What type of audit ensures that AI systems work without bias or discrimination?

Bias audits are specifically designed to assess AI systems for fairness and ensure that they operate without biases or discrimination. These audits focus on identifying, measuring, and mitigating any unintended biases that may be present in algorithms or models, thereby safeguarding against outcomes that can affect individuals or groups unfairly based on race, gender, ethnicity, or other characteristics. By conducting bias audits, organizations can better understand how their AI systems make decisions and take corrective actions to promote equity.

Performance audits, while important, primarily evaluate how well an AI system performs against defined benchmarks, not necessarily its fairness. Financial audits focus on the accuracy of financial records and compliance with accounting principles, which is not relevant to evaluating bias in AI. Compliance audits are aimed at ensuring adherence to laws, regulations, and policies, which may touch on bias but do not specifically concentrate on identifying or measuring discrimination or bias in AI outputs.