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Fairness in AI (Algorithmic Fairness)

Algorithmic fairness is the study and practice of designing AI systems that do not produce discriminatory or biased outcomes against specific groups. This involves identifying and mitigating different types of biases, such as demographic parity or equal opportunity, that can arise from training data or model design. It's a critical ethical consideration beyond just predictive accuracy.

In plain terms

It's like designing traffic lights to ensure all types of vehicles get a fair turn, not just the most common ones, to prevent some groups from being perpetually stuck.

Why it matters

Ensuring fairness prevents AI from perpetuating or amplifying societal inequalities and builds trust in AI systems.

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