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And there are plenty of edge cases to contend with, including sensors being blinded or impaired by bad weather, bright sunlight, or obstructions. Then there are the inevitable software and hardware failures. But more important, the edge cases involve dealing with the unknown. You can’t program a car for every imaginable situation, so at some stage, you have to trust that it will cope with just about anything that’s thrown at it, using whatever intelligence it has. And it’s hard to be confident about that, especially when even the smallest misunderstanding, like mistaking a paper bag for a large rock, could lead a car to do something unnecessarily dangerous.

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For a more hands-on perspective, I head across town to talk to people actually developing self-driving cars. I visit Raj Rajkumar, a member of CMU’s robotics faculty who runs a lab funded by GM. In the fast-moving world of research into driverless cars, which is often dominated by people in Silicon Valley, Rajkumar might seem a bit old school. Wearing a gray suit, he greets me at his office and then leads me to a basement garage where he’s been working on a prototype Cadillac. The car contains numerous sensors, similar to the ones found on Uber’s cars, but they are all miniaturized and hidden away so that it looks completely normal. Rajkumar is proud of his progress on making driverless cars practical, but he warns me that Uber’s taxis might be raising hopes unreasonably high. “It’s going to take a long time before you can take the driver out of the equation,” he says. “I think people should mute their expectations.”

Besides the reliability of a car’s software, Rajkumar worries that a driverless vehicle could be hacked. “We know about the terror attack in Nice, where the terrorist driver was mowing down hundreds of people. Imagine there’s no driver in the vehicle,” he says. Uber says it takes this issue seriously; it recently added two prominent experts on automotive computer security to its team. Rajkumar also warns that fundamental progress is needed to get computers to interpret the real world more intelligently. “We as humans understand the situation,” he says. “We are cognitive, sentient beings. We comprehend, we reason, and we take action. When you have automated vehicles, they are just programmed to do certain things for certain scenarios.”

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I get to experience the reality of the technology’s limits firsthand, about halfway through my ride in Uber’s car, shortly after I’m invited to sit in the driver’s seat. I push a button to activate the automated driving system, and I’m told I can disengage it at any time by moving the steering wheel, touching a pedal, or hitting another big red button. The car seems to be driving perfectly, just as before, but I can’t help noticing how nervous the engineer next to me now is. And then, as we’re sitting in traffic on a bridge, with cars approaching in the other direction, the car begins slowly turning the steering wheel to the left and edging out into the oncoming lane. “Grab the wheel,” the engineer shouts.

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