# Superintelligence Strategy: Expert Version

arXiv: https://arxiv.org/abs/2503.05628 · HTML: https://mlsanity.com/paper/2503.05628/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 53 references that are in the map.
- First posted on arXiv 7 Mar 2025.

## Builds on (most cited first, 16 of 16)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2204.05862/) (2022)
- [Constitutional AI: Harmlessness from AI Feedback](https://mlsanity.com/paper/2212.08073/) (2022)
- [Representation Engineering: A Top-Down Approach to AI Transparency](https://mlsanity.com/paper/2310.01405/) (2023)
- [Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2307.15217/) (2023)
- [Improving Alignment and Robustness with Circuit Breakers](https://mlsanity.com/paper/2406.04313/) (2024)
- [Unsolved Problems in ML Safety](https://mlsanity.com/paper/2109.13916/) (2021)
- [An Overview of Catastrophic AI Risks](https://mlsanity.com/paper/2306.12001/) (2023)
- [Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming](https://mlsanity.com/paper/2501.18837/) (2025)
- [Observational Scaling Laws and the Predictability of Language Model Performance](https://mlsanity.com/paper/2405.10938/) (2024)
- [Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs](https://mlsanity.com/paper/2502.08640/) (2025)
- [Forecasting Future World Events with Neural Networks](https://mlsanity.com/paper/2206.15474/) (2022)
- [Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?](https://mlsanity.com/paper/2407.21792/) (2024)
- [Adversaries Can Misuse Combinations of Safe Models](https://mlsanity.com/paper/2406.14595/) (2024)
- [Natural Selection Favors AIs over Humans](https://mlsanity.com/paper/2303.16200/) (2023)
- [Verification methods for international AI agreements](https://mlsanity.com/paper/2408.16074/) (2024)

## Built on by (most cited first, 7 of 7)

- [From AGI to ASI](https://mlsanity.com/paper/2606.12683/) (2026)
- [Technical Requirements for Halting Dangerous AI Activities](https://mlsanity.com/paper/2507.09801/) (2025)
- [Against racing to AGI: Cooperation, deterrence, and catastrophic risks](https://mlsanity.com/paper/2507.21839/) (2025)
- [AI Alignment Strategies from a Risk Perspective: Independent Safety Mechanisms or Shared Failures?](https://mlsanity.com/paper/2510.11235/) (2025)
- [Threshold Crossings as Tail Events for Catastrophic AI Risk](https://mlsanity.com/paper/2503.18979/) (2025)
- [AI Researchers Must Help Lead Arms Control to Mitigate Military AI Risks](https://mlsanity.com/paper/2606.11533/) (2026)
- [The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AI](https://mlsanity.com/paper/2608.05173/) (2026)

## Abstract (arXiv)

Rapid advances in AI are beginning to reshape national security. Destabilizing AI developments could rupture the balance of power and raise the odds of great-power conflict, while widespread proliferation of capable AI hackers and virologists would lower barriers for rogue actors to cause catastrophe. Superintelligence -- AI vastly better than humans at nearly all cognitive tasks -- is now anticipated by AI researchers. Just as nations once developed nuclear strategies to secure their survival, we now need a coherent superintelligence strategy to navigate a new period of transformative change. We introduce the concept of Mutual Assured AI Malfunction (MAIM): a deterrence regime resembling nuclear mutual assured destruction (MAD) where any state's aggressive bid for unilateral AI dominance is met with preventive sabotage by rivals. Given the relative ease of sabotaging a destabilizing AI project -- through interventions ranging from covert cyberattacks to potential kinetic strikes on datacenters -- MAIM already describes the strategic picture AI superpowers find themselves in. Alongside this, states can increase their competitiveness by bolstering their economies and militaries through AI, and they can engage in nonproliferation to rogue actors to keep weaponizable AI capabilities out of their hands. Taken together, the three-part framework of deterrence, nonproliferation, and competitiveness outlines a robust strategy to superintelligence in the years ahead.