mlsanityData to 7 Oct 2026

Superintelligence Strategy: Expert Version

arXiv 2503.05628 ↗First posted 7 Mar 2025cs.CY cs.AIcited by 6

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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.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 16 of its 53 references that are in the map. First posted on arXiv 7 Mar 2025.

Builds on

16 of 53 references.

References · 16

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  3. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  4. 2023Representation Engineering: A Top-Down Approach to AI Transparencycited by 1,239
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4 more
  1. 2024Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?cited by 56
  2. 2024Adversaries Can Misuse Combinations of Safe Modelscited by 31
  3. 2023Natural Selection Favors AIs over Humanscited by 24
  4. 2024Verification methods for international AI agreementscited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 2.

6 papers.