Ethical Considerations in AI: Bias and Fairness
As AI systems become more pervasive, it is crucial to address ethical concerns around bias and fairness. Machine learning models can reflect and amplify societal biases if their training data is unbalanced or discriminatory. Developers and organizations must implement rigorous testing, diverse datasets, and transparent decision-making processes to mitigate bias and ensure equitable outcomes for all users.
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