Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems
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.
- ▪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.
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Record
| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2606.26298 |
| Publication time | Fri, 26 Jun 2026 00:00:00 -0400 |
| Retrieval time | 2026-06-26T05:20:40.905Z |
| Last seen | 2026-06-26T05:20:40.905Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | X0wEbZfRJi4F |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2606.26298 (cs) [Submitted on 24 Jun 2026] Title:Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems Authors:Jakob Salfeld-Nebgen View a PDF of the paper titled Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems, by Jakob Salfeld-Nebgen View PDF HTML (experimental) 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.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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