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 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 ...

As organizations increasingly rely on algorithms to rank candidates for jobs, university spots, and financial services, a new method, named hyperFA*IR, offers a more principled approach when picking ...

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 ...

The hardest problem in any marketplace is not growth — it is knowing what caused it. Nihar V. Patel, a product data scientist ...

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 ...

And this wasn’t an isolated incident. Stories abound of stereotypes in large language models (LLMs) in education, technology and other fields. LLMs pose significant hurdles to algorithmic fairness, ...

An economist explores the gender data bias behind credit scoring and borrowing money from the bank that excludes women ...