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Sprint projectNov 2, 2025Barcelona

System Dynamics Game-Theoretic Model of the AI Development Race

Ariel Gil · Team System Dynamics BCN

Submitted to The AI Forecasting Hackathon. Sprint projects are early-stage work by participants, not Apart Research publications.

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A Game theoretic / System Dynamics model of the race dynamics of the US, China, and EU, as a follow up to the Armstrong et al. (2016) paper “Racing to the Precipice”. We find preliminary results where knowledge of competitor capabilities delays the decision to race, contradicting the preceding paper.

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Does the project meaningfully advance AI timeline prediction and capability forecasting? Does it clearly connect to measurable indicators of AI progress (compute, benchmarks, economic impacts, automation milestones)? Does it build on or challenge existing forecasting frameworks like biological anchors, scaling laws, or scenario planning? Does it offer novel methodologies, data sources, or empirical insights that could improve forecast accuracy? Is it grounded in observable trends rather than pure speculation?

Does this project inform critical decisions about AI development and preparedness? Does it help identify key uncertainties, decision points, or early warning indicators? How well does the project connect technical metrics to real-world impacts and policy needs? Could the output guide resource allocation, safety research priorities, or regulatory timelines? Does it reduce uncertainty around transformative AI milestones or capability emergence?

Is the project methodologically rigorous, reproducible, and technically sound? Is the forecasting approach well-calibrated with appropriate uncertainty quantification? Are the data sources, assumptions, and limitations clearly documented? Does the project demonstrate sound statistical methodology and honest treatment of model uncertainties? Would the tool, model, or framework be useful for ongoing forecasting efforts, research planning, or policy analysis?

  1. This is a very exciting topic, I’m glad to see an extension of Armstrong et al. 's model to make it more dynamic.

    Some more interpretation of the results would be beneficial - I found it difficult to get useful takeaways from this by looking at the plots, and the current analysis a bit scant.

    Assuming the EU as a serious actor in AI development is a bit odd, and would warrant some more justification. I’d also be excited to see a dynamic simulation of just the US and China (two actors).

    Future work could explore how enabling aggressive actions could change the outcome. For example, currently, the model doesn’t take into account the possibility of sabotage of others’ AI projects.

  2. I think this is really exciting work that addresses a concrete risk scenario of the AI arms race. The simulation setup seems sound overall. You could possibly look into further exploring how robust your findings/conclusions are against the hyper parameters used, as well as going further into what has changed since the Armstrong (2016) paper.

Cite this project

@misc{gil2025system,
  title = {{System Dynamics Game-Theoretic Model of the AI Development Race}},
  author = {Ariel Gil},
  year = {2025},
  month = nov,
  note = {Submitted to The AI Forecasting Hackathon, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/system-dynamics-gametheoretic-model-of-the-ai-development-race-dqe3}},
  url = {https://apartresearch.com/sprints/projects/system-dynamics-gametheoretic-model-of-the-ai-development-race-dqe3}
}

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