Why Timnit Gebru wants AI giants to think small
Years after she was ousted from Google, Gebru is still exposing the dangers of building language models that are quite large. [Photo: Kimberly White/Getty Images; Marcel Strauß/Unsplash; rawpixel; Markus Spiske/Unsplash; Michael Dziedzic/Unsplash] BY ISSIE LAPOWSKY Timnit Gebru used to believe it was possible to curb tech giants’ worst impulses from the inside out. She tried it herself at Microsoft, where in 2018 she coauthored a seminal paper that revealed just how bad commercial facial recognition systems—including Microsoft’s—were at detecting Black, female faces. The paper did prompt Microsoft to tweak the accuracy of its system, but Gebru viewed that action as a half-step when the company could have stopped developing facial recognition technology altogether. She tried bringing that level of accountability to Google, where she went to work in the fall of 2018 as colead of the search giant’s ethical AI team. It was there that she cowrote another paper outlining the dangers of large