Cynthia Rudin is the second recipient of the AAII Squirrel AI Award for “pioneering socially responsible AI.” The computer science and engineering professor’s work focuses on creating and deploying interpretable AI systems to improve societal problems. Her models have been deployed across healthcare and the criminal justice system to improve people’s daily lives.
Her interpretable approach to machine learning is the opposite of the black box models that so often make headlines. The transparent approach to algorithmic decision-making ensures that non-technical stakeholders are able to understand AI processes without losing their effectiveness. As Professor Rudin puts it, “We’ve been systematically showing that for high-stakes applications, there’s no loss in accuracy to gain interpretability, as long as we optimize our models carefully.” The interpretable approach to model development is a valuable alternative to using explainable AI tools to try to approximate the decision-making of more opaque black box models.