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  1. en.wikipedia.org › wiki › Timnit_GebruTimnit Gebru - Wikipedia

    Timnit Gebru (Amharic and Tigrinya: ትምኒት ገብሩ; 1982/1983) is an Eritrean Ethiopian-born computer scientist who works in the fields of artificial intelligence (AI), algorithmic bias and data mining. She is an advocate for diversity in technology and co-founder of Black in AI, a community of Black researchers working in AI.

  2. Timnit Gebru ist eine Informatikerin, die auf dem Gebiet der künstlichen Intelligenz forscht. Bis Anfang Dezember 2020 war sie Co-Leiterin der Abteilung für Ethik in der KI bei dem US-amerikanischen Technologieunternehmen Google. Sie ist Mitgründerin des Distributed AI Research Institute.

  3. Timnit Gebru is a leading researcher and activist in the field of ethical AI and algorithmic bias. She is the founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR), and a co-founder of Black in AI and AddisCoder.

  4. 4. Dez. 2020 · Timnit Gebru, co-lead of Google's ethical AI team, was forced out after challenging the company's large language models. The paper she coauthored highlighted the environmental, financial, and social costs of these AI systems.

    • Karen Hao
  5. Proceedings of the 2020 conference on fairness, accountability, and …. , 2020. 704. 2020. Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States. T Gebru, J Krause, Y Wang, D Chen, J Deng, EL Aiden, L Fei-Fei. Proceedings of the National Academy of Sciences 114 (50), 13108-13113.

  6. Timnit Gebru is the founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR), a nonprofit organization that aims to advance ethical and inclusive AI. She is also a researcher and lecturer at Stanford University, and a frequent critic of biased and harmful AI applications.

    • The Distributed AI Research Institute (DAIR)
  7. Timnit Gebru is a research scientist at Google in the ethical AI team. She studies algorithmic bias, fairness, transparency and accountability in AI, and has a PhD from Stanford in computer vision.