Data Dilemmas in Health

Facing the tough decisions of a serious health threat brings the need for information and analysis into a sharp and personal focus. Computer scientist Regina Barzilay was an expert in natural language processing when she joined MIT; her cancer diagnosis led her to collaborations in healthcare, where she has advanced imaging, prediction, drug discovery, and clinical AI. She joins Munther Dahleh and Liberty Vittert to talk about issues from data collection and privacy to bias and “distributional shift” – when an algorithm is used on a dataset with key differences from the data used to train it.

Om Podcasten

We face many overwhelming challenges in America today: systemic racism, data privacy, and political misinformation. These are big problems, and there are a lot of opinions and ideas on how to fix them. Scholars and industry experts often disagree on how to find solutions. So, how can we find the right way to move forward? We let the data speak for itself. Join hosts Liberty Vittert and Munther Dahleh as they gather data and get the facts about today’s most pressing problems to find out: are solutions even possible? They’ll investigate with MIT professors dedicated to researching these issues, and talk with the people on the ground encountering these problems every day so that we can find the best solutions that triumph over these challenges and solve America’s biggest problems. Data Nation is a production of MIT's Institute for Data, Systems, and Society.