arXiv:2607.00220v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are routinely modified after deployment through retraining and changes in their environments. These transformations raise a metaphysical question: under what conditions does an AI system remain the same system over time or across deployments? Earlier work formulates synchronic and diachronic identity propositionally, by relating identity within a fixed AI system type to equality of trustworthiness levels. Such criteria specify when identity statements are true, but leave implicit the structure of the states
The paper addresses a foundational philosophical question regarding AI identity that becomes increasingly relevant as AI systems evolve and are continuously modified in real-world deployments.
Understanding AI identity is crucial for establishing accountability, legal frameworks, and ethical guidelines for autonomous systems that learn and adapt.
This theoretical work provides a new categorical framework for defining AI identity, potentially leading to more robust and consistent approaches in AI governance and system design.
- · AI ethicists
- · AI legal professionals
- · Developers of robust AI systems
- · Developers of undefined AI systems
Philosophical and mathematical foundations for AI identity are strengthened.
Improved frameworks for regulatory compliance and auditability of evolving AI systems emerge.
The development of 'AI rights' or 'AI personhood' discussions may gain more structured conceptual grounds.
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Read at arXiv cs.AI