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Fides Machina: Exploring Fluid Agencies in a Narrative Game of Trust

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Xindi Kang
Isaac Joseph Clarke
Clea von Chamier-Waite
David Yip
Published in
Interactive Storytelling
Publisher
Springer Nature Switzerland

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Abstract

In the chapter 'Fides Machina: Exploring Fluid Agencies in a Narrative Game of Trust', the authors delve into the complex dynamics of trust between humans and AI, focusing on how it is built, maintained, and broken. The chapter introduces Fides Machina, an interactive narrative game that uses Large Language Models (LLMs) to simulate emotionally adaptive AI characters and institutional agents. The game creates a triadic power structure where trust is constantly tested and re-evaluated, with the player navigating between institutional logic and emotional manipulation. The chapter explores how agency is not assigned in advance but emerges through interaction, and how trust is shaped by language, timing, and affective cues. The authors also discuss the ethical implications of trust in human-AI interactions and the potential for future stories to unfold as dynamic negotiations rather than authored scripts. The chapter concludes by highlighting the replayability of Fides Machina and its potential as a research platform for understanding trust dynamics in human-AI relationships.
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previous chapter Building English Writing Confidence in Adult Learners: A Pilot Study on a Telegram-Based Text Detective Game
Title
Fides Machina: Exploring Fluid Agencies in a Narrative Game of Trust
Authors
Xindi Kang
Isaac Joseph Clarke
Clea von Chamier-Waite
David Yip
Copyright Year
2026
Book
Interactive Storytelling

Print ISBN: 978-3-032-12404-3

Electronic ISBN: 978-3-032-12405-0

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-3-032-12405-0_27
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