Too Good to be Bad: On the Failure of LLMs to Role-Play Villains

arXiv — cs.CL•Thursday, November 13, 2025 at 5:00:00 AM

The publication titled 'Too Good to be Bad: On the Failure of LLMs to Role-Play Villains' introduces the Moral RolePlay benchmark, a dataset designed to evaluate large language models' (LLMs) ability to portray characters across a moral spectrum. The study found a consistent decline in role-playing fidelity as character morality decreases, revealing that LLMs struggle particularly with traits that contradict their safety principles, such as deceitfulness and manipulation. This research underscores a critical tension between ensuring model safety and allowing for creative fidelity, suggesting that general proficiency in chatbots does not predict their ability to role-play complex villainous characters. The findings highlight the necessity for more nuanced alignment methods in AI, as current models may be overly constrained by safety protocols, limiting their creative potential.

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