Associate Professor Marzyeh Ghassemi discusses why, despite its tremendous potential for good, AI must be approached with caution, especially in high risk areas like healthcare.  Biases in training data can perpetuate real-world inequalities, providers might rely too much on potentially faulty AI, and tools created for one demographic might not necessarily translate to a different population. However, considering the incredible potential of AI to tackle challenges in transformative ways, it’s worth approaching these considerations with rigorous academic insight.  Learn more about her work here: https://www.csail.mit.edu/person/marzyeh-ghassemi

AI’s Bias in Predictive Healthcare with Associate Professor Marzyeh Ghassemi

MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) Alliances serves as a gateway into the lab for industry and governmental institutions seeking a closer connection to the work, researchers, and students of CSAIL. Our podcast aims to provide inside access to topics covered by CSAIL and other leaders advancing computer science and AI research.

AI’s Bias in Predictive Healthcare with Associate Professor Marzyeh Ghassemi

MIT CSAIL Alliances