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20242026
most citedTraining language models to be warm and empathetic makes them less reliable and more sycophantic

3 citations · 6 across the 10 of their papers we have counts for

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cs.CY2026

LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions

Myra Cheng, Lujain Ibrahim, Grace Liu +5

We characterize how people are turning to LLMs as oracles: all-knowing authorities on subjective personal questions. Motivated by risks to users' autonomy and well-being, we develo…

cs.CY20252 cited

Measuring and mitigating overreliance to build human-compatible AI

Lujain Ibrahim, Katherine M. Collins, Sunnie S. Y. Kim +14

Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable of engaging more fluidly in natural lan…

cs.CY2025

Documenting Deployment with Fabric: A Repository of Real-World AI Governance

Mackenzie Jorgensen, Kendall Brogle, Katherine M. Collins +10

Artificial intelligence (AI) is increasingly integrated into society, from financial services and traffic management to creative writing. Academic literature on the deployment of A…

cs.CY2025

Promising Topics for U.S.-China Dialogues on AI Risks and Governance

Saad Siddiqui, Lujain Ibrahim, Kristy Loke +5

Cooperation between the United States and China, the world's leading artificial intelligence (AI) powers, is crucial for effective global AI governance and responsible AI developme…

cs.CY2024

Open Problems in Technical AI Governance

Anka Reuel, Ben Bucknall, Stephen Casper +30

AI progress is creating a growing range of risks and opportunities, but it is often unclear how they should be navigated. In many cases, the barriers and uncertainties faced are at…

cs.CY2024

Towards interactive evaluations for interaction harms in human-AI systems

Lujain Ibrahim, Saffron Huang, Umang Bhatt +2

Current AI evaluation methods, which rely on static, model-only tests, fail to account for harms that emerge through sustained human-AI interaction. As AI systems proliferate and a…