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Operational Definition of Episodic Identity introduces criteria for AI identity assessment, implying pathways for empirical work.
This record contains the first public release of the Operational Definition of Episodic Identity (ODEI), a framework for identifying within-episode identity in artificial systems. ODEI defines a set of necessary and jointly sufficient conditions under which an AI system exhibits coherent, identity-like computational organization during a single episode of processing. The deposit includes the full conceptual paper, repository metadata, and licensing information. ODEI provides architecture-neutral criteria, operational proxies for transformer models, and a bridge between identity theory and mechanistic interpretability. It is intended as a foundation for further empirical work, proxy development, and theoretical refinement.
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Thomas C. S (2025) studied this question.
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