Algorithmic Bias: Algorithmic bias refers to the tendency of algorithms to produce discriminatory or unfair results due to biases in the data or design.
Data Bias: Data bias occurs when the data used for training machine learning models is unrepresentative or contains inherent biases.
Fairness in AI: Fairness in AI focuses on developing algorithms and systems that avoid discrimination and ensure equitable outcomes for all individuals.