Description:

The Master of Arts in Medical Humanities and Bioethics Program

Presents

A Montgomery Lecture

With

Jonathan Hourmozdi, MD, MA
AI in Cardiovascular Disease Fellow
Center for Artificial Intelligence, Bluhm Cardiovascular Institute
McCormick School of Engineering, Northwestern University

Demystifying AI: Explainability and Algorithmic Bias in Healthcare

With the rise of large language models and a resurgence of chatbots like OpenAI's Chat-GPT powered by new cutting-edge artificial intelligence technology, interest and investment into AI adoption in healthcare are at fever pitch. And yet, even before generative AI and foundational models captured the public imagination, we have already been integrating powerful AI predictive algorithms into various healthcare applications. In this talk, we will explore whether machine learning and deep learning are really so different from other modeling techniques that came before. We will unpack the so-called "black box" problem of neural networks and other deep learning models and discuss how this contributes to algorithmic bias. The hope is that by peering under the hood of these new technologies, we can better understand the potential ethical implications of their adoption and hopefully find some proactive solutions.

This lecture is open to the public and will be held in the Searle Seminar Room in the Lurie Research Building (303 E Superior), Chicago Campus. For those outside the Chicago area and anyone who would prefer to attend remotely, a Zoom option is also available.

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