While generative AI tools are increasingly adopted for creative and analytical tasks, their role in interpretive practices, where meaning is subjective, plural, and non-causal, remains poorly understood. This paper examines AI-assisted tarot reading, a divinatory practice in which users pose a query, draw cards through a randomized process, and ask AI systems to interpret the resulting symbols. Drawing on interviews with tarot practitioners and Hartmut Rosa's Theory of Resonance, we investigate how users seek, negotiate, and evaluate resonant interpretations in a context where no causal relationship exists between the query and the data being interpreted. We identify distinct ways practitioners incorporate AI into their interpretive workflows, including using AI to navigate uncertainty and self-doubt, explore alternative perspectives, and streamline or extend existing divinatory practices. Based on these findings, we offer design recommendations for AI systems that support interpretive meaning-making without collapsing ambiguity or foreclosing user agency.

翻译：尽管生成式AI工具在创意和分析任务中的应用日益广泛，但它们在阐释性实践中的作用——即意义具有主观性、多元性和非因果性的领域——仍鲜为人知。本文研究了AI辅助塔罗占卜这一占卜实践，用户在其中提出查询，通过随机过程抽取卡牌，并要求AI系统解读所得符号。基于对塔罗实践者的访谈以及哈特穆特·罗萨的共鸣理论，我们探究了在查询与被解读数据之间不存在因果关系的语境下，用户如何寻求、协商并评估共鸣性解读。我们识别了实践者将AI融入其阐释工作流程的不同方式，包括利用AI应对不确定性与自我怀疑、探索替代性视角，以及精简或扩展现有占卜实践。基于这些发现，我们为AI系统提出了设计建议，以支持阐释性意义构建，同时不消解模糊性或限制用户能动性。