activity
20242026
collaborators

27 papers

cs.CY2026

Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts

Alexander K. Saeri, Jess Graham, Michael Noetel +185

Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…

cs.AI2026

Human agency in initial human-AI proof formalization workflows

Katherine M. Collins, Simon Frieder, Jonas Bayer +14

For centuries, human mathematicians have written proofs to substantiate their mathematical arguments; yet, the ability to automatically verify the validity of proofs has long been…

cs.CY2026

Cognitive offloading and the speedup illusion in human-AI interaction

Sunny Yu, Myra Cheng, Ahmad Jabbar +4

Large language models (LLMs) have the potential to boost human productivity by speeding up task completion -- provided users know when to offload cognitive work to them. But we do…

cs.CY2026

The efficiency-gain illusion: People underestimate the rate of AI use and overestimate its benefits on simple tasks

Sunny Yu, Myra Cheng, Ahmad Jabbar +4

People are increasingly turning to AI assistance for simple tasks, e.g., arithmetic, spell-check, and answering simple questions. But does AI assistance actually save users time an…

cs.LG2026

On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation

Andy Han, Kristina Fujimoto, Avidan Shah +5

Aligned models can misbehave in several ways: they are often sycophantic, fall victim to jailbreaks, or fail to include appropriate safety warnings. Consistency training is a promi…

cs.CY2026

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…