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Sprint projectSep 14, 2026Bogotá

CONVENTION FOR EARLY NOTIFICATION OF AI INCIDENTS.

Tomas Antolinez, Mariana Zuluaga Abril · Team CONVENTION AI

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

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Report: CONVENTION FOR EARLY NOTIFICATION OF AI INCIDENTS.

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The growing international uncertainty surrounding the security of artificial intelligence has highlighted the urgent need for operational tools capable of effectively responding to current incidents and developing resources that can mitigate catastrophic risks. The 1986 Convention on Early Notification of Nuclear Accidents addressed the issue of radioactive emissions through a notification mechanism, providing an effective and rapid response to a problem that posed a high risk at the time; for this reason, it was used as a reference. From a regulatory response perspective, the convention for early notification of AI incidents is proposed a notification mechanism designed to address the shortcomings identified in current regulations.The proposed treaty consists of 18 articles structured to provide an operational and legally binding framework that ensures prompt notification, the effective flow of information, and a clear path for coordinated action among developers, infrastructure operators, and governments

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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.

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  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.
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  1. I would have liked to have seen more effort put into the related work as I believe there are numerous proposals for mechanisms to coordinate internationally on incident reporting. That said, the proposed framework here benefits from being relatively simple.

  2. Overall this submission presented a promising idea clearly and concisely. Well done!

    The authors correctly identify a gap in current incident reporting requirements, which is that they do not appear meet the severity thresholds of existing regulatory frameworks. They propose addressing this gap by adapting the Convention on Early Notification of a Nuclear Accident to AI incidents. In and of itself, this seems like a very interesting idea!

    One of the most important questions here is what the definition of an AI incident should be, and I would have liked to see a bit more discussion on this point. The authors define AI incidents as either containment issues or monitor evasion. It would be useful to explain this choice and its tradeoffs. Could the definition trigger reporting too often? Could it miss other incidents, such as those involving bioterrorism? Defining which incidents warrant reporting is a difficult question, and one worth exploring further.

    The comparison between nuclear and AI incidents could also be developed. How do these incidents differ, and what might those differences mean for the effectiveness of a similar convention for AI?

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Cite this project

@misc{antolinez2026convention,
  title = {{CONVENTION FOR EARLY NOTIFICATION OF AI INCIDENTS.}},
  author = {Tomas Antolinez and Mariana Zuluaga Abril},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/convention-for-early-notification-of-ai-incidents-x055}},
  url = {https://apartresearch.com/sprints/projects/convention-for-early-notification-of-ai-incidents-x055}
}

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