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Beloved Afterlives: Governing AI Resurrection Beyond Consent

Aug 2026 · 0 citations · 44 references
Computer Science

TL;DR

Rel relational authority is developed: authorization is distributed across people, records, providers, and audiences, and must remain traceable as those relations change, and must remain traceable as those relations change.

Abstract

AI resurrection is often framed as a question of consent: did the represented person authorize being made to speak? That question matters, but it freezes authority at the moment of creation. A representation can later change models, pass to relatives, depend on a provider, incorporate records shared with others, or circulate far beyond its intended audience. We argue that the central governance problem is therefore not whether authorization exists once, but whether it remains legible as the representation moves. Across a public-record audit of 93 systems, creation was far easier to inspect than the conditions for speaking, contesting, preserving, or leaving: consent or authority information was thin in 82 systems, objection or redress in 82, and deletion or export in 77. The differences among systems reveal why these gaps cannot be reduced to one transparency score. Human afterlives show consent becoming incomplete over time. Companion-animal afterlives begin where subject consent is unavailable and shared care must allocate authority. Adjacent persona and mimetic systems show how voices, likenesses, and personalities can travel into later afterlife uses. Four public cases follow the same movement from premortem participation, through intimate postmortem creation, to third-party circulation and family contestation. From this evidence we develop relational authority: authorization is distributed across people, records, providers, and audiences, and must remain traceable as those relations change. This reframes AI resurrection from a product authorized once into an accountability chain linking creation authority, source boundaries, circulation, contestation, and exit. The study measures what users and affected parties can inspect publicly; private implementation and lived outcomes remain open empirical questions.

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