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.
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.
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A lawyer for the Wikimedia Foundation has responded to Senator Ted Cruz's accusations of left-wing bias on Wikipedia, attributing the concerns to misunderstandings of the platform's volunteer-driven editing process. Jacob Rogers emphasized that the foundation does not control content and welcomes participation from anyone unhappy with articles. The letter from Cruz demands documents on oversight and bias, but carries no legal weight.