As part of the MIT Task Force on the Work of the Future’s series of research briefs, Professor Thomas Malone, Professor Daniela Rus, and Robert Laubacher collaborated on "Artificial Intelligence and the Future of Work," a brief that provides a comprehensive overview of AI today and what lies at the AI frontier.

Imagine that one day you’re riding the train and decide to hop the turnstile to avoid paying the fare. It probably won’t have a big impact on the financial well-being of your local transportation system. But now ask yourself, “What if everyone did that?” The outcome is much different — the system would likely go bankrupt and no one would be able to ride the train anymore.

The national dialogue on race has progressed powerfully and painfully in the past year, and issues of racial bias in the news have become ubiquitous. However, for over a decade, researchers from MIT’s Imagination, Computation, and Expression Laboratory (ICE Lab) have been developing systems to model, simulate, and analyze such issues of identity. 

MIT CSAIL and STEMM Global Scientific Community announced that they will gather thought leaders from all over the world at a virtual summit dedicated to AI in Healthcare on October 1-2, 2020. The aim of the summit is to boost effective collaboration among leading AI academics, healthcare experts and business leaders to support innovation in healthcare. 

In this episode of Radio Corona, we discuss digital contact tracing initiatives throughout the world with Danny Weitzner of MIT’s CSAIL, and Bobbie Johnson, a senior editor at MIT Technology Review.

This week the White House announced that MIT Professor Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), has been selected to serve on the President’s Council of Advisors on Science and Technology (PCAST).

A team led by MIT researchers and including experts from many institutions is developing a system that augments “manual” contact tracing by public health officials, while preserving the privacy of all individuals.

“I want society to truly embrace machine learning,” says Madry, a recently tenured professor in the Department of Electrical Engineering and Computer Science. “To do that, we need to figure out how to train models that people can use safely, reliably, and in a way that they understand.”

View the annual list from MIT Technology Review that includes technologies that "will make a real difference in solving important problems."