The data scientist and adjunct UF professor is one of several local researchers who say the systems behind AI can reflect bias in ways that shape real-world outcomes.

As organizations increasingly rely on algorithms to rank candidates for jobs, university spots, and financial services, a new ...

The accuracy and robustness of computational models is only one side of the equation. The field of algorithmic fairness and accountability investigates the decision-making capabilities of data-driven ...

As organizations increasingly rely on algorithms to rank candidates for jobs, university spots, and financial services, ...

This research area examines how individuals perceive fairness in algorithmic decision-making and how these perceptions affect the acceptance and adoption of AI systems. We investigate various fairness ...

In total, 5,708 patients from five randomized phase III trials were included. Two MMAI algorithms were evaluated: (1) the distant metastasis (DM) MMAI model optimized to predict risk of DM, and (2) ...

BKC Faculty Associate Ben Green writes about the challenge of creating equitable policy reforms around algorithmic fairness. “Efforts to promote equitable public policy with algorithms appear to be ...

Part 2, Digital Inequality Series: Under what conditions can artificial intelligence benefit all of society vs. just a few people? Kalinda Ukanwa, a quantitative marketing scholar at the University of ...