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most citedMeasuring and mitigating overreliance to build human-compatible AI

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cs.CY20261 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.CY2026

How are AI agents used? Evidence from 177,000 MCP tools

Merlin Stein

Today's AI agents are built on large language models (LLMs) equipped with tools to access and modify external environments, such as corporate file systems, API-accessible platforms…

cs.CY2025

Who Should Run Advanced AI Evaluations -- AISIs?

Merlin Stein, Milan Gandhi, Theresa Kriecherbauer +2

Artificial Intelligence (AI) Safety Institutes and governments worldwide are deciding whether they evaluate advanced AI themselves, support a private evaluation ecosystem or do bot…

cs.CY2024

Monitoring Human Dependence On AI Systems With Reliance Drills

Rosco Hunter, Richard Moulange, Jamie Bernardi +1

AI systems are assisting humans with increasingly diverse intellectual tasks but are still prone to mistakes. Humans are over-reliant on this assistance if they trust AI-generated…

cs.CY2024

The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AI

Merlin Stein, Jamie Bernardi, Connor Dunlop

Language-based AI systems are diffusing into society, bringing positive and negative impacts. Mitigating negative impacts depends on accurate impact assessments, drawn from an empi…