Bias

Bias measures how much systematic error an estimator makes on average. If a method repeatedly gives results that are wrong in the same direction, it is said to be biased. In statistics, this concept is essential for assessing the reliability of measurement and estimation methods. In machine learning, bias also relates to how much a model oversimplifies or systematically misses the true structure of the problem. For that reason, bias is important not only in ethical discussions, but also in technical model quality.