mccormick.northwestern.edu

Examining Algorithmic Fairness and Accountability

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 ...
Medscape

Algorithmic Fairness: Mitigating Bias in Healthcare AI

Healthcare is undergoing an artificial intelligence (AI) revolution. Facilitated by improved infrastructure for handling large quantities of data, AI-derived tools are quickly becoming integrated in ...
The American Journal of Managed Care

Predictive Models for Low Birth Weight: A Comparative Analysis of Algorithmic Fairness–Improving Approaches

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: ...
Forbes

Why Tech Executives Must Embrace Diversity As Their First Line Of Defense Against The Business Impacts Of Algorithmic Bias

Forbes contributors publish independent expert analyses and insights. I break down barriers so women can break through in tech. It matters who is in the room when technology decisions are being made.
Fast Company

This tool lets you see–and correct–the bias in an algorithm

Accenture’s new Fairness Tool is a way to quickly evaluate whether your data is creating fair outcomes. “I’m hoping is that this is something that we can make accessible and available and easy to use ...
Harvard Medical School

A Harm-Reduction Framework for Algorithmic Fairness

In this article, we recognize the profound effects that algorithmic decision-making can have on people's lives and propose a harm-reduction framework for algorithmic fairness. We argue that any ...