Maya Chen explores how machine learning systems develop biases nobody programmed—through optimization dynamics, noisy feedback loops, and architectural choices. She reveals why invisible weights matter more than explicit ones, affecting real decisions about content, jobs, and loans, and explains how to make hidden preferences visible and contestable.
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This content was created in partnership and with the help of Artificial Intelligence AI
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