Deep Unlearning
The Rise of AI and the Radicalization of a Tech Idealist
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Deep Unlearning
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Timnit Gebru
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Timnit Gebru
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Timnit Gebru
Timnit Gebru has been present at nearly every inflection point in tech’s recent history. She was an engineer at Apple on the cusp of the iPhone’s first release, a PhD student at Stanford’s computer vision lab as her advisor worked on the enormous datasets so crucial to AI’s development, and the most senior Black woman on the Ethical AI team at Google as DeepMind and Open AI took over the field of artificial intelligence—where she was forced out for having raised the alarm about bias in large language models, causing global shockwaves in the tech industry.
Starting with her childhood during which she was forced to flee the 1998 Ethiopian-Eritrean war, through the fraught process of achieving refugee status, Gebru shows how her early love of science and math was inextricably intertwined with her belief that these were reliably objective safe spaces. Over time, through high school in Greater Boston, college at Stanford, and jobs at Apple, Microsoft, and Google, she came to realize that perhaps some of the biases and injustices she witnessed in her life outside of academics were true about technology, too.
Over the course of her life, Gebru has seen up close how the destructive ideologies and outsized egos of the tech world have come to wreak havoc on our environment, our economies, and the lives of billions of people. She has also come to understand how we could have made a different choice every step of the way, and how we still can.
Part memoir and part manifesto, Deep Unlearning is as much about ideology as it is about technology—and about how to guarantee justice in both.
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