Bias
AI cancer tools can infer patient demographics, raising bias concerns
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Artificial intelligence systems designed to diagnose cancer from tissue slides are learning to infer patient demographics, leading to uneven diagnostic performance across racial, gender, and age groups. Researchers at Harvard Medical School and collaborators identified the problem and developed a method that sharply reduces these disparities, underscoring the need for routine bias checks in medical AI.
A report from the Media Research Center analyzed coverage in the Big Four news apps—Apple News, Google News, Microsoft’s MSN, and Yahoo News—finding a strong preference for left-leaning outlets. The study, covering 106 days from Halloween to Valentine’s Day, showed right-leaning sources receiving minimal visibility. Platforms featured thousands of stories, with disparities in outlet representation.
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New research shows that personalized algorithms on platforms like YouTube can hinder learning by limiting exposure to information, even for those with no prior knowledge. Participants in a study explored less material, drew incorrect conclusions, and felt overly confident in their errors. The findings highlight risks for biased understanding in everyday digital interactions.