collaborators

12 papers

cs.HC2026

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…

cs.CY2026

"Death by a thousand taxonomies?": AI Risk Classification In Practice

Glen Berman, Ned Cooper, Angel Hsing-Chi Hwang +3

The harms in which AI is implicated range in nature and scope from unsafe user interactions through to the societal-wide consequences of AI adoption. Classification of the diverse…

cs.HC2026

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…

cs.CV2026

MM-SCALE: Grounded Multimodal Moral Reasoning via Scalar Judgment and Listwise Alignment

Eunkyu Park, Wesley Hanwen Deng, Cheyon Jin +8

Vision-Language Models (VLMs) continue to struggle to make morally salient judgments in multimodal and socially ambiguous contexts. Prior works typically rely on binary or pairwise…

cs.HC2025

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…

cs.AI2025

PersonaTeaming: Exploring How Introducing Personas Can Improve Automated AI Red-Teaming

Wesley Hanwen Deng, Sunnie S. Y. Kim, Akshita Jha +4

Recent developments in AI governance and safety research have called for red-teaming methods that can effectively surface potential risks posed by AI models. Many of these calls ha…