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Author Information
Timnit Gebru (Black in AI)
Timnit Gebru was recently fired by Google for raising issues of discrimination in the workplace. Prior to that she was a co-lead of the Ethical AI research team at Google Brain. She received her PhD from the Stanford Artificial Intelligence Laboratory, studying computer vision under Fei-Fei Li, and did a postdoc at Microsoft Research, New York City in the FATE (Fairness Accountability Transparency and Ethics in AI) group, where she studied algorithmic bias and the ethical implications underlying projects aiming to gain insights from data. Timnit also co-founded Black in AI, a nonprofit that works to increase the presence, inclusion, visibility and health of Black people in the field of AI.
Emily Denton (Google)
Emily Denton is a Research Scientist at Google where they examine the societal impacts of AI technology. Their recent research centers on critically examining the norms, values, and work practices that structure the development and use of machine learning datasets. Prior to joining Google, Emily received their PhD in machine learning from the Courant Institute of Mathematical Sciences at New York University, where they focused on unsupervised learning and generative modeling of images and video.
More from the Same Authors
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2021 : Constructing a Visual Dataset to Study the Effects of Spatial Apartheid in South Africa »
Raesetje Sefala · Timnit Gebru · Luzango Mfupe · Nyalleng Moorosi · Richard Klein -
2021 : Whose ground truth? Challenging the mythical objective, neutral standpoint »
Emily Denton -
2021 Tutorial: Beyond Fairness in Machine Learning »
Timnit Gebru · Emily Denton -
2021 : Machine learning in practice: Who is benefiting? Who is being harmed? »
Timnit Gebru -
2020 : Strategies for anticipating and mitigating risks »
Ashley Casovan · Timnit Gebru · Shakir Mohamed · Solon Barocas · Aviv Ovadya -
2020 : Panel 1: Tensions & Cultivating Resistance AI »
Abeba Birhane · Timnit Gebru · Noopur Raval · Ramon Vilarino -
2018 : Bias and fairness in AI »
Timnit Gebru · Margaret Mitchell · Brittny-Jade E Saunders -
2017 Workshop: Learning Disentangled Features: from Perception to Control »
Emily Denton · Siddharth Narayanaswamy · Tejas Kulkarni · Honglak Lee · Diane Bouchacourt · Josh Tenenbaum · David Pfau -
2017 : Invited Talk »
Emily Denton -
2017 Poster: Unsupervised Learning of Disentangled Representations from Video »
Emily Denton · vighnesh Birodkar -
2017 Spotlight: Unsupervised Learning of Disentangled Representations from Video »
Emily Denton · vighnesh Birodkar -
2016 : Discussion panel »
Ian Goodfellow · Soumith Chintala · Arthur Gretton · Sebastian Nowozin · Aaron Courville · Yann LeCun · Emily Denton -
2015 Poster: Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks »
Emily Denton · Soumith Chintala · arthur szlam · Rob Fergus -
2014 Poster: Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation »
Emily Denton · Wojciech Zaremba · Joan Bruna · Yann LeCun · Rob Fergus