Learning from Data

Algorithms can learn from data rather than relying on predefined rules, allowing them to adapt and improve over time. However, if biases exist within the training data, such as gender disparities in promotions, the algorithms may inadvertently perpetuate those biases. This learning process mirrors how humans differentiate between concepts, as they observe patterns and refine their understanding through experience.