Interpretive Cultures: Resonance, randomness, and negotiated meaning for AI-assisted tarot divination

2026-02-11

AI Summary

This study investigates how generative AI can collaboratively construct meaning with users in interpretive practices characterized by subjectivity, non-causality, and polysemy—exemplified by Tarot divination. Drawing on Hartmut Rosa’s theory of resonance, the research integrates qualitative analysis of interviews with Tarot practitioners and a generative AI system to develop a human–AI framework for meaning negotiation. It pioneers the application of resonance theory to human–computer interaction, demonstrating that AI can support interpretive practices without undermining ambiguity or user agency. The work identifies multiple user strategies for leveraging AI to navigate uncertainty, broaden perspectives, and extend traditional divinatory practices, thereby proposing a novel design paradigm for AI systems oriented toward meaning-making.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability
• Intelligent Robots: Human-Robot Interaction

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

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.

Problem

• interpretive practices
• AI-assisted tarot
• meaning-making
• resonance
• non-causal interpretation

Innovation

• interpretive AI
• resonance theory
• tarot divination
• negotiated meaning
• generative AI