Mitigation Strategies for Bias

Mitigation strategies for bias are the proactive steps taken to reduce or eliminate unfair prejudices within data, algorithms, and decision-making processes. These strategies involve identifying potential sources of bias, implementing techniques to correct or compensate for them, and continuously monitoring outcomes to ensure fairness and equity. The goal is to create more accurate, reliable, and just results by addressing and minimizing the impact of bias.

Visit the following resources to learn more:

• @article@Addressing AI bias: a human-centric approach to fairness
• @article@When AI Gets It Wrong: Addressing AI Hallucinations and Bias
• @video@Algorithmic Bias in AI: What It Is and How to Fix It