In January, 2015, the computer scientist Sebastian Thrun became fascinated by a conundrum in medical diagnostics. Thrun, who grew up in Germany, is lean, with a shaved head and an air of comic exuberance; he looks like some fantastical fusion of Michel Foucault and Mr. Bean. Formerly a professor at Stanford, where he directed the Artificial Intelligence Lab, Thrun had gone off to start Google X, directing work on self-learning robots and driverless cars. But he found himself drawn to learning devices in medicine. His mother had died of breast cancer when she was forty-nine years old—Thrun’s age now. “Most patients with cancer have no symptoms at first,” Thrun told me. “My mother didn’t. By the time she went to her doctor, her cancer had already metastasized. I became obsessed with the idea of detecting cancer in its earliest stage—at a time when you could still cut it out with a knife. And I kept thinking, Could a machine-learning algorithm help?”

The New Yorker → A.I. Versus M.D.