
By and large the industry had generally resisted computer technology.
Many car manufacturers adhered to a “computers are buggy” philosophy.
However, engineers elsewhere in the country were beginning to think about transportation through the new lens of cheap sensors, the microprocessor, and the Internet.

In the spring of 2010, rumors about an experimental Google car began to float around Silicon Valley.
Initially they sounded preposterous.
The company, nominally a provider of Internet search, was supposedly hiding the cars in plain sight.
Google engineers, so the story went, had succeeded in robotically driving from San Francisco to Los Angeles on freeways at night!
The notion immediately elicited both guffaws and pointed reminders that such an invention would be illegal, even if it was possible.
How could they get away with something so crazy?

Of course, Google’s young cofounders Sergey Brin and Larry Page had by then perfected a public image for wild schemes based on AI and other futuristic technologies to transform the world.
Eric Schmidt, the company’s chief executive officer beginning in 2001, would tell reporters that his role was one of adult supervision—persuading the cofounders which of their ideas should be kept above and which below the “bar.”
The cofounders famously considered the idea of a space elevator.
New, incredibly strong material had recently been developed, and this material was so strong that, rather than using a rocket, it would be possible to build a cable that reached from the Earth into orbit to inexpensively hoist people and materials into space.
When queried about the idea Schmidt would pointedly state that this was one of the ideas that was being considered, but was—for the moment at least—“below the bar.”

In the hothouse community of technical workers that is Silicon Valley, however, it is difficult to keep secrets.
It was obvious that something was afoot.
Within a year after the final DARPA Grand Challenge event in 2007, Sebastian Thrun had taken a
leave from Stanford and gone to work full-time at Google.
His departure was never publicly announced, or even mentioned in the press, but among the Valley’s digerati, Thrun’s change of venue was noted with intense interest.
A year later, while he was with colleagues in a bar in Alaska at an artificial intelligence conference, he spilled out a few tantalizing comments.
Those words circulated back in Silicon Valley and made people wonder.

In the end, however, it was a high school friend of one of the low-paid drivers the company had hired to babysit its robotic Prius fleet who inadvertently spilled the beans.
One of the kids I went to high school with is being paid fifteen dollars an hour by Google to sit in a car while it drives itself!
a young college student blurted to me.
At that point the secret became impossible to contain.
The company was parking its self-driving cars in the open lots on the Google campus.

The Google engineers had made no effort to conceal the sensors attached to the roof of the ungainly-looking creatures, which looked even odder than their predecessor, Stanford’s Stanley.
Rather than an array of sensors mounted above the windshield, each Prius had a single 360-degree lidar, mounted a foot above the center of the car’s roof.
The coffee-can-sized mechanical laser, made by Velodyne, a local high-tech company, made it possible to easily create a real-time map of the surrounding environment for several hundred feet in all directions.
It wasn’t cheap—at the time the lidar alone added $70,000 to the vehicle cost.

How did the odd-looking Toyotas, also equipped with less obtrusive radars, cameras, GPS, and inertial guidance sensors, escape discovery for as long as they did?
There were several reasons.
The cars were frequently driven at night, and the people who saw them confused them with a ubiquitous fleet of Google Street View cars, which had a large camera on a mast above the roof taking photographs that were used to build a visual map of the surrounding street as the car drove.
(They
also recorded people’s Wi-Fi network locations, which then could be used as beacons to improve the precision in locating Google’s Android smartphones.)

The Street View assumption usually hid the cars in plain sight, but not always.
The Google engineer who had the pleasure of the first encounter with law enforcement was James Kuffner, a former CMU roboticist who had been one of the first members of the team.
Kuffner had made a name for himself at Carnegie Mellon working on both navigation and a variety of humanoid robot projects.
His expertise was in motion planning, figuring out how to teach machines to navigate in the real world.
He was bitten by the robot car bug as part of Red Whittaker’s DARPA Grand Challenge team, and when key members of that group began to disappear into a secret Google project code-named Chauffeur, he jumped at the chance.

Late one night they were testing the robotic Prius in Carmel, one of the not-quite-urban driving areas they were focusing on closely.
They were testing the system late at night because they were anxious to build detailed maps with centimeter accuracy, and it was easier to get baseline maps of the streets when no one was around.
After passing through town several times with their distinctive lidar prominently displayed, Kuffner was sitting in the driver’s seat when the Prius was pulled over by a local policeman suspicious about the robot’s repeated passes.

“What is this?”
he asked, pointing to the roof.

Kuffner, like all of the Google drivers, had been given strict instructions how to respond to this inevitable confrontation.
He reached behind him and handed a prewritten document to the officer.
The police officer’s eyes widened as he read it.
Then he grew increasingly excited and kept the Google engineers chatting late into the night about the future of transportation.

The incident did not lead to public disclosure, but once I discovered the cars in the company’s parking lots while reporting for the
New York Times,
the Google car engineers relented and offered me a ride.

From a backseat vantage point it was immediately clear that in the space of just three years, Google had made a significant leap past the cars of the Grand Challenge.
The Google Prius replicated much of the original DARPA technology, but with more polish.
Engaging the autopilot made a whooshing
Star Trek
sound.
Technically, the ride was a remarkable tour de force.
A test drive began with the car casually gliding away from Google’s campus on Mountain View city streets.
Within a few blocks, the car had stopped at both stop signs and stoplights and then merged onto rush-hour traffic on the 101 freeway.
At the next exit the car then drove itself off the freeway onto a flyover overpass that curved gracefully over the 101.
What was most striking to the first-time passenger was the car’s ability to steer around the curve exactly as a human being might.
There was absolutely nothing robotic about AI’s driving behavior.

When the
New York Times
published the story, the Google car struck Detroit like a thunderbolt.
The automobile industry had been adding computer technology and sensors to cars at a maddeningly slow pace.
Even though cruise control had been standard for decades, intelligent cruise control—using sensors to keep pace with traffic automatically—was still basically an exotic feature in 2010.
A number of automobile manufacturers had outposts in Silicon Valley, but in the wake of the publicity surrounding the Google car, the remaining carmakers rushed to build labs close by.
Nobody wanted to see a repeat of what happened to personal computer hardware makers when Microsoft Windows became an industry standard and hardware manufacturers found that their products were increasingly low-margin commodities while much of the profit in the industry flowed to Microsoft.
The automotive industry now realized that it was facing the same threat.

At the same time, the popular reaction to the Google car was mixed.
There had long been a rich science-fiction tradition of
Jetsons
-like futuristic robot cars.
They had even been the stuff of TV series like
Knight Rider,
a 1980s show featuring
a crime fighter assisted by an artificially intelligent car.
There was also a dark-side vision of automated driving, perhaps best expressed in Daniel Suarez’s 2009 sci-fi thriller
Daemon,
in which AI-controlled cars not only drove themselves, but ran people down as well.
Still, the general perception was a deep well of skepticism about whether driverless cars would ever become a reality.
However, Sebastian Thrun had made his point abundantly clear that humans are terrible drivers, largely the consequence of human fallibility and inattention.
By the time his project was discovered, Google cars had driven more than a hundred thousand miles without an accident, and over the next several years that number would rise above a half-million miles.
A young Google engineer, Anthony Levandowski, routinely commuted from Berkeley to Mountain View, a distance of fifty miles, in one of the Priuses, and Thrun himself would let a Google car drive him from Mountain View to his vacation home in Lake Tahoe on weekends.