"AI Research: From Arrogant and Ignorant to Accountable and Inclusive"

Leo Celi, M.D.
Principal Research Scientist
Clinical Research Director, Laboratory of Computational Physiology
Massachusetts Institute of Technology
 

ABSTRACT
For those in the exciting field of medical artificial intelligence (AI), we need to remind ourselves that real-world data are heavily influenced by long-standing social, cultural, and institutional biases, as well as provider subjectivity in decision-making. How do we create AI when the ground truth is not fair? In addition, algorithms designed with perspectives that under-represent most of the world are bound to maintain the status quo. We should not only invest in storage and compute technologies, federated learning platform, GPTs, GRUs and NFTs. Our goal should be to build capacity across populations and diversity of perspectives in research. This is the biggest investment we can make to prioritize equity.
 

BIOGRAPHY
Leo Anthony Celi is a research scientist at MIT, where he directs the research at the Laboratory for Computational Physiology. He completed medical studies at the University of the Philippines, a master's degree in biomedical informatics at MIT and a master's degree in public health (clinical effectiveness) from Harvard T.H. Chan School of Public Health. In his work around the world, he contributes to strengthening the connection between data science and clinical medicine in order to improve healthcare delivery. Celi heads MIT Critical Data, a global consortium that puts data and learning at the front and center of healthcare. His group is behind the publicly available Medical Information Mart for Intensive Care (MIMIC) - a huge electronic health record database that has more than fifty thousand users from around the world.