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A number of leading AI companies, including OpenAI, Google DeepMind, andAnthropic, have the stated goal of building artificial general intelligence(AGI) - AI systems that achieve or exceed human performance across a wide rangeof cognitive tasks. In pursuing this goal, they may develop and deploy AIsystems that pose particularly significant risks. While they have already takensome measures to mitigate these risks, best practices have not yet emerged. Tosupport the identification of best practices, we sent a survey to 92 leadingexperts from AGI labs, academia, and civil society and received 51 responses.Participants were asked how much they agreed with 50 statements about what AGIlabs should do. Our main finding is that participants, on average, agreed withall of them. Many statements received extremely high levels of agreement. Forexample, 98% of respondents somewhat or strongly agreed that AGI labs shouldconduct pre-deployment risk assessments, dangerous capabilities evaluations,third-party model audits, safety restrictions on model usage, and red teaming.Ultimately, our list of statements may serve as a helpful foundation forefforts to develop best practices, standards, and regulations for AGI labs.

Towards best practices in AGI safety and governance: A survey of expert opinion