5 papers
AI Organizations are More Effective but Less Aligned than Individual Agents
Judy Hanwen Shen, Daniel Zhu, Siddarth Srinivasan +5
AI is increasingly deployed in multi-agent systems; however, most research considers only the behavior of individual models. We experimentally show that multi-agent "AI organizatio…
Investigating Data Interventions for Subgroup Fairness: An ICU Case Study
Erin Tan, Judy Hanwen Shen, Irene Y. Chen
In high-stakes settings where machine learning models are used to automate decision-making about individuals, the presence of algorithmic bias can exacerbate systemic harm to certa…
How AI Impacts Skill Formation
Judy Hanwen Shen, Alex Tamkin
AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills requir…
The Limits of AI Data Transparency Policy: Three Disclosure Fallacies
Judy Hanwen Shen, Ken Liu, Angelina Wang +7
Data transparency has emerged as a rallying cry for addressing concerns about AI: data quality, privacy, and copyright chief among them. Yet while these calls are crucial for accou…
Disclosure and Evaluation as Fairness Interventions for General-Purpose AI
Vyoma Raman, Judy Hanwen Shen, Andy K. Zhang +4
Despite conflicting definitions and conceptions of fairness, AI fairness researchers broadly agree that fairness is context-specific. However, when faced with general-purpose AI, w…