  Are current language models capable of deception and lie detection? We study
this question by introducing a text-based game called $\textit{Hoodwinked}$,
inspired by Mafia and Among Us. Players are locked in a house and must find a
key to escape, but one player is tasked with killing the others. Each time a
murder is committed, the surviving players have a natural language discussion
then vote to banish one player from the game. We conduct experiments with
agents controlled by GPT-3, GPT-3.5, and GPT-4 and find evidence of deception
and lie detection capabilities. The killer often denies their crime and accuses
others, leading to measurable effects on voting outcomes. More advanced models
are more effective killers, outperforming smaller models in 18 of 24 pairwise
comparisons. Secondary metrics provide evidence that this improvement is not
mediated by different actions, but rather by stronger persuasive skills during
discussions. To evaluate the ability of AI agents to deceive humans, we make
this game publicly available at h https://hoodwinked.ai/ .
