Managing extreme AI risks amid rapid progress
Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel,, Trevor Darrell, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai, Shalev-Shwartz, Gillian Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter,, At{\i}l{\i}m G\"une\c{s} Baydin, Sheila McIlraith, Qiqi Gao

TL;DR
This paper discusses the rapid advancement of AI, highlights potential extreme risks including loss of human control, and proposes a comprehensive plan combining technical and governance strategies to mitigate these risks.
Contribution
It provides a detailed analysis of extreme AI risks and introduces a comprehensive plan integrating technical research with adaptive governance to better manage these dangers.
Findings
AI capabilities are rapidly increasing, raising significant safety concerns.
Current governance mechanisms are insufficient to prevent misuse of advanced AI.
A combined approach of technical and governance measures is essential for risk mitigation.
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,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEthics and Social Impacts of AI · Artificial Intelligence in Healthcare and Education
MethodsFocus
