The Controllability Trap: A Governance Framework for Military AI Agents
The article discusses a new governance framework for military AI agents called the Agentic Military AI Governance Framework (AMAGF). It identifies six governance failures that can occur with agentic AI systems and proposes a continuous model for measuring and managing control quality. The framework aims to enhance human oversight in military operations through preventive, detective, and corrective governance strategies.
- ▪The framework addresses distinct control failures not covered by existing safety measures.
- ▪It introduces a Control Quality Score (CQS) to quantify human control in real-time.
- ▪The governance model emphasizes continuous measurement and management of control quality throughout the operational lifecycle.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2603.03515 |
| Publication time | Tue, 28 Apr 2026 21:24:13 +0000 |
| Retrieval time | 2026-04-28T21:35:32.840Z |
| Last seen | 2026-04-28T21:35:32.840Z |
| 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 | TkaT-gZu0Lp2 |
| 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 |
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| 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.
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Computer Science > Computers and Society arXiv:2603.03515 (cs) [Submitted on 3 Mar 2026] Title:The Controllability Trap: A Governance Framework for Military AI Agents Authors:Subramanyam Sahoo View a PDF of the paper titled The Controllability Trap: A Governance Framework for Military AI Agents, by Subramanyam Sahoo View PDF HTML (experimental) Abstract:Agentic AI systems - capable of goal interpretation, world modeling, planning, tool use, long-horizon operation, and autonomous coordination - introduce distinct control failures not addressed by existing safety frameworks. We identify six agentic governance failures tied to these capabilities and show how they erode meaningful human control in military settings.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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