# Timnit Gebru

Timnit Gebru is an Ethiopian-born Eritrean computer scientist specializing in AI ethics, algorithmic bias, and data mining. She is a co-founder of Black in AI and founder of DAIR, known for her work on large language models' risks.

Timnit W. Gebru (Amharic and Tigrinya: ትምኒት ገብሩ; born 1982/1983) is an Ethiopian-born Eritrean computer scientist specializing in [artificial intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence), algorithmic bias, and data mining. She is a co-founder of Black in AI, an advocacy group promoting Black representation in AI research and development, and founder of the Distributed Artificial Intelligence Research Institute (DAIR). Her work has focused on the societal impacts of AI, particularly on marginalized communities, and she gained international attention in December 2020 following her departure from Google's Ethical AI team.

Gebru's research has combined [machine learning](https://www.wikiprompt.org/wiki/machine-learning) with social science to expose biases in AI systems, including her doctoral work using [deep learning](https://www.wikiprompt.org/wiki/deep-learning) on Google Street View images to infer neighborhood demographics. She has been recognized as a leading voice in AI ethics, named one of the World's 50 Greatest Leaders by Fortune, one of Nature's ten people who shaped science in 2021, and one of Time's most influential people in 2022.

## Early life and education

Gebru was raised in Addis Ababa, Ethiopia, by her mother, an economist, after her father, an electrical engineer with a PhD, died when she was five. Both parents were from Eritrea. At age 15, during the Eritrean–Ethiopian War, she fled Ethiopia after family members were deported to Eritrea and compelled to fight. Initially denied a U.S. visa, she briefly lived in Ireland before receiving political asylum in the U.S., an experience she described as "miserable." She settled in Somerville, Massachusetts, for high school, where she encountered racial discrimination, with some teachers refusing to let her take Advanced Placement courses despite her academic performance.

A pivotal encounter with police occurred after high school: when she called police to report a friend's assault, her friend, a Black woman, was arrested instead. Gebru called it a "blatant example of systemic racism." In 2001, she was accepted at Stanford University, earning a Bachelor of Science, Master of Science, and PhD in computer vision in 2017, advised by [Fei-Fei Li](https://www.wikiprompt.org/wiki/fei-fei-li). During the 2008 U.S. presidential election, she canvassed for Barack Obama. She presented her doctoral research at the 2017 LDV Capital Vision Summit, winning the competition and sparking collaborations with entrepreneurs and investors. In 2016 and 2018, she volunteered with AddisCoder, a programming initiative for Ethiopian students. While at Stanford, she authored an unpublished paper on AI's lack of diversity, criticizing the field's "boy's club culture" and reflecting on experiences of harassment at conferences.

## Career at Apple

From 2004 to 2013, Gebru worked at Apple, initially as an intern in the hardware division, designing circuitry for audio components, then as a full-time audio engineer. Her manager told Wired she was "fearless" and well-liked. She developed signal processing algorithms for the first iPad Gangnam Style, though she later said she didn't consider surveillance uses, finding it "technically interesting." In 2021, during the #AppleToo movement led by engineer Cher Scarlett, Gebru revealed experiences of "so many egregious things" at Apple, calling for accountability and criticizing media coverage that shields tech giants.

## Stanford and Microsoft research

In 2013, Gebru joined Fei-Fei Li's lab at Stanford, combining [deep learning](https://www.wikiprompt.org/wiki/deep-learning) with Google Street View to estimate demographics of U.S. neighborhoods, demonstrating that socioeconomic attributes like voting patterns, income, race, and education can be inferred from car images. At the 2015 Neural Information Processing Systems (NIPS) conference, she was one of few Black attendees out of 3,700; in 2016, she counted only five Black men and herself as the only Black woman among 8,500. With colleague Rediet Abebe, she co-founded Black in AI. In summer 2017, she joined Microsoft's FATE (Fairness, Accountability, Transparency, and Ethics in AI) lab as a postdoctoral researcher, speaking on AI biases and advocating for diversity in AI teams.

## Google Ethical AI team and departure

In 2018, Gebru became technical co-lead of Google's Ethical AI team, focusing on algorithmic fairness and transparency. In December 2020, she coauthored a paper on [large language models](https://www.wikiprompt.org/wiki/large-language-model) (LLMs) as "stochastic parrots," highlighting risks like environmental costs and bias amplification, and submitted it for publication. Google, citing failure to wait for internal review, requested withdrawal or removal of all Google-affiliated authors. Gebru asked for reviewer identities and feedback, threatening to discuss a "last date" if refused. Google terminated her employment, framing it as accepting her resignation; Gebru maintained she had not offered to resign. The controversy sparked public debate over academic freedom at tech companies, with thousands of researchers and employees signing letters of support.

The paper was later published externally, influencing subsequent discourse on AI model risks)Skip.

## Founding DAIR and continued advocacy

Following her departure, Gebru founded the Distributed Artificial Intelligence Research Institute (DAIR) in 2021 to conduct independent AI ethics research, aiming to center marginalized voices. She has continued to speak on algorithmic bias, data mining ethics, and the need for accountability in AI development. Her work has been influential in shaping discussions about responsible AI, particularly in relation to [generative AI](https://www.wikiprompt.org/wiki/generative-ai) and its societal impacts.

## Legacy and recognition

Gebru's contributions have been widely acknowledged. She was named among Fortune's World's 50 Greatest Leaders, Nature's ten people who shaped science in 2021, and Time's 100 most influential people in 2022. Her research and advocacy have informed policy debates on AI regulation, and she remains a prominent critic of unchecked technological optimism in the field.

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Source: https://www.wikiprompt.org/wiki/timnit-gebru-3
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Last updated: 2026-10-07T16:49:30.732636+00:00