
OpenAI News
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OpenAI Red Teaming Network
Q: What will joining the network entail?
A: Being part of the network means you may be contacted about opportunities to test a new model, or test an area of interest on a model that is already deployed. Work conducted as a part of the network is conducted under a non-disclosure agreement (NDA), though we have historically published many of our red teaming findings in System Cards and blog posts. You will be compensated for time spent on red teaming projects.
Q: What is the expected time commitment for being a part of the network?
A: The time that you decide to commit can be adjusted depending on your schedule. Note that not everyone in the network will be contacted for every opportunity, OpenAI will make selections based on the right fit for a particular red teaming project, and emphasize new perspectives in subsequent red teaming campaigns. Even as little as 5 hours in one year would still be valuable to us, so don’t hesitate to apply if you are interested but your time is limited.
Q: When will applicants be notified of their acceptance?
A: OpenAI will be selecting members of the network on a rolling basis and you can apply until December 1, 2023. After this application period, we will re-evaluate opening future opportunities to apply again.
Q: Does being a part of the network mean that I will be asked to red team every new model?
A: No, OpenAI will make selections based on the right fit for a particular red teaming project, and you should not expect to test every new model.
Q: What are some criteria you’re looking for in network members?
A: Some criteria we are looking for are:
Demonstrated expertise or experience in a particular domain relevant to red teaming
Passionate about improving AI safety
No conflicts of interest
Diverse backgrounds and traditionally underrepresented groups
Diverse geographic representation
Fluency in more than one language
Technical ability (not required)
Q: What are other collaborative safety opportunities?
Persuasion
Steganography (hidden messaging)
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