mlsanityData to 14 Oct 2026

The human biological advantage over AI

arXiv 2509.04130 ↗First posted 4 Sep 2025cs.AI cs.CYcited by 0

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Abstract (arXiv)

Recent advances in AI raise the possibility that AI systems will one day be able to do anything humans can do, only better. If artificial general intelligence (AGI) is achieved, AI systems may be able to understand, reason, problem solve, create, and evolve at a level and speed that humans will increasingly be unable to match, or even understand. These possibilities raise a natural question as to whether AI will eventually become superior to humans, a successor "digital species", with a rightful claim to assume leadership of the universe. However, a deeper consideration suggests the overlooked differentiator between human beings and AI is not the brain, but the central nervous system (CNS), providing us with an immersive integration with physical reality. It is our CNS that enables us to experience emotion including pain, joy, suffering, and love, and therefore to fully appreciate the consequences of our actions on the world around us. And that emotional understanding of the consequences of our actions is what is required to be able to develop sustainable ethical systems, and so be fully qualified to be the leaders of the universe. A CNS cannot be manufactured or simulated; it must be grown as a biological construct. And so, even the development of consciousness will not be sufficient to make AI systems superior to humans. AI systems may become more capable than humans on almost every measure and transform our society. However, the best foundation for leadership of our universe will always be DNA, not silicon.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 47 references that are in the map. First posted on arXiv 4 Sep 2025.

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References · 3

  1. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  2. 2022Forecasting AI Progress: Evidence from a Survey of Machine Learning Researcherscited by 7
  3. 2019The scientific case for brain simulationscited by 3

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