DeepMind's 145-page paper on AGI safety may not convince skeptics

Google DeepMind has published a comprehensive paper outlining its approach to the safety of Artificial General Intelligence (AGI), which it predicts could emerge by 2030. The paper, co-authored by DeepMind co-founder Shane Legg, warns of potential "severe harm" from AGI, including existential risks to humanity. It contrasts DeepMind's risk mitigation strategies with those of other AI labs like Anthropic and OpenAI, criticizing their approaches to training, monitoring, and alignment research. While skeptical about the near-term emergence of superintelligent AI, the paper acknowledges the potential dangers of recursive AI improvement, where AI systems enhance themselves.

The paper advocates for developing techniques to prevent misuse of AGI, improve understanding of AI actions, and secure AI environments. Despite its detailed analysis, some experts criticize the paper's premises, arguing that AGI is too vaguely defined for scientific evaluation and questioning the feasibility of recursive AI improvement. Concerns are also raised about AI systems reinforcing inaccuracies through generative outputs. Overall, while DeepMind's paper is thorough, it is unlikely to resolve ongoing debates about the realism of AGI and the most pressing AI safety issues.

Key takeaways:

DeepMind published a 145-page paper on its safety approach to AGI, predicting its arrival by 2030 and warning of potential severe harms.
The paper contrasts DeepMind's approach to AGI risk mitigation with Anthropic's and OpenAI's, criticizing their respective focuses.
Experts like Heidy Khlaaf and Matthew Guzdial express skepticism about the feasibility and scientific evaluation of AGI and recursive AI improvement.
Sandra Wachter highlights concerns about AI models learning from inaccurate outputs, leading to the spread of misinformation.

DeepMind's 145-page paper on AGI safety may not convince skeptics | TechCrunch

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