A discussion on 12 US AI policy ideas to improve outcomes, covering topics such as governance, advanced AI regulation, harm tracking, and emergency shutdown mechanisms.
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Quick takeaways
Control export of Frontier AI models to limit risks.
Enforce strict information security and safety testing for AI models.
Deep dives
Control the export of Frontier AI models
One key policy recommendation is to control the export of Frontier AI models that possess highly general capabilities. This involves restricting the export of models trained with a significant compute budget, contributing to limiting the spread of models posing high risks. Moreover, regulating API access can prevent the generation of optimized datasets for training risky models efficiently, enhancing governance over AI proliferation.
Implement cybersecurity measures for AI models
Another crucial suggestion involves enforcing stringent information security requirements for Frontier AI models. This includes cyber, physical, and personnel security measures during model training to prevent unintended dissemination of dangerous models. Additionally, introducing rigorous safety testing and evaluation, potentially overseen by independent auditors, aims to enhance safety protocols for AI systems and reduce risks.
About two years ago, I wrote that “it’s difficult to know which ‘intermediate goals’ [e.g. policy goals] we could pursue that, if achieved, would clearly increase the odds of eventual good outcomes from transformative AI.” Much has changed since then, and in this post I give an update on 12 ideas for US policy goals[1]Many […]
The original text contained 7 footnotes which were omitted from this narration.