REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets A Wang, A Narayanan, O Russakovsky European Conference on Computer Vision, 733-751, 2020 | 194 | 2020 |
Learning Robotic Manipulation through Visual Planning and Acting A Wang, T Kurutach, K Liu, P Abbeel, A Tamar Robotics: Science and Systems (RSS), 2019 | 158 | 2019 |
Understanding and Evaluating Racial Biases in Image Captioning D Zhao, A Wang, O Russakovsky International Conference on Computer Vision (ICCV), 2021 | 135 | 2021 |
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation A Wang, VV Ramaswamy, O Russakovsky ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022 | 99 | 2022 |
Directional Bias Amplification A Wang, O Russakovsky International Conference on Machine Learning (ICML), 2021 | 70 | 2021 |
Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy A Wang, S Kapoor, S Barocas, A Narayanan ACM Conference on Fairness, Accountability, and Transparency, 2023 | 66 | 2023 |
Measuring Representational Harms in Image Captioning A Wang, S Barocas, K Laird, H Wallach ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022 | 51 | 2022 |
Safer Classification By Synthesis W Wang, A Wang, A Tamar, X Chen, P Abbeel NeurIPS 2017 Workshop on Aligned Artificial Intelligence, 2017 | 46 | 2017 |
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging J Katzman, A Wang, M Scheuerman, SL Blodgett, K Laird, H Wallach, ... Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 | 37 | 2023 |
Overwriting Pretrained Bias with Finetuning Data A Wang, O Russakovsky Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 36* | 2023 |
The Limits of Global Inclusion in AI Development A Chan, CT Okolo, Z Terner, A Wang AAAI 2021 Workshop on Reframing Diversity in AI, 2021 | 31 | 2021 |
Measuring Implicit Bias in Explicitly Unbiased Large Language Models X Bai, A Wang, I Sucholutsky, TL Griffiths arXiv preprint arXiv:2402.04105, 2024 | 30 | 2024 |
Manipulative tactics are the norm in political emails: Evidence from 100K emails from the 2020 US election cycle A Mathur, A Wang, C Schwemmer, M Hamin, BM Stewart, A Narayanan Big Data & Society, 2023 | 30 | 2023 |
Gender artifacts in visual datasets N Meister, D Zhao, A Wang, VV Ramaswamy, R Fong, O Russakovsky Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 28 | 2023 |
Large language models cannot replace human participants because they cannot portray identity groups A Wang, J Morgenstern, JP Dickerson arXiv preprint arXiv:2402.01908, 2024 | 26 | 2024 |
Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways A Wang, X Bai, S Barocas, SL Blodgett arXiv preprint arXiv:2402.04420, 2024 | 4* | 2024 |
Strategies for Increasing Corporate Responsible AI Prioritization A Wang, T Datta, JP Dickerson arXiv preprint arXiv:2405.03855, 2024 | 2 | 2024 |
Visions of a Discipline: Analyzing Introductory AI Courses on YouTube S Engelmann, MZ Choksi, A Wang, C Fiesler The 2024 ACM Conference on Fairness, Accountability, and Transparency, 2400-2420, 2024 | 1 | 2024 |
Evaluating Generative AI Systems is a Social Science Measurement Challenge H Wallach, M Desai, N Pangakis, AF Cooper, A Wang, S Barocas, ... arXiv preprint arXiv:2411.10939, 2024 | | 2024 |
Benchmark suites instead of leaderboards for evaluating AI fairness A Wang, A Hertzmann, O Russakovsky Patterns 5 (11), 2024 | | 2024 |