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Main Authors: Cappelen, Herman, Dever, Josh, Hawthorne, John
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2405.19832
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author Cappelen, Herman
Dever, Josh
Hawthorne, John
author_facet Cappelen, Herman
Dever, Josh
Hawthorne, John
contents This paper presents an argument that certain AI safety measures, rather than mitigating existential risk, may instead exacerbate it. Under certain key assumptions - the inevitability of AI failure, the expected correlation between an AI system's power at the point of failure and the severity of the resulting harm, and the tendency of safety measures to enable AI systems to become more powerful before failing - safety efforts have negative expected utility. The paper examines three response strategies: Optimism, Mitigation, and Holism. Each faces challenges stemming from intrinsic features of the AI safety landscape that we term Bottlenecking, the Perfection Barrier, and Equilibrium Fluctuation. The surprising robustness of the argument forces a re-examination of core assumptions around AI safety and points to several avenues for further research.
format Preprint
id arxiv_https___arxiv_org_abs_2405_19832
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AI Safety: A Climb To Armageddon?
Cappelen, Herman
Dever, Josh
Hawthorne, John
Artificial Intelligence
This paper presents an argument that certain AI safety measures, rather than mitigating existential risk, may instead exacerbate it. Under certain key assumptions - the inevitability of AI failure, the expected correlation between an AI system's power at the point of failure and the severity of the resulting harm, and the tendency of safety measures to enable AI systems to become more powerful before failing - safety efforts have negative expected utility. The paper examines three response strategies: Optimism, Mitigation, and Holism. Each faces challenges stemming from intrinsic features of the AI safety landscape that we term Bottlenecking, the Perfection Barrier, and Equilibrium Fluctuation. The surprising robustness of the argument forces a re-examination of core assumptions around AI safety and points to several avenues for further research.
title AI Safety: A Climb To Armageddon?
topic Artificial Intelligence
url https://arxiv.org/abs/2405.19832