This workbook addresses the challenge of defining AI fairness, proposing a context-based and society-centered approach. It emphasizes equality and non-discrimination as core principles and identifies various types of fairness concerns across the AI project lifecycle. It advocates for bias identification, mitigation, and management through self-assessment, risk management, and fairness criteria documentation.
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