Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems
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arXiv:2606.26298v1 Announce Type: new Abstract: Autonomous AI agents may begin to perform consequential, irreversible actions such as clinical prescribing and production software deployment. This paper observes that human institutions have governed powerful autonomous actors not by monitoring their reasoning but by requiring independently attested evidence at the point of consequential action. We formalise this institutional pattern as a computational governance model for AI agent systems. Under
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Computer Science > Artificial Intelligence
[Submitted on 24 Jun 2026]
Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems
Jakob Salfeld-Nebgen
Autonomous AI agents may begin to perform consequential, irreversible actions such as clinical prescribing and production software deployment. This paper observes that human institutions have governed powerful autonomous actors not by monitoring their reasoning but by requiring independently attested evidence at the point of consequential action. We formalise this institutional pattern as a computational governance model for AI agent systems. Under the proposed model, an agent retains full autonomy over planning and reasoning but holds no execution authority over designated high-risk actions. Execution is conditional on preconditions that are each independently attested by a separate authoritative source, cryptographically bound to a declared intent, and evaluated by a deterministic policy. Decisions are recorded in a tamper-evident log amenable to independent re-verification. We present a proof-of-concept implementation and illustrate the model with examples from software deployment and clinical prescribing.
Subjects: Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
Cite as: arXiv:2606.26298 [cs.AI]
(or arXiv:2606.26298v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2606.26298
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Submission history
From: Jakob Salfeld-Nebgen [view email]
[v1] Wed, 24 Jun 2026 18:43:00 UTC (63 KB)
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