219 citations · 423 across the 16 of their papers we have counts for
17 papers
AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI
Ayse Gizem Yasar, Andrew Chong, Evan Dong +9
As AI technology advances rapidly, concerns over the risks of bigness in digital markets are also growing. The EU's Digital Markets Act (DMA) aims to address these risks. Still, th…
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Stephen Casper, Xander Davies, Claudia Shi +29
Reinforcement learning from human feedback (RLHF) is a technique for training AI systems to align with human goals. RLHF has emerged as the central method used to finetune state-of…
Accountability Infrastructure: How to implement limits on platform optimization to protect population health
Nathaniel Lubin, Thomas Krendl Gilbert
Attention capitalism has generated design processes and product development decisions that prioritize platform growth over all other considerations. To the extent limits have been…
Optimization's Neglected Normative Commitments
Benjamin Laufer, Thomas Krendl Gilbert, Helen Nissenbaum
Optimization is offered as an objective approach to resolving complex, real-world decisions involving uncertainty and conflicting interests. It drives business strategies as well a…
Dynamic Documentation for AI Systems
Soham Mehta, Anderson Rogers, Thomas Krendl Gilbert
AI documentation is a rapidly-growing channel for coordinating the design of AI technologies with policies for transparency and accessibility. Calls to standardize and enact docume…
Beyond Bias and Compliance: Towards Individual Agency and Plurality of Ethics in AI
Thomas Krendl Gilbert, Megan Welle Brozek, Andrew Brozek
AI ethics is an emerging field with multiple, competing narratives about how to best solve the problem of building human values into machines. Two major approaches are focused on b…