Bias Mitigation

Bias mitigation involves identifying and reducing unfair or unintentional prejudices in algorithms and data. When developing AI systems, biases can lead to unfair treatment of certain groups based on race, gender, or other factors. Mitigation techniques aim to make these systems more equitable by adjusting data or models to minimize these biases. This process helps ensure that AI decisions are more just, accurate, and inclusive, promoting fairness across diverse populations.