# Strategic Insights from Simulation Gaming of AI Race Dynamics

arXiv: https://arxiv.org/abs/2410.03092 · HTML: https://mlsanity.com/paper/2410.03092/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 113 references that are in the map.
- First posted on arXiv 4 Oct 2024.

## Builds on (most cited first, 11 of 11)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [On the Opportunities and Risks of Foundation Models](https://mlsanity.com/paper/2108.07258/) (2021)
- [An Overview of Catastrophic AI Risks](https://mlsanity.com/paper/2306.12001/) (2023)
- [Foundational Challenges in Assuring Alignment and Safety of Large Language Models](https://mlsanity.com/paper/2404.09932/) (2024)
- [Thousands of AI Authors on the Future of AI](https://mlsanity.com/paper/2401.02843/) (2024)
- [TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI](https://mlsanity.com/paper/2306.06924/) (2023)
- [The Transformative Potential of Artificial Intelligence](https://mlsanity.com/paper/1912.00747/) (2019)
- [AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research](https://mlsanity.com/paper/2405.01859/) (2024)
- [Exploring AI Futures Through Role Play](https://mlsanity.com/paper/1912.08964/) (2019)
- [Forecasting AI Progress: A Research Agenda](https://mlsanity.com/paper/2008.01848/) (2020)

## Built on by (most cited first, 3 of 3)

- [Embodied AI: Emerging Risks and Opportunities for Policy Action](https://mlsanity.com/paper/2509.00117/) (2025)
- [Falling Behind Drives Unsafe Development in an Idealised AI Race Experiment](https://mlsanity.com/paper/2607.26034/) (2026)
- [Dark Speculation: Combining Qualitative and Quantitative Understanding in Frontier AI Risk Analysis](https://mlsanity.com/paper/2511.21838/) (2025)

## 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.