Labeling bias occurs when the labels assigned to data points in a dataset are influenced by subjective opinions, cultural norms, or systemic inequalities, leading to skewed representations of certain groups. This bias can affect the performance and fairness of machine learning models by causing them to learn from and perpetuate these biased labels, which ultimately affects decision-making processes and outcomes.
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