Google is still firing AI researchers amid criticism of its work. The New York Times has learned Google fired machine learning scientist Satrajit Chatterjee in March, soon after it refused to publish a paper Chatterjee and others wrote challenging earlier findings that computers could design some chip components more effectively than humans. The scientist was reportedly allowed to collaborate on a paper disputing those claims after he and fellow authors expressed reservations, but was dismissed after a resolution committee rejected the paper and the researchers hoped to bring the issue to CEO Sundar Pichai and Alphabet’s board of directors.
The company hasn’t detailed why it fired Chatterjee, but told the Times he’d been “terminated with cause.” It also maintained that the original paper had been “thoroughly vetted” and peer-reviewed, and that the study challenging the claims “did not meet our standards.”
Whether or not the science holds up, the exit underscores the ongoing clash between Google’s management and the AI teams that drive many of its projects. The problems began in earnest when Google fired ethicist Timnit Gebru in 2020 following a dispute over a paper, with two others following suit. The matter escalated when the internet giant terminated Margaret Mitchell in early 2021. While Google claimed Mitchell violated data confidentiality policies, she also publicly criticized executives and the decision to fire Gebru. These firings led veteran engineers to leave the firm and demand reforms, and that’s not including company-wide protests over military contracts. Google investigated Gebru’s firing and promised changes, but the Chatterjee firing might not ease tensions.
It’s no secret that Google is proud of its AI research. It’s keen to tout algorithms that can outperform humans in fields like chip design and cancer detection, and its flagship Pixel 6 phones are built around a custom AI-focused processor. Any flaws could significantly hinder Google’s business, not to mention tarnish its reputation as a leader in AI development.
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