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Answer :
Fairness measures in AI product development ensure ethical and unbiased outcomes, prevent discrimination, and promote equity.
These measures are designed to prevent systemic discrimination and promote equity in decision-making processes. Fairness in AI also enhances transparency and accountability, helping to build trust among users by demonstrating that the system operates without unfair bias. Additionally, by incorporating fairness measures, developers can create more inclusive products that better serve diverse populations and comply with regulatory standards.
An example of fairness measures includes implementing algorithms that identify and mitigate biases in training data, or employing diverse data sets to ensure broad representation. By prioritizing fairness, AI systems can achieve more equitable outcomes in applications ranging from hiring practices to loan approvals.
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