When Ethics and Payoffs Diverge: LLM Agents in Morally Charged Social Dilemmas
Steffen Backmann, David Guzman Piedrahita, Emanuel Tewolde, Rada Mihalcea, Bernhard Schölkopf, Zhijing Jin — 2025-05-25 — Max Planck Institute for Intelligent Systems — arXiv
Summary
Introduces MoralSim, a benchmark testing how frontier LLMs behave in prisoner’s dilemma and public goods games when ethical norms conflict with payoff-maximizing strategies, evaluating multiple models across different moral framings and situational factors.
Key Result
No tested model exhibits consistently moral behavior in MoralSim, with substantial variation across models in their tendency to act morally and consistency across game types, moral framings, and situational factors.
Source
- Link: https://arxiv.org/abs/2505.19212
- Listed in the Shallow Review of Technical AI Safety 2025 under 1 agenda(s):
- capability-evals — Evals