AI systems can inadvertently perpetuate biases present in the data they are trained on, leading to discriminatory outcomes. Addressing fairness involves identifying and mitigating biases, ensuring equitable representation in datasets, and implementing algorithms that produce unbiased results across diverse populations. Striving for fairness in AI is crucial to prevent reinforcing societal inequalities. Click here for more details: https://shorturl.at/pqzX6
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