Bias in algorithms can occur due to several factors: 1. Data Bias: If the training data itself is biased, the algorithm will likely replicate those biases. For example, if historical hiring data favors a particular demographic, the algorithm will continue to favor that group. 2. Algorithm Design: The design of the algorithm may inherently favor certain outcomes. For instance, certain metrics used in a credit scoring algorithm might disproportionately disadvantage specific groups. 3. Human Intervention: Biases can also be introduced through human intervention, where individuals might consciously or unconsciously incorporate their biases into the algorithm.