Identifying artificial intelligence “blind spots”
Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.
Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.
MIT “Policy Congress” examines the complex terrain of artificial intelligence regulation.
Hackathons promote doctor-data scientist collaboration and expanded access to electronic medical-records to improve patient care.
Tool for nonstatisticians automatically generates models that glean insights from complex datasets.
New EAPS thesis field is the most recent to join the computational science and engineering doctoral program within the Center for Computational Engineering.
“Counterpoints,” produced by MIT Sloan Management Review, aims to reveal fascinating insights about sports analytics.
Merging different types of location-stamped data can make it easier to discern users’ identities, even when the data is anonymized.
Speakers at the summit included Massachusetts Secretary of Labor Rosalin Acosta and former Google chairman Eric Schmidt.
MIT Libraries offer expanded resources in geographic information systems, data visualization, data management, and more for the Institute community.
A roundup of MIT student research projects offers a glimpse of where computing is going next.
Researchers find most fantasy sports are based on skill, not luck.
Model predicts whether ER patients suffering from sepsis urgently need a change in therapy.
Study identifies reasons for unsettled editing disagreements and offers predictive tools that could improve deliberation.
Computer model could improve human-machine interaction, provide insight into how children learn language.