David Guzman Piedrahita — accepted AI-conference papers

2026

CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas

Emanuel Tewolde, Xiao Zhang, David Guzman Piedrahita, Vincent Conitzer, Zhijing Jin

ICML 2026poster

It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, according to recent works, the opposite trend appears to be the case: LLMs with stronger reasoning capabilities behave _less_ cooperatively in mixed-motive games such as the prisoner's …

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2026

Position: Safe Models Do Not Guarantee Safe Societies: The Case for Sociopolitical Risk

David Guzman Piedrahita, Dave Banerjee, Changling Li, Terry Zhang, Kevin Blin, Samuel Simko +5

ICML 2026spotlight

Sociopolitical AI risks are threats to collective self-determination: a society's capacity to articulate its interests and realize them through institutions. We argue that sociopolitical AI risks emerge when general-purpose AI systems are integrated into society in ways that disproportionately ampli…

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