wired | The repercussions of Gebru’s termination quickly radiated out from her team to the rest of Google and, beyond that, to the entire discipline of AI fairness research.
Some Google employees, including David Baker, a director who’d been at the company for 16 years, publicly quit over its treatment of Gebru. Google’s research department was riven by mistrust and rumors about what happened and what might happen next. Even people who believed Gebru had behaved in ways unbecoming of a corporate researcher saw Google’s response as ham-handed. Some researchers feared their work would now be policed more closely. One of them, Nicholas Carlini, sent a long internal email complaining of changes that company lawyers made to another paper involving large language models, published after Gebru was fired, likening the intervention to “Big Brother stepping in.” The changes downplayed the problems the paper reported and removed references to Google’s own technology, the email said.
Soon after, Google rolled out its response to the roiling scandal and sketched out a more locked-down future for in-house research probing AI’s power. Marian Croak, the executive who had shown interest in Gebru’s work, was given the task of consolidating the various teams working on what the company called responsible AI, including Mitchell and Gebru’s. Dean sent around an email announcing that a review of Gebru’s ouster had concluded; he was sorry, he said, that the company had not “handled this situation with more sensitivity.”
Dean also announced that progress on improving workforce diversity would now be considered in top executives’ performance reviews—perhaps quietly conceding Gebru’s assertion that leaders were not held accountable for their poor showing on this count. And he informed researchers that they would be given firmer guidance on “Google’s research goals and priorities.” A Google source later explained that this meant future projects touching on sensitive or commercial topics would require more input from in-house legal experts, product teams, and others within Google who had relevant expertise. The outlook for open-minded, independent research on ethical AI appeared gloomy. Google claimed that it still had hundreds of people working on responsible AI, and that it would expand those teams; the company painted Gebru and Mitchell’s group as a tiny and relatively unimportant cog in a big machine. But others at Google said the Ethical AI leaders and their frank feedback would be missed. “For me, it’s the most critical voices that are the most important and where I have learned the most,” says one person who worked on product changes with Gebru and Mitchell’s input. Bengio, the women’s manager, turned his back on 14 years of working on AI at Google and quit to join Apple.
Outside of Google, nine Democrats in Congress wrote to Pichai questioning his commitment to preventing AI’s harms. Mitchell had at one point tried to save the “Stochastic Parrots” paper by telling executives that publishing it would bolster arguments that the company was capable of self-policing. Quashing it was now undermining those arguments.
Some academics announced that they had backed away from company events or funding. The fairness and technology conference’s organizers stripped Google of its status as a sponsor of the event. Luke Stark, who studies the social impacts of AI at the University of Western Ontario, turned down a $60,000 grant from Google in protest of its treatment of the Ethical AI team. When he applied for the money in December 2020, he had considered the team a “strong example” of how corporate researchers could do powerful work. Now he wanted nothing to do with Google. Tensions built into the field of AI ethics, he saw, were beginning to cause fractures.
“The big tech companies tried to steal a march on regulators and public criticism by embracing the idea of AI ethics,” Stark says. But as the research matured, it raised bigger questions. “Companies became less able to coexist with internal critical research,” he says. One person who runs an ethical AI team at another tech company agrees. “Google and most places did not count on the field becoming what it did.”
To some, the drama at Google suggested that researchers on corporate payrolls should be subject to different rules than those from institutions not seeking to profit from AI. In April, some founding editors of a new journal of AI ethics published a paper calling for industry researchers to disclose who vetted their work and how, and for whistle-blowing mechanisms to be set up inside corporate labs. “We had been trying to poke on this issue already, but when Timnit got fired it catapulted into a more mainstream conversation,” says Savannah Thais, a researcher at Princeton on the journal’s board who contributed to the paper. “Now a lot more people are questioning: Is it possible to do good ethics research in a corporate AI setting?”
If that mindset takes hold, in-house ethical AI research may forever be held in suspicion—much the way industrial research on pollution is viewed by environmental scientists. Jeff Dean admitted in a May interview with CNET that the company had suffered a real “reputational hit” among people interested in AI ethics work. The rest of the interview dealt mainly with promoting Google’s annual developer conference, where it was soon announced that large language models, the subject of Gebru’s fateful critique, would play a more central role in Google search and the company’s voice assistant. Meredith Whittaker, faculty director of New York University’s AI Now Institute, predicts that there will be a clearer split between work done at institutions like her own and work done inside tech companies. “What Google just said to anyone who wants to do this critical research is, ‘We’re not going to tolerate it,’” she says. (Whittaker herself once worked at Google, where she clashed with management over AI ethics and the Maven Pentagon contract before leaving in 2019.)
Any such divide is unlikely to be neat, given how the field of AI ethics sprouted in a tech industry hothouse. The community is still small, and jobs outside big companies are sparser and much less well paid, particularly for candidates without computer science PhDs. That’s in part because AI ethics straddles the established boundaries of academic departments. Government and philanthropic funding is no match for corporate purses, and few institutions can rustle up the data and computing power needed to match work from companies like Google.
For Gebru and her fellow travelers, the past five years have been vertiginous. For a time, the period seemed revolutionary: Tech companies were proactively exploring flaws in AI, their latest moneymaking marvel—a sharp contrast to how they’d faced up to problems like spam and social network moderation only after coming under external pressure. But now it appeared that not much had changed after all, even if many individuals had good intentions.
Inioluwa Deborah Raji, whom Gebru escorted to Black in AI in 2017, and who now works as a fellow at the Mozilla Foundation, says that Google’s treatment of its own researchers demands a permanent shift in perceptions. “There was this hope that some level of self-regulation could have happened at these tech companies,” Raji says. “Everyone’s now aware that the true accountability needs to come from the outside—if you’re on the inside, there’s a limit to how much you can protect people.”
Gebru, who recently returned home after her unexpectedly eventful road trip, has come to a similar conclusion. She’s raising money to launch an independent research institute modeled on her work on Google’s Ethical AI team and her experience in Black in AI. “We need more support for external work so that the choice is not ‘Do I get paid by the DOD or by Google?’” she says.
Gebru has had offers, but she can’t imagine working within the industry anytime in the near future. She’s been thinking back to conversations she’d had with a friend who warned her not to join Google, saying it was harmful to women and impossible to change. Gebru had disagreed, claiming she could nudge things, just a little, toward a more beneficial path. “I kept on arguing with her,” Gebru says. Now, she says, she concedes the point.
