In cases where certain groups are underrepresented in the available data, synthetic data generation can be a valuable tool. Synthetic data, generated by algorithms to simulate real-world phenomena, can help balance datasets and reduce bias by adding diversity where it is lacking. However, it is crucial to ensure that the process of generating synthetic data does not introduce new biases.
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