Fairness in AI

Fairness in AI refers to the principle that artificial intelligence systems should operate without bias, discrimination, or inequality, ensuring equitable treatment for all individuals regardless of their characteristics such as race, gender, age, or socioeconomic status. It involves assessing and mitigating the potential biases present in AI algorithms, training data, and the deployment processes of AI systems. The goal is to promote justice and inclusivity in AI outcomes, ensuring that these technologies do not reinforce existing prejudices or create new forms of discrimination. Fairness in AI encompasses various approaches to evaluation and intervention, including statistical measures of fairness, algorithmic adjustments, and ongoing monitoring of AI systems' impact on diverse populations. It is a critical area of focus, particularly as AI is increasingly used in high-stakes situations such as hiring, law enforcement, and healthcare.