Google AI scientist Bengio resigns after colleagues’ firings


A distinguished scientist at Google, Bengio spent about 14 years at the company and was among its first employees involved in a decade-old project known as Google Brain.

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Google research manager Samy Bengio on Tuesday said he is resigning, according to an internal email seen by Reuters, in a blow to the Alphabet Inc unit after the firings of his colleagues who questioned paper review and diversity practices.

Though at least two Google engineers had earlier resigned in protest of the dismissal of artificial intelligence (AI)researcher Timnit Gebru, Bengio is the highest-profile yet todepart.

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Google and Bengio did not immediately respond to requests for comment. Bloomberg earlier reported the news.

A distinguished scientist at Google, Bengio spent about 14 years at the company and was among its first employees involved in a decade-old project known as Google Brain that advanced algorithms crucial to the functioning of various modern artificial intelligence systems.

In the email he sent internally, Bengio said, “I have decided to leave Google in order to pursue other exciting opportunities.”

Google fired staff scientist Margaret Mitchell in February after alleging she transferred electronic files out of the company. It fired fellow researcher Gebru in December after she threatened to quit rather than retract a paper.

Mitchell has said she tried “to raise concerns about race and gender inequity, and speak up about Google’s problematic firing of Dr. Gebru.” Gebru has said the company wanted to suppress her criticism of its products and its efforts to increase workforce diversity.

Bengio had defended the pair, who co-led a team of about a dozen researching ethical issues related to AI software. In December, Bengio said on Facebook that he was stunned that Gebru, whom he was managing, was removed from the company without his being consulted prior.

He did not mention their firings in his farewell note.

“I learned so much with all of you, in terms of machine learning research of course, but also on how difficult yet important it is to organize a large team of researchers so as to promote long term ambitious research, exploration, rigor,diversity and inclusion,” he said.



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