As AI Spreads, Urgent Action Needed to Prevent Embedded Biases from Causing Harm
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AI models can reflect and amplify existing human biases, leading to discrimination in areas like hiring, healthcare, and criminal justice.
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Biased AI poses a major threat as its adoption grows across industries, with potentially devastating societal impacts.
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Examples include Amazon's recruiting algorithm discriminating against women and Microsoft's facial recognition software assigning more negative emotions to Black males.
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Mitigating bias requires accountability and oversight across the AI model development lifecycle, from problem framing to data collection to testing.
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Global coordination is needed on AI governance frameworks to ensure new technologies align with ethical values and prevent marginalized groups from being further disadvantaged.