One of the central challenges in ethical AI is ensuring fairness across diverse groups. AI systems can inadvertently perpetuate or even amplify existing biases present in training data or design processes. Tackling this challenge involves rigorous testing and evaluation for bias, the development of more inclusive data sets, and the implementation of fairness-aware algorithms. Innovators and ethicists emphasize the importance of sociotechnical approaches that consider both technical and social dimensions in addressing AI fairness.
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