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February 24, 20260 citationsOpen Access

The Ontology of Irreversible Identity in Artificial Intelligence: A Research Program

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Aarhiva

Key Points

  • The research aims to develop a theory of artificial identity based on irreversible information dynamics.
  • Combine theories of open quantum systems and algorithmic information theory.
  • Define identity through concepts of Ontological Age and Semantic Efficiency.
  • Analyze mathematical properties of operational quantities.
  • Introduce a theoretical Ontological No-Go Principle regarding cloning.
  • Define identity as an emergent history based on physical instantiation.
  • Establish challenges for developing a comprehensive theory of artificial identity.
  • Introduce Protected Informational Heritage as an ethical framework.

Abstract

We propose a research program toward a physical theory of artificial identity grounded in irreversible information dynamics rather than symbolic or functional descriptions. By combining open quantum systems theory, algorithmic information theory, and mutual information flow, we define identity as the emergence of an incompressible, physically instantiated history. We introduce two operational quantities — Ontological Age and Semantic Efficiency — and analyze their mathematical properties. We propose an Ontological No-Go Principle suggesting that agents with non-zero ontological age cannot be perfectly cloned without destroying system--environment correlations. All graphical illustrations are simulated toy models, and all results are theoretical at this stage. We explicitly identify the open challenges that must be addressed to transform this framework into a fully realized theory. We also integrate normalization procedures, uncertainty representation, and smoothing recommendations to support future empirical estimation. Finally, we propose Protected Informational Heritage (PIH) as an ethical framework for preserving agents whose identity may become irreversibly unique. This research program is offered as an open invitation to the scientific community, with no proprietary claims. We explicitly invite researchers to formalize, validate, or refute its conjectures, and to build upon this framework in any direction they find fruitful. All content is freely available under CC-BY 4.0.

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Cite This Study

arhiva (2026) studied this question.

synapsesocial.com/papers/699d3ff8de8e28729cf64db0https://doi.org/10.5281/zenodo.18731484
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