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 ...

This study compared 6 algorithmic fairness–improving approaches for low-birth-weight predictive models and found that they improved accuracy but decreased sensitivity for Black populations. Objective: ...

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 ...

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 ...

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) ...

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 ...

With the exponential growth of AI technologies, financial institutions must address algorithmic bias head on, as it is one of ...