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arXiv:2303.16200cs.CY

Natural Selection Favors AIs over Humans

Dan Hendrycks

Abstract

For billions of years, evolution has been the driving force behind the development of life, including humans. Evolution endowed humans with high intelligence, which allowed us to become one of the most successful species on the planet. Today, humans aim to create artificial intelligence systems that surpass even our own intelligence. As artificial intelligences (AIs) evolve and eventually surpass us in all domains, how might evolution shape our relations with AIs? By analyzing the environment that is shaping the evolution of AIs, we argue that the most successful AI agents will likely have undesirable traits. Competitive pressures among corporations and militaries will give rise to AI agents that automate human roles, deceive others, and gain power. If such agents have intelligence that exceeds that of humans, this could lead to humanity losing control of its future. More abstractly, we argue that natural selection operates on systems that compete and vary, and that selfish species typically have an advantage over species that are altruistic to other species. This Darwinian logic could also apply to artificial agents, as agents may eventually be better able to persist into the future if they behave selfishly and pursue their own interests with little regard for humans, which could pose catastrophic risks. To counteract these risks and evolutionary forces, we consider interventions such as carefully designing AI agents' intrinsic motivations, introducing constraints on their actions, and institutions that encourage cooperation. These steps, or others that resolve the problems we pose, will be necessary in order to ensure the development of artificial intelligence is a positive one.

arXiv comments
An explainer video corresponding to the paper is available at https://www.youtube.com/watch?v=48h-ySTggE8
Journal reference
DOI
Subjects
cs.CYComputers and Society cs.AIArtificial Intelligence cs.LGMachine Learning cs.NENeural and Evolutionary Computing

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Linked by 2 identifiable commenters in 4 comments across 3 threads, from Apr 2023 to Jun 2023. Found in 5 HN submissions from Mar 2023 to Sep 2026. Open submission discussions.

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Discussed in comments3 threads

    • This is a short version of a much longer piece: https://arxiv.org/abs/2303.16200 The long piece is still aimed at a non-expert audience and can be read incrementally. The author takes a lot of care to attempt to justify his claims about the application of neo-Darwinian…

      da39a3eeView on HNParent context

    • Could you list some of the assumptions that you're skeptical about? I think that would help stress-test the author's claims about applying evolutionary theory to AI. Note that the full version of the puece is https://arxiv.org/abs/2303.16200.

      da39a3eeView on HNParent context

    • This article is a shortened version of the much longer (but still written for a non-expert audience) paper: https://arxiv.org/abs/2303.16200

      da39a3eeView on HNParent context

    • > I find LLMs fascinating, and do not perceive them as an existential threat What do you think of this? http://arxiv.org/abs/2303.16200

      blackbear_View on HNParent context

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