NEJM AI Grand Rounds

Can AI Be Harmful? A Conversation with MIT’s Dr. Marzyeh Ghassemi

Jun 28, 2023

01:11:58

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Episode guests

Marzyeh Ghassemi

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Episode notes

Introduction

3min

How I Got Interested in AI

2min

How I Got Interested in Computer Science

3min

Hurtful Words, Quantifying Bices in Clinical Contextual Word Embeddings

3min

The Performance Gap Between Black and White Patients

4min

The Importance of Regulating Large Language Models

2min

The Importance of Understanding Bias in Machine Learning

3min

Differential Privacy in Machine Learning

2min

The Importance of Having a Single Model That Serves All Populations

4min

10.

The Need for More Models for Demographic Identity

2min

11.

The Importance of Data in Predicting Bias

2min

12.

AI Recognition of Patient Race in Medical Imaging

2min

13.

Can You Predict AUC?

3min

14.

The Role of Chest X-Rays in Melaninization Levels

2min

15.

The Threat of Inquiry

4min

16.

The False Hope of Current Approaches to Explainable AI in Health Care

4min

17.

How to Trust a Black Box AI Tool

3min

18.

The Importance of Human Subjects in Trusting a Model

4min

19.

The Importance of Collaboration With Larger Health Systems

2min

20.

The Scale Hypothesis for Machine Learning

3min

21.

The Impact of AI on Humanity

2min

22.

The Importance of Open Data in Machine Learning Research

2min

23.

The Draw of Academia

5min

24.

AI and Medicine: What Worries You the Most?

3min

25.

The Most Controversial Opinion on Machine Learning

3min

26.

The Importance of GPT Ford in Machine Learning

2min

Dr. Marzyeh Ghassemi has been at the forefront of medical machine learning for several years. In this episode, she describes her group’s work and her perspectives on developing and applying machine learning to understand and improve health in ways that are robust, private, and fair. Dr. Ghassemi is an Assistant Professor at MIT in Electrical Engineering and Computer Science and the Institute for Medical Engineering & Science.

Transcript

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