8 citations · 16 across the 13 of their papers we have counts for
12 papers · 1 filter
Who Does What in AI Auditing? Designing Human-AI Collaboration for Auditing Generative AI
Eunkyu Park, Markelle Roesti, Wesley Hanwen Deng +5
AI auditing increasingly incorporates AI agents to expand the scale and breadth of audit coverage, yet little is known about how auditing work should be divided without displacing…
Use and Effects of LLMs in Peer Review: A Randomized Experiment and Survey at ICML 2026
Sunnie S. Y. Kim, Wesley Hanwen Deng, Jennifer Wortman Vaughan +8
LLMs are rapidly reshaping peer review, making it important to understand how reviewers use them in practice and how different LLM-use policies affect review outcomes. We investiga…
What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research
Wesley Hanwen Deng, Agathe Balayn, Andrew Selbst +6
Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implement, and sustain RAI work direct…
PersonaTeaming: Supporting Persona-Driven Red-Teaming for Generative AI
Wesley Hanwen Deng, Mingxi Yan, Sunnie S. Y. Kim +5
Recent developments in AI safety research have called for red-teaming methods that effectively surface potential risks posed by generative AI models, with growing emphasis on how r…
Seeing Twice: How Side-by-Side T2I Comparison Changes Auditing Strategies
Matheus Kunzler Maldaner, Wesley Hanwen Deng, Jason I. Hong +2
While generative AI systems have gained popularity in diverse applications, their potential to produce harmful outputs limits their trustworthiness and utility. A small but growing…
"I Don't Think RAI Applies to My Model'' -- Engaging Non-champions with Sticky Stories for Responsible AI Work
Nadia Nahar, Chenyang Yang, Yanxin Chen +4
Responsible AI (RAI) tools -- checklists, templates, and governance processes -- often engage RAI champions, individuals intrinsically motivated to advocate ethical practices, but…