Fairness and Bias in AI

Fairness and bias in AI refer to how these systems can unintentionally favor or discriminate against certain groups or individuals. AI learns from large data sets, which may contain historical inequalities or prejudices. If not carefully managed, AI decisions—like screening jobs or approving loans—might reinforce these biases, leading to unfair outcomes. Ensuring fairness involves designing AI that treats people equitably, while addressing bias means identifying and reducing prejudiced patterns in data and algorithms. It’s about making AI tools more just and unbiased, so they serve everyone fairly.