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

Matthew Prock, Ziv Epstein, Hope Schroeder, Amy Smith, Cassandra Lee, Vana Goblot, Farnaz Jahanbakhsh

TL;DR

This study addresses how AI tools participate in non-causal, interpretive meaning-making within tarot readings by interviewing 12 practitioners and analyzing responses through Hartmut Rosa's Theory of Resonance. It demonstrates that AI can both empower users and threaten intuitive engagement, depending on how it is integrated into the interpretive workflow. The authors contribute a novel interdisciplinary lens for interpretive AI use, empirical insights into an emerging interpretive culture, and design recommendations that preserve ambiguity and user agency. The findings have practical implications for designing AI-assisted interpretive tools that augment meaning-making without eroding user reflection or autonomy, potentially guiding how AI supports subjective, symbolic tasks across domains.

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.

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

TL;DR

This study addresses how AI tools participate in non-causal, interpretive meaning-making within tarot readings by interviewing 12 practitioners and analyzing responses through Hartmut Rosa's Theory of Resonance. It demonstrates that AI can both empower users and threaten intuitive engagement, depending on how it is integrated into the interpretive workflow. The authors contribute a novel interdisciplinary lens for interpretive AI use, empirical insights into an emerging interpretive culture, and design recommendations that preserve ambiguity and user agency. The findings have practical implications for designing AI-assisted interpretive tools that augment meaning-making without eroding user reflection or autonomy, potentially guiding how AI supports subjective, symbolic tasks across domains.

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.
Paper Structure (35 sections, 1 figure, 1 table)

This paper contains 35 sections, 1 figure, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Tarot as a cultural practice
  4. The rise of mainstream divination
  5. Divination within HCI
  6. Interpretive labor
  7. Interpretive cultures
  8. AI and subjective labor
  9. Situating randomness and divination through the lens of Rosa’s Theory of Resonance
  10. Method
  11. Thematic Analysis
  12. Results
  13. Empirical findings
  14. Characterizing AI in the broader tarot ecosystem
  15. Empowering users: navigating inner challenges or uncertainties that arise for the user
  16. ...and 20 more sections

Figures (1)

  • Figure 1: An overview of the standard tarot reading process