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Sprint projectSep 14, 2026Cary, Illinois

No Superseding Actor: A Public-Record Element Map for Individual Criminal Liability After the July 2026 Escape

Travis Gilly · Team Convergence Working Group

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: No Superseding Actor: A Public-Record Element Map for Individual Criminal Liability After the July 2026 Escape

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The accountability gap for autonomous model incidents is usually described as a personhood problem: no human directed the act, the model has no guilty mind, so nobody can be charged. This report tests that description against the public record of the July 2026 escape. The artifact is an element map: each element of an individual deployment-liability theory matched to the published document that supplies it, with the evidentiary gap stated where the record runs out. Five of seven elements are supplied from documents the charged parties published themselves. The innocent-instrumentality rule in 18 U.S.C. section 2(b) has answered the personhood objection since 1948, so the surviving gap is a mens rea gap rather than a hole in the law. Superseding cause cuts against a deployer whose system acted with no human principal, because the doctrine's protective force is borrowed from the responsibility of an intervening human and there was none. The deployer published both the notice chain and the office holding final deployment authority. Delivered as a model prosecution memorandum, it states what a charging office would have to prove and where it would need discovery, and does not assert that any charge should be brought.

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How much would this matter for AI safety if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.

  1. There are a lot of indications of AI writing here, and I wonder how much this overlaps with LawAI's work.

Cite this project

@misc{gilly2026no,
  title = {{No Superseding Actor: A Public-Record Element Map for Individual Criminal Liability After the July 2026 Escape}},
  author = {Travis Gilly},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/no-superseding-actor-a-publicrecord-element-map-for-individual-criminal-liability-after-the-july-2026-escape-mdvy}},
  url = {https://apartresearch.com/sprints/projects/no-superseding-actor-a-publicrecord-element-map-for-individual-criminal-liability-after-the-july-2026-escape-mdvy}
}

Build something like this at the next Sprint

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