AI Auditing

The systematic evaluation of an AI system's outputs, behaviour, or training data to identify harms such as bias, stereotype reproduction, or accessibility failures. Audits may be conducted by industry professionals, external researchers, regulators, or end users, and are increasingly used to surface harms experienced by minoritised communities — including disabled people — whose perspectives may be absent from model development.