Towards best practices in AGI safety and governance: A survey of expert
  opinion
A number of leading AI companies, including OpenAI, Google DeepMind, and
Anthropic, have the stated goal of building artificial general intelligence
(AGI) - AI systems that achieve or exceed human performance across a wide range
of cognitive tasks. In pursuing this goal, they may develop and deploy AI
systems that pose particularly significant risks. While they have already taken
some measures to mitigate these risks, best practices have not yet emerged. To
support the identification of best practices, we sent a survey to 92 leading
experts from AGI labs, academia, and civil society and received 51 responses.
Participants were asked how much they agreed with 50 statements about what AGI
labs should do. Our main finding is that participants, on average, agreed with
all of them. Many statements received extremely high levels of agreement. For
example, 98% of respondents somewhat or strongly agreed that AGI labs should
conduct 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 for
efforts to develop best practices, standards, and regulations for AGI labs.
6461cc525ea1bc9a9da95171
Jonas Schuett
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2023-05-15T13:03:22.707Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/2FpECzBD8aOiUagRlCnVZ.jpeg
Jonas Schuett
user
jonasschuett
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Noemi Dreksler
claimed_verified
2023-05-15T15:28:24.891Z
64623caab438438da3bff220
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/he62MWI9BYT5YyEG5BsIh.png
Noemi Dreksler
user
noemidreksler
6461cc525ea1bc9a9da95173
Markus Anderljung
claimed_verified
2023-05-15T15:28:17.860Z
64624f222a83863b97bda981
/avatars/bd13153c1358d6cdcb7959478ef5f3e1.svg
Markus Anderljung
user
markusanderljung
6461cc525ea1bc9a9da95174
David McCaffary
admin_assigned
2023-05-16T09:55:22.673Z
62862aca504d3770030879df
/avatars/d6184246d8a9ba384bd8e7c9760c5efe.svg
David McCaffary
user
mccaffary
6461cc525ea1bc9a9da95175
Lennart Heim
6461cc525ea1bc9a9da95176
Emma Bluemke
6461cc525ea1bc9a9da95177
Ben Garfinkel
Towards best practices in AGI safety and governance: A survey of expert
  opinion
A number of leading AI companies, including OpenAI, Google DeepMind, and
Anthropic, have the stated goal of building artificial general intelligence
(AGI) - AI systems that achieve or exceed human performance across a wide range
of cognitive tasks. In pursuing this goal, they may develop and deploy AI
systems that pose particularly significant risks. While they have already taken
some measures to mitigate these risks, best practices have not yet emerged. To
support the identification of best practices, we sent a survey to 92 leading
experts from AGI labs, academia, and civil society and received 51 responses.
Participants were asked how much they agreed with 50 statements about what AGI
labs should do. Our main finding is that participants, on average, agreed with
all of them. Many statements received extremely high levels of agreement. For
example, 98% of respondents somewhat or strongly agreed that AGI labs should
conduct 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 for
efforts to develop best practices, standards, and regulations for AGI labs.
Experts agree on a set of risk mitigation practices for AGI labs, including pre-deployment assessments and third-party audits.
AGI labs pre-deployment risk assessments dangerous capabilities evaluations third-party model audits safety restrictions red teaming