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Jessica Dai

7 accepted papers

2026

Position: Mechanisms for Aggregated Individual Reporting Should be Established for Post-Deployment Evaluation

ICML 2026poster

The need for developing model evaluations beyond static benchmarking, especially in the post-deployment phase, is now well-understood. At the same time, concerns about the concentration of power in deployed AI systems have sparked a keen interest in "democratic" or "public" AI. In this work, we brin…

Cited by 0SourceScholar
2026

Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data

ICML 2026poster

ChatGPT was launched on November 30, 2022; the r/ChatGPT subreddit was created just one day later. Since then, chatbot-based AI products have gone from niche proofs-of-concept to widely-used household names. However, the ways in which adoption has developed, especially among non-experts, remains poo…

Cited by 0SourceScholar
2025

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

ICML 2025poster

When an individual reports a negative interaction with some system, how can their personal experience be contextualized within broader patterns of system behavior? We study the *reporting database* problem, where individual reports of adverse events arrive sequentially, and are aggregated over time.…

2024

Can Probabilistic Feedback Drive User Impacts in Online Platforms?

AISTATS 2024poster

A common explanation for negative user impacts of content recommender systems is misalignment between the platform’s objective and user welfare. In this work, we show that misalignment in the platform’s objective is not the only potential cause of unintended impacts on users: even when the platform’…

Cited by 8SourcePDFScholar
2024

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

ICML 2024oral

What is *agency,* and why does it matter? In this work, we draw from the political science and philosophy literature and give two competing visions of what it means to be an (ethical) agent. The first view, which we term *mechanistic*, is commonly— and implicitly—assumed in AI research, yet it is a…

Cited by 2SourcePDFScholar
2023

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

NeurIPS 2023spotlight

From clinical development of cancer therapies to investigations into partisan bias, adaptive sequential designs have become increasingly popular method for causal inference, as they offer the possibility of improved precision over their non-adaptive counterparts. However, even in simple settings (e.…