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Sprint projectJun 13, 2025Toronto

Red Teaming A Narrow Path: A Critical Analysis

Shivam Arora

Submitted to Red Teaming A Narrow Path: ControlAI Policy Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: Red Teaming A Narrow Path: A Critical Analysis

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ControlAI has developed "A Narrow Path" - the first comprehensive plan to address extinction risks from Artificial Superintelligence (ASI). In this document we review, critique, and red-team Phase 0: Safety policies of the proposed plan. We found out that these policies are well-intentioned but lack sufficient grounding in technical understanding, resulting in significant gaps in their design and applicability. Our analysis highlights how, even when fully implemented, these policies leave room for strategic evasion that undermines their original purpose.

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Does the analysis realistically assess what government agencies, resources, and expertise would be needed to implement these policies? Are the identified implementation challenges specific and grounded in understanding of how similar policies have worked (or failed) in practice? Does the submission adequately consider bureaucratic, technical, and coordination complexities involved in enforcement? How well does the analysis account for real-world constraints like budget limitations, regulatory capture, and inter-agency coordination?

Does the analysis identify specific ways the policies could fail to prevent ASI development or be circumvented by determined actors? How thoroughly does the submission examine edge cases, loopholes, or unintended consequences that could undermine the 20-year goal? Does the assessment consider different threat models (state actors, rogue researchers, corporate actors) and how policies address each? Are the identified failure modes realistic and significant, or primarily theoretical edge cases?

Does the submission cite relevant historical examples of similar policies (nuclear non-proliferation, export controls, dual-use technology regulation) to support its arguments? Are claims backed by empirical data, documented case studies, or credible expert analysis rather than speculation? How well does the analysis draw lessons from comparable regulatory domains to assess likely outcomes? Does the submission avoid making unsupported assertions about what "would" or "could" happen without evidence?

  1. The discussion on "found systems" may have missed the explanation of the requirement on "direct use": "We similarly introduce the concept of “direct use” so this policy only applies to cases where AIs are playing a key role in the research or development of improving AIs."

    The objection re: AI safety researchers on unauthorized access seems reasonable. I believe it's somewhat addressed in footnote 23, but way too easy to miss.

    The superintelligence ban policy is more a normative & guiding principle than a technical definition - which is hard to do and could be gamed

Cite this project

@misc{arora2025red,
  title = {{Red Teaming A Narrow Path: A Critical Analysis}},
  author = {Shivam Arora},
  year = {2025},
  month = jun,
  note = {Submitted to Red Teaming A Narrow Path: ControlAI Policy Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/red-teaming-a-narrow-path-a-critical-analysis-84oh}},
  url = {https://apartresearch.com/sprints/projects/red-teaming-a-narrow-path-a-critical-analysis-84oh}
}

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