mlsanityData to 13 Oct 2026

Strategic Insights from Simulation Gaming of AI Race Dynamics

arXiv 2410.03092 ↗First posted 4 Oct 2024cs.CY cs.AIcited by 3

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Abstract (arXiv)

We present insights from "Intelligence Rising", a scenario exploration exercise about possible AI futures. Drawing on the experiences of facilitators who have overseen 43 games over a four-year period, we illuminate recurring patterns, strategies, and decision-making processes observed during gameplay. Our analysis reveals key strategic considerations about AI development trajectories in this simulated environment, including: the destabilising effects of AI races, the crucial role of international cooperation in mitigating catastrophic risks, the challenges of aligning corporate and national interests, and the potential for rapid, transformative change in AI capabilities. We highlight places where we believe the game has been effective in exposing participants to the complexities and uncertainties inherent in AI governance. Key recurring gameplay themes include the emergence of international agreements, challenges to the robustness of such agreements, the critical role of cybersecurity in AI development, and the potential for unexpected crises to dramatically alter AI trajectories. By documenting these insights, we aim to provide valuable foresight for policymakers, industry leaders, and researchers navigating the complex landscape of AI development and governance.

Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). Builds on 11 of its 113 references that are in the map. First posted on arXiv 4 Oct 2024.

Builds on

11 of 113 references.

References · 11

  1. 2020Language Models are Few-Shot Learnerscited by 32,320
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  7. 2023TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AIcited by 26
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  9. 2024AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Researchcited by 13
  10. 2019Exploring AI Futures Through Role Playcited by 3
  11. 2020Forecasting AI Progress: A Research Agendacited by 3

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.