Another pressing concern is the potential for AI systems to perpetuate bias and discrimination. AI algorithms are often trained on datasets that reflect existing social and cultural biases, which can result in unfair outcomes and perpetuate systemic inequalities. For example, facial recognition systems have been criticized for their inaccuracy in identifying people of color, while AI-powered hiring tools have been shown to favor male candidates over female ones. To address this issue, developers must prioritize transparency, accountability, and fairness in AI system design, ensuring that algorithms are audited and tested for bias.
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