Car manufacturers will have difficulty demonstrating just how safe self-driving vehicles are because of what’s at the core of their smarts: machine learning.

“You can’t just assume this stuff is going to work,” says Phillip Koopman, a computer scientist at Carnegie Mellon University who works in the automotive industry.

In 2014, a market research firm projected that the self-driving car market will be worth $87 billion by 2030. Several companies, including Google, Tesla, and Uber, are experimenting with computer-assisted or fully autonomous driving projects—with varying success because of the myriad technical obstacles that must be overcome.

Koopman is one of several researchers who believe that the nature of machine learning makes verifying that these autonomous vehicles will operate safely very challenging.

Traditionally, he says, engineers write computer code to meet requirements and then perform tests to check that it met them.

But with machine learning, which lets a computer grasp complexity—for example,…[Read more]