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 ...

The rapid proliferation of algorithmic systems has sparked widespread concerns about their potential to perpetuate and ...

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 ...

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: ...

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 ...

Who gets the job interview. Who receives public benefits. Who is flagged as high risk. Increasingly, these outcomes are ...

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 ...

As algorithmic decision-making becomes increasingly pervasive, it raises challenging issues pertaining to equality and equity. This timely discussion on fairness and technology is grounded in ...