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Inioluwa Deborah Raji
Inioluwa Deborah Raji
Fellow, Mozilla Foundation
Verified email at mozillafoundation.org
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Cited by
Year
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
17672019
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
7072020
Actionable auditing: Investigating the impact of publicly naming biased performance results of commercial ai products
ID Raji, J Buolamwini
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 429-435, 2019
5612019
Data and its (dis) contents: A survey of dataset development and use in machine learning research
A Paullada, ID Raji, EM Bender, E Denton, A Hanna
Patterns 2 (11), 2021
5022021
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 2020 AAAI/ACM Conference on AI, Ethics, and Society, 145-151, 2020
3412020
AI Now 2019 Report
K Crawford, R Dobbe, T Dryer, G Fried, B Green, E Kaziunas, A Kak, ...
289*2019
AI and the Everything in the Whole Wide World Benchmark
ID Raji, EM Bender, A Paullada, E Denton, A Hanna
Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021
2022021
The fallacy of AI functionality
ID Raji, IE Kumar, A Horowitz, A Selbst
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
1412022
You can't sit with us: Exclusionary pedagogy in ai ethics education
ID Raji, MK Scheuerman, R Amironesei
Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021
1042021
Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem
S Costanza-Chock, ID Raji, J Buolamwini
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
952022
Are we learning yet? a meta review of evaluation failures across machine learning
T Liao, R Taori, ID Raji, L Schmidt
Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021
872021
About face: A survey of facial recognition evaluation
ID Raji, G Fried
AAAI 2020 Workshop on AI Evaluation, 2021
752021
On the legal compatibility of fairness definitions
A Xiang, ID Raji
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural …, 2019
622019
Outsider oversight: Designing a third party audit ecosystem for ai governance
ID Raji, P Xu, C Honigsberg, D Ho
Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 557-571, 2022
572022
Participatory approaches to machine learning
B Kulynych, D Madras, S Milli, ID Raji, A Zhou, R Zemel
International Conference on Machine Learning Workshop 7, 2020
382020
About ml: Annotation and benchmarking on understanding and transparency of machine learning lifecycles
ID Raji, J Yang
Human-Centric Machine Learning workshop at Neural Information Processing …, 2019
372019
Fake ai
F Kaltheuner
Meatspace press, 2021
292021
Actionable auditing revisited: Investigating the impact of publicly naming biased performance results of commercial ai products
ID Raji, J Buolamwini
Communications of the ACM 66 (1), 101-108, 2022
212022
Organizational governance of emerging technologies: AI adoption in healthcare
JY Kim, W Boag, F Gulamali, A Hasan, HDJ Hogg, M Lifson, D Mulligan, ...
proceedings of the 2023 ACM conference on fairness, accountability, and …, 2023
162023
Ai regulation has its own alignment problem: The technical and institutional feasibility of disclosure, registration, licensing, and auditing
N Guha, C Lawrence, LA Gailmard, K Rodolfa, F Surani, R Bommasani, ...
George Washington Law Review, Forthcoming, 2023
122023
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