Managing extreme AI risks amid rapid progress

Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel +20 more
10/26/2023
cs.CYcs.AIcs.CL

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Abstract

Artificial Intelligence (AI) is progressing rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI's impact, with risks that include large-scale social harms, malicious uses, and an irreversible loss of human control over autonomous AI systems. Although researchers have warned of extreme risks from AI, there is a lack of consensus about how exactly such risks arise, and how to manage them. Society's response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness, and barely address autonomous systems. In this short consensus paper, we describe extreme risks from upcoming, advanced AI systems. Drawing on lessons learned from other safety-critical technologies, we then outline a comprehensive plan combining technical research and development with proactive, adaptive governance mechanisms for a more commensurate preparation.

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Cite this paper

@article{bengio2023managing,
  title  = {Managing extreme AI risks amid rapid progress},
  author = {Yoshua Bengio and Geoffrey Hinton and Andrew Yao and Dawn Song and Pieter Abbeel and Trevor Darrell and Yuval Noah Harari and Ya-Qin Zhang and Lan Xue and Shai Shalev-Shwartz and Gillian Hadfield and Jeff Clune and Tegan Maharaj and Frank Hutter and Atılım Güneş Baydin and Sheila McIlraith and Qiqi Gao and Ashwin Acharya and David Krueger and Anca Dragan and Philip Torr and Stuart Russell and Daniel Kahneman and Jan Brauner and Sören Mindermann},
  year   = {2023},
  eprint = {2310.17688},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.17688v3}
}

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