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If a machine-learning model is trained using an unbalanced dataset, such as one that contains far more images of people with lighter skin than people with darker skin, there is serious risk the ...

GAINESVILLE, Fla.--(BUSINESS WIRE)--Exactech, a developer and producer of innovative implants, instrumentation, and smart technologies for joint replacement surgery, reports a new study 1 that ...

Joseph, Matthew, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Rawlsian Fairness for Machine Learning." Paper presented at the 3rd Workshop on Fairness, Accountability, and ...

Today, businesses rely on predictive models for a multitude of reasons. At the very least, they enable novel insights that can streamline internal processes; at the most, they are essential drivers of ...

Unfairly trained Artificial Intelligence (AI) systems can reinforce bias, therefore AI systems must be trained fairly. Experts say AI fairness is a dataset issue for each specific machine learning ...

Applying machine learning to a U.S. Environmental Protection Agency initiative, researchers reveal how key design elements determine what communities bear the burden of pollution. The approach could ...

Earlier this week, Google announced that it was piloting a machine learning intensive for college students. Today, its broader Machine Learning Crash Course is adding a new training module on fairness ...