EurekAlert!

Injecting fairness into machine-learning models

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 ...
Business Wire

Exactech Publishes New Machine Learning Research That Evaluates Fairness and Accuracy of AI Predictions

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 ...
Nextgov

Building fairness into AI is crucial – and hard to get right

Get the latest federal technology news delivered to your inbox. With this transformative power, however, comes a significant responsibility: the need to ensure that these technologies are developed ...
Harvard Business School

An Empirical Study of Rich Subgroup Fairness for Machine Learning

Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, ...
Science Daily

Assessing regulatory fairness through 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 ...
Harvard Business School

Rawlsian Fairness for Machine Learning

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 ...
Science Daily

Machine learning can be fair and accurate

Researchers are challenging a long-held assumption that there is a trade-off between accuracy and fairness when using machine learning to make public policy decisions. Carnegie Mellon University ...
Diginomica

Can we measure fairness? A fresh look at a critical AI debate

Bias is a universal trait among humans. It can be meaningless, or it can be dangerous. For example, I am biased about the Philadelphia Phillies baseball team. If a Phillies pitcher competes for the Cy ...