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Timnit Gebru

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Timnit Gebru
Gebru in 2018
Gebru in 2018
Born
Addis Ababa, Ethiopia
Alma materStanford University
Known forAlgorithmic bias
Scientific career
InstitutionsMicrosoft Research
Google
Apple

Timnit Gebru is a computer scientist who works on algorithmic bias and data mining. She is an advocate for diversity in technology and a co-founder of Black in AI, a community of black researchers working in artificial intelligence. Her employment with Google as technical co-lead of the Ethical Artificial Intelligence Team was abruptly ended in December 2020 after she was forced to retract an academic paper.[1][2][3][4][5][6][7][excessive citations]

Early life and education

Gebru was born and raised in Addis Ababa, Ethiopia.[8] Her father and two oldest sisters are electrical engineers.[9] Her father died when she was five years old and she was raised by her mother.[10] Her mother and father originated from Eritrea. She escaped potential forced deportation to Eritrea by the Ethiopian government in the late 1990s and traveled to Ireland. She then moved to the United States to join her mother (who also fled from Ethiopia few months prior) and her two older sisters who had been living in the U.S. Gebru is the youngest of three.[citation needed]

After completing high school in Massachusetts, she was accepted to study at Stanford University.[8] There she earned her Bachelor's and Master's degrees in electrical engineering.[11] Gebru worked at Apple Inc., developing signal processing algorithms for the first iPad.[12] Gebru earned her doctorate under the supervision of Fei-Fei Li at Stanford University in 2017. She used data mining of publicly available images.[13] She was interested in the amount of money spent by governmental and non-governmental organisations trying to collect information about communities.[14] 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.[11] If the number of pickup trucks outnumbers the number of sedans, the community are more likely to vote for the Republican party.[15] They analysed over 15 million images from the 200 most populated US cities.[16] The work was extensively covered in the media, being picked up by BBC News, Newsweek, The Economist, and The New York Times.[17][18][19]

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.[20] Gebru won the competition, starting a series of collaborations with other entrepreneurs and investors.[20] Both during her PhD in 2016 and in 2018, Gebru returned to Ethiopia with Jelani Nelson's programming campaign AddisCoder.[21][22] After her PhD, Gebru joined Microsoft as a postdoctoral researcher in the Fairness, Accountability, Transparency and Ethics in AI (FATE) lab.[16][23]

Career and research

Gebru discussing her findings that one can predict, with some reliability, the way an American will vote from the type of vehicle they drive.

Gebru worked at Google on the ethics of artificial intelligence. She studied the implications of artificial intelligence, looking to improve the ability of technology to do social good.[24] She collaborated with the MIT research group Gender Shades.[25] Gebru worked with Joy Buolamwini to investigate facial recognition software; finding that black women were 35% less likely to be recognised than white men.[26] When Gebru attended an artificial intelligence conference in 2016, she noticed that she was the only black woman out of 8,500 delegates.[27] 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.[citation needed] She has discussed bias in artificial intelligence in podcasts and interviews.[28][29]

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.[30] 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 more trouble identifying darker-skinned females than any other technology company's facial recognition software.[31] In a New York Times interview, Gebru has further expressed that she believes facial recognition is too dangerous to be used for law enforcement and security purposes right now.[32]

Exit from Google

In December 2020, Gebru announced that she had been fired by Google after an alleged dispute over a research paper. Google workers started the #ISupportTimnit campaign to stand in solidarity with Gebru. Jeff Dean, Google’s head of AI research, maintains that she resigned voluntarily, though this was disputed by current and former Google employees.[33][34][35]

Awards

Gebru, Joy Buolamwini, and Inioluwa Raji won VentureBeat's 2019 AI Innovations Award in the category AI for Good for their research highlighting the significant problem of algorithmic bias in facial recognition.[36][37]

Selected publications

  • Gebru, Timnit; Krause, Jonathan; Wang, Yilun; Chen, Duyun; Deng, Jia; Aiden, Erez Lieberman; Fei-Fei, Li (12 December 2017). "Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States". Proceedings of the National Academy of Sciences. 114 (50): 13108–13113. doi:10.1073/pnas.1700035114. ISSN 0027-8424. PMC 5740675. PMID 29183967.
  • Buolamwini, Joy; Gebru, Timnit (2018). "Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification". Proceedings of Machine Learning Research. 81: 1–15. ISSN 1938-7288.
  • Gebru, Timnit (9 July 2020). "Race and Gender". In Dubber, Markus D.; Pasquale, Frank; Das, Sunit (eds.). The Oxford Handbook of Ethics of AI. Oxford University Press. pp. 251–269. doi:10.1093/oxfordhb/9780190067397.013.16. ISBN 978-0-19-006739-7.

References

  1. ^ "Top AI ethics researcher says Google fired her; company denies it". Reuters. Archived from the original on 5 December 2020. Retrieved 4 December 2020.
  2. ^ "Timnit Gebru: Google staff rally behind fired AI researcher". BBC. Archived from the original on 4 December 2020. Retrieved 4 December 2020.
  3. ^ "Google fires prominent AI ethicist Timnit Gebru". The Verge. Archived from the original on 3 December 2020. Retrieved 4 December 2020.
  4. ^ "Google's co-lead of Ethical AI team says she was fired for sending an email". TechCrunch. Archived from the original on 4 December 2020. Retrieved 4 December 2020.
  5. ^ "Renowned AI researcher says Google abruptly fired her, spurring industrywide criticism of the company". CNBC. Archived from the original on 4 December 2020. Retrieved 4 December 2020.
  6. ^ Langley, Hugh (3 December 2020). "One of Google's leading AI researchers says she's been fired in retaliation for an email to other employees". Business Insider. Archived from the original on 5 December 2020. Retrieved 3 December 2020.
  7. ^ "Timnit Gebru: Google staff rally behind fired AI researcher". MIT Technology Review. Retrieved 5 December 2020.
  8. ^ a b Lahde, Lisa. "AI Innovators: How One Woman Followed Her Passion and Brought Diversity to AI". Forbes. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  9. ^ "Final | Timnit Gebru". Campaign | 1 million women in STEM. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  10. ^ Chisling, Ava (24 July 2017). "Excuse me, sir, but where are all the women?". ROSS Intelligence. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  11. ^ a b AI, People In (16 September 2017). "Timnit Gebru honored as an Alicorn of Artificial Intelligence by People in AI". Selfpreneur. Archived from the original on 5 December 2020. Retrieved 9 January 2019.
  12. ^ "Timnit Gebru". Databricks. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  13. ^ "Understanding the Limits of AI: When Algorithms Fail". MIT Tech Review. Archived from the original on 5 December 2020. Retrieved 9 January 2019.
  14. ^ Capital, L. D. V. (1 August 2017), Timnit Gebru - 2017 Entrepreneurial Computer Vision Challenge Finalist Presentations, archived from the original on 5 December 2020, retrieved 9 January 2019
  15. ^ Fei-Fei, Li; Aiden, Erez Lieberman; Deng, Jia; Chen, Duyun; Wang, Yilun; Krause, Jonathan; Gebru, Timnit (12 December 2017). "Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States". Proceedings of the National Academy of Sciences. 114 (50): 13108–13113. doi:10.1073/pnas.1700035114. ISSN 1091-6490. PMC 5740675. PMID 29183967.
  16. ^ a b "Timnit Gebru". Design Better. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  17. ^ Lufkin, Bryan (6 January 2018). "What Google Street View tells us about income". Worklife. BBC. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  18. ^ "A machine-learning census of America's cities". The Economist. 2 March 2017. ISSN 0013-0613. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  19. ^ Lohr, Steve (31 December 2017). "How Do You Vote? 50 Million Google Images Give a Clue". The New York Times. ISSN 0362-4331. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  20. ^ a b "Timnit Gebru Wins 2017 ECVC: Leveraging Computer Vision to Predict Race, Education and Income via Google Streetview Images". LDV Capital. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  21. ^ Magazine, Tadias. "Timnit Gebru: Among Incredible Women Advancing A.I. Research at Tadias Magazine". Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  22. ^ "History | AddisCoder". www.addiscoder.com. Archived from the original on 21 March 2018. Retrieved 10 January 2019.
  23. ^ "Timnit Gebru". World Science Festival. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  24. ^ University, Office of Web Communications, Cornell. "Digital Life Seminar | Timnit Gebru". Cornell. Archived from the original on 10 January 2019. Retrieved 9 January 2019.{{cite web}}: CS1 maint: multiple names: authors list (link)
  25. ^ "Team". MIT Media Lab. Archived from the original on 25 July 2019. Retrieved 9 January 2019.
  26. ^ Lohr, Steve (9 February 2018). "Facial Recognition Is Accurate, if You're a White Guy". The New York Times. ISSN 0362-4331. Archived from the original on 9 January 2019. Retrieved 9 January 2019.
  27. ^ Birhaner, De (26 May 2017). "Ethiopian Ms. Timnit Gebru Fights Algorithmic Bias And Homogenous Thinking in A.I." De Birhan. Archived from the original on 23 October 2018. Retrieved 9 January 2019.
  28. ^ "Facial Recognition, Demographic Analysis and More with Timnit Gebru". Georgian Partners. 20 December 2018. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  29. ^ "3 Ways to Counter Unconscious Bias in AI". Salesforce Blog. Archived from the original on 10 January 2019. Retrieved 9 January 2019.
  30. ^ Mitchell, Margaret; Wu, Simone; Zaldivar, Andrew; Barnes, Parker; Vasserman, Lucy; Hutchinson, Ben; Spitzer, Elena; Raji, Inioluwa Deborah; Gebru, Timnit (2019). "Model Cards for Model Reporting". Proceedings of the Conference on Fairness, Accountability, and Transparency - FAT* '19. New York, New York, USA: ACM Press: 220–229. arXiv:1810.03993. doi:10.1145/3287560.3287596. ISBN 978-1-4503-6125-5. S2CID 52946140.
  31. ^ Mitchell, Andrea (April 2019). "A.I. Experts Question Amazons Facial-Recognition Technology". ICT Monitor Worldwide; Amman. Archived from the original on 26 November 2019.
  32. ^ Ovide, Shira (9 June 2020). "A Case for Banning Facial Recognition". The New York Times. ISSN 0362-4331. Archived from the original on 17 July 2020. Retrieved 12 July 2020.
  33. ^ "Google workers mobilize against firing of top Black female executive". NBC News. Archived from the original on 5 December 2020. Retrieved 5 December 2020.
  34. ^ "Timnit Gebru: Google staff rally behind fired AI researcher". MIT Technology Review. Retrieved 5 December 2020.
  35. ^ Ghaffary, Shirin (4 December 2020). "The controversy behind a star Google AI researcher's departure". Vox. Retrieved 6 December 2020.
  36. ^ "AI innovation winners announced in San Francisco". Innovation Matrix. 12 July 2019. Archived from the original on 12 July 2020. Retrieved 12 July 2020.
  37. ^ Jul 18; Burt, 2019 | Chris (18 July 2019). "Buolamwini, Gebru and Raji win AI Innovation Award for research into biometric bias". Biometric Update. Archived from the original on 12 July 2020. Retrieved 12 July 2020.{{cite web}}: CS1 maint: numeric names: authors list (link)
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