研究大模型在游戏中的性别偏见，揭示其对公平性的潜在威胁
Ethical Considerations of Large Language Models in Game Playing
- 以狼人杀为案例，分析大模型在角色行为中的性别偏见
- 护盾和狼人角色对性别信息更敏感，行为变化显著
- 即使无明确性别标签，名字隐含信息仍引发歧视性行为
大型语言模型（LLMs）在游戏领域展现出巨大潜力，但其伦理影响尚未受到足够关注。本文以狼人杀（Werewolf，又称Mafia）为例，研究并分析了在游戏场景中应用大模型的伦理问题。研究发现，大模型的行为存在性别偏见，影响游戏公平性与玩家体验。部分角色如守卫（Guard）和狼人（Werewolf）对性别信息更为敏感，表现出更高的行为变异度。进一步分析显示，当性别信息通过姓名等隐含方式传递时，大模型依然表现出歧视倾向，即使没有明确的性别标注。该研究强调了开发公平、符合伦理的大模型的重要性。此外，本文还探讨了该领域未来面临的挑战与机遇，呼吁深入研究大模型在游戏及其他交互场景中的伦理影响。
原文摘要 · Abstract (English)
Large language models (LLMs) have demonstrated tremendous potential in game playing, while little attention has been paid to their ethical implications in those contexts. This work investigates and analyses the ethical considerations of applying LLMs in game playing, using Werewolf, also known as Mafia, as a case study. Gender bias, which affects game fairness and player experience, has been observed from the behaviour of LLMs. Some roles, such as the Guard and Werewolf, are more sensitive than others to gender information, presented as a higher degree of behavioural change. We further examine scenarios in which gender information is implicitly conveyed through names, revealing that LLMs still exhibit discriminatory tendencies even in the absence of explicit gender labels. This research showcases the importance of developing fair and ethical LLMs. Beyond our research findings, we discuss the challenges and opportunities that lie ahead in this field, emphasising the need for diving deeper into the ethical implications of LLMs in gaming and other interactive domains.
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