(Sept. 19, 2023)
We’re announcing an open call for the OpenAI Red Teaming Network and invite domain experts interested in improving the safety of OpenAI’s models to join our efforts. We are looking for experts from various fields to collaborate with us in rigorously evaluating and red teaming our AI models. Today, we are launching a more formal effort to build on these earlier foundations, and deepen and broaden our collaborations with outside experts in order to make our models safer. Working with individual experts, research institutions, and civil society organizations is an important part of our process. We see this work as a complement to externally specified governance practices, such as third party audits.
What is the OpenAI Red Teaming Network? The OpenAI Red Teaming Network is a community of trusted and experienced experts that can help to inform our risk assessment and mitigation efforts more broadly, rather than one-off engagements and selection processes prior to major model deployments. Members of the network will be called upon based on their expertise to help red team at various stages of the model and product development lifecycle. Not every member will be involved with each new model or product, and time contributions will be determined with each individual member, which could be as few as 5–10 hours in one year.
Outside of red teaming campaigns commissioned by OpenAI, members will have the opportunity to engage with each other on general red teaming practices and findings. The goal is to enable more diverse and continuous input, and make red teaming a more iterative process. This network complements other collaborative AI safety opportunities including our Researcher Access Program and open-source evaluations.
Why join the OpenAI Red Teaming Network?
This network offers a unique opportunity to shape the development of safer AI technologies and policies, and the impact AI can have on the way we live, work, and interact. By becoming a part of this network, you will be a part of our bench of subject matter experts who can be called upon to assess our models and systems at multiple stages of their deployment.
Seeking diverse expertise
Assessing AI systems requires an understanding of a wide variety of domains, diverse perspectives and lived experiences. We invite applications from experts from around the world and are prioritizing geographic as well as domain diversity in our selection process.
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