mlsanityData to 7 Oct 2026

Cooperative Evolutionary Pressure and Diminishing Returns Might Explain the Fermi Paradox: On What Super-AIs Are Like

arXiv 2404.03685 ↗First posted 1 Apr 2024physics.soc-ph cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

With an evolutionary approach, the basis of morality can be explained as adaptations to problems of cooperation. With 'evolution' taken in a broad sense, AIs that satisfy the conditions for evolution to apply will be subject to the same cooperative evolutionary pressure as biological entities. Here the adaptiveness of increased cooperation as material safety and wealth increase is discussed -- for humans, for other societies, and for AIs. Diminishing beneficial returns from increased access to material resources also suggests the possibility that, on the whole, there will be no incentive to for instance colonize entire galaxies, thus providing a possible explanation of the Fermi paradox, wondering where everybody is. It is further argued that old societies could engender and eventually give way to super-AIs, since it is likely that super-AIs are feasible, and fitter. Closing is an aside on effective ways for morals and goals to affect life and society, emphasizing environments, cultures, and laws, and exemplified by how to eat. 'Diminishing returns' is defined, as less than roots, the inverse of infeasibility. It is also noted that there can be no exponential colonization or reproduction, for mathematical reasons, as each entity takes up a certain amount of space. Appended are an algorithm for colonizing for example a galaxy quickly, models of the evolution of cooperation and fairness under diminishing returns, and software for simulating signaling development.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 550 references that are in the map. First posted on arXiv 1 Apr 2024.

Builds on

12 of 550 references.

References · 12

  1. 2017Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithmcited by 723
  2. 2017Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypescited by 251
  3. 2023The science of fake newscited by 94
  4. 2014Growth rates of modern science: A bibliometric analysis based on the number of publications and cited referencescited by 63
  5. 2024Thousands of AI Authors on the Future of AIcited by 48
  6. 2017When Will AI Exceed Human Performance? Evidence from AI Expertscited by 41
  7. 2023Embedding Democratic Values into Social Media AIs via Societal Objective Functionscited by 25
  8. 2021Mathematical foundations of moral preferencescited by 15
  9. 2022Forecasting AI Progress: Evidence from a Survey of Machine Learning Researcherscited by 7
  10. 2019Forecasting Transformative AI: An Expert Surveycited by 4
  11. 2021Emergence of Self-Reproducing Metabolisms as Recursive Algorithms in an Artificial Chemistrycited by 3
  12. 2017Expert and Non-Expert Opinion about Technological Unemploymentcited by 1

Built on by

Not cited yet.