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Timnit Gebru
Timnit Gebru
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Gender shades: Intersectional accuracy disparities in commercial gender classification
J Buolamwini, T Gebru
Conference on fairness, accountability and transparency, 77-91, 2018
69932018
On the dangers of stochastic parrots: Can language models be too big?🦜
EM Bender, T Gebru, A McMillan-Major, S Shmitchell
Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021
54692021
Datasheets for datasets
T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ...
Communications of the ACM 64 (12), 86-92, 2021
25062021
Model cards for model reporting
M Mitchell, S Wu, A Zaldivar, P Barnes, L Vasserman, B Hutchinson, ...
Proceedings of the conference on fairness, accountability, and transparency …, 2019
21992019
Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing
ID Raji, A Smart, RN White, M Mitchell, T Gebru, B Hutchinson, ...
Proceedings of the 2020 conference on fairness, accountability, and …, 2020
8702020
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, 2017
5892017
Saving face: Investigating the ethical concerns of facial recognition auditing
ID Raji, T Gebru, M Mitchell, J Buolamwini, J Lee, E Denton
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 145-151, 2020
4052020
Lessons from archives: Strategies for collecting sociocultural data in machine learning
ES Jo, T Gebru
Proceedings of the 2020 conference on fairness, accountability, and …, 2020
4052020
Race and gender
T Gebru
The Oxford handbook of ethics of AI, 251-269, 2020
2132020
Fine-grained recognition in the wild: A multi-task domain adaptation approach
T Gebru, J Hoffman, L Fei-Fei
Proceedings of the IEEE international conference on computer vision, 1349-1358, 2017
1932017
Learning features and parts for fine-grained recognition
J Krause, T Gebru, J Deng, LJ Li, L Fei-Fei
2014 22nd International conference on pattern recognition, 26-33, 2014
1572014
AI Art and its Impact on Artists
HH Jiang, L Brown, J Cheng, M Khan, A Gupta, D Workman, A Hanna, ...
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 363-374, 2023
1532023
Fine-grained car detection for visual census estimation
T Gebru, J Krause, Y Wang, D Chen, J Deng, L Fei-Fei
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
1352017
Diversity and inclusion metrics in subset selection
M Mitchell, D Baker, N Moorosi, E Denton, B Hutchinson, A Hanna, ...
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 117-123, 2020
1192020
iCassava 2019 fine-grained visual categorization challenge
E Mwebaze, T Gebru, A Frome, S Nsumba, J Tusubira
arXiv preprint arXiv:1908.02900, 2019
822019
Detecting bias with generative counterfactual face attribute augmentation
E Denton, B Hutchinson, M Mitchell, T Gebru, A Zaldivar
arXiv preprint arXiv:1906.06439 2 (5), 7, 2019
772019
FAccT'21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
EM Bender, T Gebru, A McMillan-Major, S Shmitchell
Association for Computing Machinery 2021, 610-623, 2021
642021
Proceedings of the 1st Conference on Fairness, Accountability and Transparency
J Buolamwini, T Gebru, SA Friedler, C Wilson
Proceedings of Machine Learning Research 81, 77-91, 2018
612018
Oxford handbook on AI ethics book chapter on race and gender
T Gebru
arXiv preprint arXiv:1908.06165, 2019
572019
Image counterfactual sensitivity analysis for detecting unintended bias
R Denton, B Hutchinson, M Mitchell, T Gebru, A Zaldivar
arXiv preprint arXiv:1906.06439, 2019
482019
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