How will people travel in the future?
have enthused technologists as much as the self-driving car. Advances in machine learning, a subfield of artificial intelligence , would enable cars to teach themselves to drive by drawing on reams of data from the real world. The more they drove, the more data they would collect, and the better they would become. Robotaxis summoned with the flick of an app would make car ownership obsolete. Best of all, reflexes operating at the speed of electronics would drastically improve safety.
And the technology was just around the corner. In 2015 Elon Musk, Tesla’s boss, predicted his cars would be capable of “complete autonomy” by 2017. Mr Musk is famous for missing his own deadlines. But he is not alone. General Motors said in 2018 that it would launch a fleet of cars without steering wheels or pedals in 2019; in June it changed its mind.
The future, in other words, is stuck in traffic. Partly that reflects the tech industry’s predilection for grandiose promises. But self-driving cars were also meant to be a flagship for the power ofHit the brakes One is that, for all the advances in machine learning, machines are still not very good at learning. Most humans need a few dozen hours to master driving. Waymo’s cars have had over 10m miles of practice, and still fall short. And once humans have learned to drive, even on the easy streets of Phoenix, they can, with a little effort, apply that knowledge anywhere, rapidly learning to adapt their skills to rush-hour Bangkok or a gravel-track in rural Greece. Computers are less flexible.
Another lesson is that machine-learning systems are brittle. Learning solely from existing data means they struggle with situations that they have never seen before. Humans can use general knowledge and on-the-fly reasoning to react to things that are new to them—a light aircraft landing on a busy road, for instance, as happened in Washington state in August . Autonomous-car researchers call these unusual situations “edge cases”. Driving is full of them, though most are less dramatic.
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