Theoretical framework models temporal continuity and relational development in artificial systems, highlighting identity persistence beyond capability metrics.
Artificial intelligence is commonly evaluated by task performance, generality, autonomy, or prospective AGI and ASI capability levels. This paper asks a different question: what kind of artificial system persists through time, and how do relations to the world, to others, and to its past self become conditions for its next orientation and action? It proposes the Developmental Artificial Subject as a functional, relational, and temporal system form. Its candidate contribution is a constitutive bridge linking developmental closure, claim-relative bearer individuation, level-relative fork and merge judgments, and migration or successor continuity assessed over declared evidence dimensions. Capability level, capability-growth path, and system form are kept analytically distinct. The theory does not presuppose consciousness, personhood, moral status, or a unique engineering architecture. Repository preprint. Not peer reviewed. A journal manuscript based on this preprint is currently under review.
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Pascal Lv (2026) studied this question.