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AI systems that use data trained with descriptive labeling can yield much harsher decisions than humans make. It's not too late to fix the problem.

A new study from researchers at the University of Toronto and the Massachusetts Institute of Technology (MIT) is challenging conventional wisdom on human-computer interaction and reducing bias in AI.The paper, which was published this month in the jo

Researchers from MIT and elsewhere have found that machine-learning models trained to mimic human decision-making often suggest harsher judgements than humans would. They found that the way data were gathered and labeled impacts how accurately a model can be trained to judge whether a rule has been violated.

Researchers from MIT and elsewhere have found that machine-learning models trained to mimic human decision-making often suggest harsher judgements than humans would. They found that the way data were gathered and labeled impacts how accurately a model can be trained to judge whether a rule has been violated.

CAMBRIDGE, Mass., May 10, 2023 — In an effort to improve fairness or reduce backlogs, machine learning models are sometimes designed to mimic human [...]