Jessica Dai

According to our database, Jessica Dai authored at least 11 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms.

Jessica Dai, Paula Gradu, Inioluwa Deborah Raji, Benjamin Recht

CoRR, February, 2025

2024

Learning With Multi-Group Guarantees For Clusterable Subpopulations.

Jessica Dai, Nika Haghtalab, Eric Zhao

CoRR, 2024

Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis.

Jessica Dai

CoRR, 2024

Mapping Social Choice Theory to RLHF.

Jessica Dai, Eve Fleisig

CoRR, 2024

Position: Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis.

Jessica Dai

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Can Probabilistic Feedback Drive User Impacts in Online Platforms?

Jessica Dai, Bailey Flanigan, Meena Jagadeesan, Nika Haghtalab, Chara Podimata

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments.

Jessica Dai, Paula Gradu, Christopher Harshaw

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Achieving Downstream Fairness with Geometric Repair.

Kweku Kwegyir-Aggrey, Jessica Dai, John P. Dickerson, Keegan Hines

CoRR, 2022

Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations.

Jessica Dai, Sohini Upadhyay, Ulrich Aïvodji, Stephen H. Bach, Himabindu Lakkaraju

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

What will it take to generate fairness-preserving explanations?

Jessica Dai, Sohini Upadhyay, Stephen H. Bach, Himabindu Lakkaraju

CoRR, 2021

Fair Machine Learning Under Partial Compliance.

Jessica Dai, Sina Fazelpour, Zachary C. Lipton

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021