Artificial Intelligence (AI) is increasingly employed in various decision-making tasks, typically as a Recommender, providing recommendations that the AI deems correct. However, recent studies suggest this may diminish human analytical thinking and lead to humans' inappropriate reliance on AI, impairing the synergy in human-AI teams. In contrast, human advisors in group decision-making perform various roles, such as analyzing alternative options or criticizing decision-makers to encourage their critical thinking. This diversity of roles has not yet been empirically explored in AI assistance. In this paper, we examine three AI roles: Recommender, Analyzer, and Devil's Advocate, and evaluate their effects across two AI performance levels. Our results show each role's distinct strengths and limitations in task performance, reliance appropriateness, and user experience. Notably, the Recommender role is not always the most effective, especially if the AI performance level is low, the Analyzer role may be preferable. These insights offer valuable implications for designing AI assistants with adaptive functional roles according to different situations.

翻译：人工智能（AI）正越来越多地应用于各种决策任务，通常作为“推荐者”（Recommender）角色，提供其认为正确的建议。然而，近期研究表明，这种模式可能削弱人类的分析性思维，导致人类对AI的不当依赖，从而损害人机协同效果。相比之下，群体决策中的人类顾问会扮演多种角色，例如分析备选方案或对决策者提出质疑以激发其批判性思维。这种角色多样性在AI辅助场景中尚未得到实证探索。本文研究了三种AI角色：推荐者、分析者（Analyzer）与魔鬼代言人（Devil's Advocate），并评估了它们在两种AI性能水平下的效果。结果显示，各角色在任务表现、依赖适当性和用户体验方面具有独特优势与局限。值得注意的是，推荐者角色并非始终最有效——当AI性能水平较低时，分析者角色可能更优。这些发现为根据不同情境设计具有自适应功能角色的AI助手提供了重要启示。