Building A Baby-Brained AI

A psychologist's work inspires autonomous carmakers to think young.

- Bryan Gardiner

Alison Gopnik's career began with a psychology experiment she now considers ridiculous. Aiming to understand how 15-month-olds connect words with abstract concepts (daddy = caregiver), she decided to visit nine kids once a week for a year. The then Oxford graduate student would record everything they said as part of her dissertation. “It was absurd for a million reasons,” says Gopnik, holed up on a winter Friday in her office at the University of California at Berkeley, where she is a professor of developmental psychology. “If a child had moved away, if there weren’t any takeaways after the year, or any number of things, all that work would have been gone,” she says, before adding, “I would never allow a student of mine to do anything like that today.”

Though her experiment didn’t solve any language-acquisition mysteries, it did overturn her assumptions about childhood learning and intelligence—and it altered her career path. Now her research has drawn the interest of artificial-intelligence scientists who want to adapt her insights to their machine-learning algorithms. What she learned about kids’ smarts while a grad student still holds sway—for her field and possibly theirs. “Instead of thinking about children as these kind of starter adults, I realized they were profoundly different,” says Gopnik, now 62, and with her own grown children and grandchildren. “The way they use words, the meanings they express, the way they express them—none of it matched how adults think or speak.”