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Sprint projectJun 13, 2025Dubai, Helsinki and Texas

Power, Proxies and People: Red-Teaming Phase 0 of A Narrow Path to Stop AI Superintelligence

Anusha Asim, Sergei Smirnov, Jackson Paulson · Team Zeropoint

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: Power, Proxies and People: Red-Teaming Phase 0 of A Narrow Path to Stop AI Superintelligence

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This project involved a red team analysis of Phase 0 of A Narrow Path, a foundational AI governance framework aimed at preventing the emergence of artificial superintelligence (ASI). The analysis critically examined five key Phase 0 policies: (1) a total ban on AI systems improving other AI systems, (2) a licensing system for advanced AI development, (3) thresholds for detecting general intelligence, (4) global governance through institutions like GUARD and IASC, and (5) the absence of behavioral influence monitoring.

Using thematic critiques, historical analogies, and a quantitative simulation of regulatory capture, the red team identified major weaknesses in both policy design and enforcement. Key vulnerabilities include the impracticality of a blanket AI-on-AI improvement ban, the risk of AI manipulating human cognition, the susceptibility of licensing regimes to corruption and monopolization, inadequate metrics for identifying general intelligence, and the marginalization of the Global South in governance structures.

The project concluded with several recommendations: adopting a risk-tiered approach to AI improvement, implementing behavioral influence audits, reforming licensing to prevent monopolies, investing in intelligence measurement science, and establishing more inclusive, globally representative institutions to coordinate AI safety efforts.

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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 threat identified of AIs influencing humans is an interesting one. Seems like it would be good if we considered that more.

    Funding intelligence metrology seems like a good suggestion.

    Discussion of possible stifling of innovation and international power dynamics seem orthogonal to the question of how to prevent superintelligence for 20 years, and the latter is to a large extent addressed in our specific formulation of GUARD. E.g. the provision of access to the most capable safe AIs to signatory countries.

Cite this project

@misc{asim2025power,
  title = {{Power, Proxies and People: Red-Teaming Phase 0 of A Narrow Path to Stop AI Superintelligence}},
  author = {Anusha Asim and Sergei Smirnov and Jackson Paulson},
  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/power-proxies-and-people-redteaming-phase-0-of-a-narrow-path-to-stop-ai-superintelligence-o0s6}},
  url = {https://apartresearch.com/sprints/projects/power-proxies-and-people-redteaming-phase-0-of-a-narrow-path-to-stop-ai-superintelligence-o0s6}
}

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