Computer Sciences

Algorithms that adjust for worker race, gender still show biases

Even after algorithms are adjusted for overt hiring discrimination, they may show a subtler kind: preferring workers who mirror dominant groups, according to a new study from researchers at The University of Texas at Austin.

Machine learning & AI

Scientists articulate new data standards for AI models

Aspiring bakers are frequently called upon to adapt award-winning recipes based on differing kitchen setups. Someone might use an eggbeater instead of a stand mixer to make prize-winning chocolate chip cookies, for instance.

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