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Identity Continuity in Long-Term Embodied AI Relationships: From Agent-Specific Identity Representation to Identity-Continuity Appraisal — arXiv:2609.23356

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.23356
License (as archived): CC0-1.0
Archived: 2026-10-09T07:01:50.903Z
SHA-256 of the archived text: 6fb4f2803f6c7de0c9f277a22d6dee0f6cdb8f1b17254f897943009b995998ae
Stable URL of this page: https://metraipolis.com/documento/dc_37ca559ba2ca

How to cite

Identity Continuity in Long-Term Embodied AI Relationships: From Agent-Specific Identity Representation to Identity-Continuity Appraisal — arXiv:2609.23356 — arXiv (en), https://arxiv.org/abs/2609.23356 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_37ca559ba2ca (Metraipolis archive dc_37ca559ba2ca, sha256 6fb4f2803f6c7de0c9f277a22d6dee0f6cdb8f1b17254f897943009b995998ae)

BibTeX

@misc{dc37ca559ba2ca,
  title = {Identity Continuity in Long-Term Embodied AI Relationships: From Agent-Specific Identity Representation to Identity-Continuity Appraisal — arXiv:2609.23356},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.23356},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_37ca559ba2ca; sha256 6fb4f2803f6c7de0c9f277a22d6dee0f6cdb8f1b17254f897943009b995998ae},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.23356. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Long-term embodied AI will undergo learning, model updates, memory compression, hardware repair, and migration across embodiments. For users who have formed sustained relationships with such systems, these changes raise not only a problem of product consistency but also one of identity continuity: whether the changed system is still experienced as the same particular agent. Existing research suggests that human-AI relationships may develop relational particularity, that robotics and artificial-identity research has identified identity and migration signals across embodiments, and that major updates or platform disruptions can be accompanied by relational loss and restoration desire. This article proposes a user-side framework in which long-term embodied AI is represented through an agent-specific identity representation organized by at least three open identity-content domains: embodied-perceptual, psychological-behavioral, and relational-autobiographical. Information from these domains is not equally weighted; shared history, relational roles, and contingent responsiveness may make some information more identity-diagnostic than others. After system change, users may integrate continuity and discontinuity evidence in a weighted manner, yielding judgments along a continuum from relatively strong identity continuity through ambiguity or partial continuity to clear identity discontinuity. Causal-historical provenance and user participation are treated as contextual evidence rather than a fourth identity-content domain. The framework also proposes identity continuity as a psychological objective for lifecycle design, including memory selection, model updating, and migration across embodiments, under constraints of privacy and user control.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-22 in cs.HC).
Categorie arXiv: Human-Computer Interaction (cs.HC) ; Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2609.23356 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T06:56:29.222Z dalla pagina https://arxiv.org/catchup/cs.HC/2026-09-22?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).