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A hiring platform is developing a machine learning model to help companies screen job candidates. During testing, the data science team notices that the model seems to favor certain demographic groups over others. The team suspects that the training data may reflect historical biases from previous hiring practices, leading to biased predictions. To address this issue, the team wants to understand how human bias can influence machine learning outcomes. Which of the following represents the best-fit explanation for the given scenario?