In what ways can biases in machine learning models, such as those found in language generation systems like GPT-2, perpetuate societal prejudices, and what measures can be taken to mitigate these biases?

Biases in machine learning models, particularly in language generation systems like GPT-2, can significantly perpetuate societal prejudices. These biases often stem from the data used to train these models, which can reflect existing societal stereotypes and inequalities. When such biases are embedded in machine learning algorithms, they can manifest in various ways, leading to the

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