5 papers
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…
Large-Scale, Longitudinal Study of Large Language Models During the 2024 US Election Season
Sarah H. Cen, Andrew Ilyas, Hedi Driss +4
The 2024 US presidential election is the first major contest to occur in the US since the popularization of large language models (LLMs). Building on lessons from earlier shifts in…
AI Supply Chains: An Emerging Ecosystem of AI Actors, Products, and Services
Aspen Hopkins, Sarah H. Cen, Andrew Ilyas +3
The widespread adoption of AI in recent years has led to the emergence of AI supply chains: complex networks of AI actors contributing models, datasets, and more to the development…
From Transparency to Accountability and Back: A Discussion of Access and Evidence in AI Auditing
Sarah H. Cen, Rohan Alur
Artificial intelligence (AI) is increasingly intervening in our lives, raising widespread concern about its unintended and undeclared side effects. These developments have brought…
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…