The Accountability Horizon: An Impossibility Theorem for Governing Human-Agent Collectives
Existing accountability frameworks for AI systems, legal, ethical, and regulatory, rest on a shared assumption: for any consequential outcome, at least one identifiable person had enough involvement and foresight to bear meaningful responsibility. This paper proves that agentic AI systems violate this assumption not as an engineering limitation but as a mathematical necessity once autonomy exceeds a computable threshold. We introduce Human-Agent Collectives, a formalisation of joint human-AI systems where agents are modelled as state-policy tuples within a shared structural causal model. Autonomy is characterised through a four-dimensional information-theoretic profile (epistemic, executi...
| Authors | Haileleol Tibebu, Hewan Shemtaga |
|---|---|
| Primary category | cs.AI |
| Published | 9 April 2026 |
| Last updated at source | 2 June 2026 |
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