AI algorithms used in creating art often rely on large datasets for training. If these datasets contain biases, such as gender, racial, or cultural biases, the AI-generated art may inadvertently reflect or perpetuate those biases. It is crucial to address and mitigate biases in training data to ensure that AI-generated art promotes fairness, inclusivity, and avoids reinforcing discriminatory or harmful stereotypes.
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