Our Collective Mission
The fight for fair access to work is not new, but the ground it is fought on is changing.
Hiring decisions that were once made by people are increasingly made by AI. These systems now determine who gets seen and who doesn't, at a scale no recruiter ever could.
The organizations that have spent decades opening doors for their communities built that expertise for a world of human decisions, but none have a way into the world of AI.
Warden is changing that. We bring the communities that are protected by law into the testing of the AI systems themselves.
What is a Community Data Partner?
A Community Data Partner is an organization that represents a specific group of workers.
They contribute data, consented by their members, along with expertise on how bias shows up for the people they serve.
That data and expertise shape Warden's test datasets and auditing methodology, so bias testing effectively reflects the candidates being assessed.
The result is that the people they represent stop being invisible in how AI hiring systems are tested.
The Program
Community Data Partners work with Warden in three ways: data, insight, and validation. Together this covers representative data, how bias affects the community, and how well our testing reflects it.
Partners contribute candidate data from the communities they serve, such as resumes and career histories. It comes with consent and with known demographics, which is what makes it usable for bias testing.
Partners share what bias looks like for the communities they support. They bring lived experience to the program, and insight is provided through focus groups and joint research projects with their community.
Partners review Warden's bias detection test data, including the demographic markers used in it, and feedback on how realistic and effective it is.
Become a Community Data Partner
Becoming a Community Data Partner is an opportunity to ensure your community is accurately represented in AI auditing, helping identify and address AI hiring disparities earlier to build a more trustworthy and fair ecosystem.
