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Multiverse Privacy Theory for Contextual Risks in Complex User-AI Interactions

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arxiv 2506.10042 v1 pith:2ZH55SQA submitted 2025-06-11 cs.CR cs.HC

Multiverse Privacy Theory for Contextual Risks in Complex User-AI Interactions

classification cs.CR cs.HC
keywords privacytheorycomplexcontextualevolvingmultiverseapplicationartificial
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In an era of increasing interaction with artificial intelligence (AI), users face evolving privacy decisions shaped by complex, uncertain factors. This paper introduces Multiverse Privacy Theory, a novel framework in which each privacy decision spawns a parallel universe, representing a distinct potential outcome based on user choices over time. By simulating these universes, this theory provides a foundation for understanding privacy through the lens of contextual integrity, evolving preferences, and probabilistic decision-making. Future work will explore its application using real-world, scenario-based survey data.

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