Our Mission
Bias Mirror was created to help organizations understand and test how generative AI systems handle identity representation, especially when demographic attributes matter for trust, equity, and compliance. We provide structured evaluation assets that help teams find and quantify identity drift, demographic bias, and intersectional failure modes before deployment.
Why This Matters
The Bias Mirror project was born from hands-on use of AI tools where repeated identity distortion — such as unexpected changes in skin tone, facial structure, or overall likeness — was observed across multiple platforms despite identical prompts. These patterns weren’t random; they highlighted gaps in how models preserve individual identity attributes.
This insight led to the development of a structured evaluation dataset designed not just to show the problem, but to measure it, test it, and provide a tool that development and governance teams can use with confidence.