The article examines whether increasing automation of AI research and development could trigger an intelligence explosion, compressing years of progress into months. It reviews preliminary evidence suggesting such acceleration is possible, discusses potential benefits and extreme risks—including loss of control over superhuman AI and erosion of checks on power—and calls for urgent policy action. The authors argue that, despite uncertainties, the high stakes demand serious attention and proactive measures.
By Alan Chan, Christoph Winter, Andrew Barto, Jakub Pachocki, Geoffrey Hinton, Eric Horvitz, Yoshua Bengio, Dawn Song, Jack Clark, Hilary Greaves, Anton Korinek, Samuel Hammond, Thore Graepel, Ben Bariach, Philip H. S. Torr, Sheila A. McIlraith, Jeff Clune, Sam Manning, Girish Sastry, Tom Davidson, Daniel Eth, S\"oren Mindermann
arXiv:2602. 16065v2 Announce Type: replace-cross Abstract: As artificial intelligence (AI)-generated content proliferates, models are increasingly trained on their own outputs, risking progressive degradation or collapse.
By Kevin Wang, Hongqian Niu, Didong Li