1 citations · 2 across the 9 of their papers we have counts for
10 papers
Qualifying and Quantifying Risk Under the EU AI Act
Gustavo Gil Gasiola, Sarah H. Cen, Frederike Zufall
The EU AI Act uses a risk-based approach to regulate AI systems, calibrating the intensity of regulation according to the risks they pose. While the term 'risk' implies quantificat…
Taxing Artificial Intelligence
Juliette Faivre, Sarah H. Cen
While AI promises major benefits, its development and deployment can shift costs onto others, including environmental pressures on local communities, labor and creative displacemen…
Using AI Agents to Automate Black-Box Audits of Personalization Algorithms at Scale
Alessandro Morosini, Sarah H. Cen, Andrew Ilyas +3
Personalization algorithms determine what content users encounter on online platforms. Auditing these systems is difficult because independent auditors have only black-box access t…
Barriers to Evidence in AI-Related Cases and the Privatization of Proof
Sarah H. Cen, Hannah Ismael, Lucia Zheng
Evidence lies at the core of litigation, but it is increasingly difficult to obtain in AI-related disputes. Even when a claimant's position has merit, cases are often settled or di…
Do LLMs Track Public Opinion? A Multi-Model Study of Favorability Predictions in the 2024 U.S. Presidential Election
Riya Parikh, Sarah H. Cen, Chara Podimata
We investigate whether Large Language Models (LLMs) can track public opinion as measured by exit polls during the 2024 U.S. presidential election cycle. Our analysis focuses on hea…
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…
Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives
Sarah H. Cen, Salil Goyal, Zaynah Javed +3
AI audits play a critical role in AI accountability and safety. One branch of the law for which AI audits are particularly salient is anti-discrimination law. Several areas of anti…
The California Report on Frontier AI Policy
Rishi Bommasani, Scott R. Singer, Ruth E. Appel +20
The innovations emerging at the frontier of artificial intelligence (AI) are poised to create historic opportunities for humanity but also raise complex policy challenges. Continue…
Measuring Strategization in Recommendation: Users Adapt Their Behavior to Shape Future Content
Sarah H. Cen, Andrew Ilyas, Jennifer Allen +2
Most modern recommendation algorithms are data-driven: they generate personalized recommendations by observing users' past behaviors. A common assumption in recommendation is that…
User Strategization and Trustworthy Algorithms
Sarah H. Cen, Andrew Ilyas, Aleksander Madry
Many human-facing algorithms -- including those that power recommender systems or hiring decision tools -- are trained on data provided by their users. The developers of these algo…