Timnit Gebru

Timnit Gebru is anEritrean computer scientist and the technical co-lead of the Ethical Artificial Intelligence Team at Google. She works on algorithmic bias and data mining. She is an advocate for diversity in technology and is the cofounder of Black in AI, a community of black researchers working in artificial intelligence.

Gebru is an Eritrean originborn and raised in Ethiopia. Both her parents are Eritreans.Her father and two oldest sisters are electrical engineers. Her father died when she was five years old and she was raised by her mother. She escaped potential forced deportation to Eritrea by Ethiopian government in the late 1990's and traveled to Ireland.She then immigrated to the United States to join her mother (who also fled from Ethiopia few months prior) and her two older sisters who were living in U.S. Gebru is the youngest of three.After completing her high school in Massachusetts,she was accepted to study at Stanford University. There she earned her Bachelor's and Master's degrees in electrical engineering. Gebru worked at Apple Inc., developing signal processing algorithms for the first IPad. Gebru earned her doctorate under the supervision of Fei-Fei Li at Stanford University in 2017. She used data mining of publicly available images. She was interested in the amount of money spent by governmental and non-governmental organisations trying to collect information about communities. To investigate alternatives, Gebru combined deep learning with Google Street View to estimate the demographics of United States neighbourhoods, showing that socioeconomic attributes such as voting patterns, income, race and education can be inferred from observations of cars. If the number of pickup trucks outnumbers the number of sedans, the community are more likely to vote for the Republican party. They analysed over 15 million images from the 200 most populated US cities. The work was extensively covered in the media, being picked up by BBC News, Newsweek, The Economist and The New York Times.

Gebru presented her research at the 2017 LDV Capital Vision Summit competition, where computer vision scientists present their work to members of industry and venture capitalists. Gebru won the competition, starting a series of collaborations with other entrepreneurs and investors. Both during her PhD in 2016 and in 2018, Gebru returned to Ethiopia with Jelani Nelson's programming campaign AddisCoder. After her PhD, Gebru joined Microsoft as a postdoctoral researcher in the Fairness, Accountability, Transparency and Ethics in AI (FARE) lab. She was honoured by the Selfpreneur as "the Alicorn in Artificial Intelligence".

Gebru works at Google on the ethics of Artificial Intelligence. She studies the implications of artificial intelligence, looking to improve the ability of technology to do social good. She collaborated with the MIT research group Gender Shades. Gebru worked with Joy Buolamwini to investigate facial recognition software; finding that black women were 35% less likely to be recognised than white men. When Gebru attended an artificial intelligence conference in 2016, she noticed that she was the only black woman out of 8,500 delegates. Together with her colleague Rediet Abebe Gebru founded Black in AI, a community of black researchers working in artificial intelligence. Black in AI have held workshops at the Conference on Neural Information Processing Systems annually since 2017. She has discussed bias in artificial intelligence in podcasts and interviews.

Gebru also worked on Microsoft's Fairness, Accountability, Transparency, and Ethics in the AI team. In 2017, Gebru spoke on the Fairness and Transparency conference, where MIT Technology Review interviewed her about biases that exist in AI systems and how adding diversity in AI teams can fix that issue. In her interview with Jackie Snow, Snow asked Gebru, "How does the lack of diversity distort artificial intelligence and specifically computer vision?" and Gebru pointed out that there are biases that exist in the software developers. Gebru and other artificial intelligence researchers signed a letter that reflected the systemic issues that reside in Amazon's facial recognition software. A study that was conducted by MIT researchers shows that Amazon's facial recognition system had trouble identifying darker-skinned females than any other technology companies facial recognition software.

In 2017 Gebru was featured on the Forbes list of incredible women advancing AI research.

In 2017 Gebru was awarded the title "Alicorn of Artificial Intelligence." She was recognized for this award because of her research on using machine learning and deep learning to predict demographic data using Google Street View.