Building explainability into the components of machine-learning models
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
Researchers have created prototypes that enable screen-reader users to quickly and easily navigate through multiple levels of information in an online chart.
Thousands of children participate in MIT-developed artificial intelligence curriculum.
A new training approach yields artificial intelligence that adapts to diverse play-styles in a cooperative game, in what could be a win for human-AI teaming.
Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.
The NCSOFT-sponsored program will advance cutting-edge technologies for gaming and data visualization.
MIT researchers design a robot that has a trick or two up its sleeve.
For individuals who communicate using a single switch, a new interface learns how they make selections, and then self-adjusts accordingly.
Associate professor and principal investigator with the MIT Schwarzman College of Computing’s Science Hub discusses the future of robotics and the importance of industry-academia collaborations.
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
New MISTI faculty director Evan Lieberman discusses the crucial role of international education for global solutions.
Overseeing business and research units across MIT Open Learning, Breazeal will focus on the future of digital technologies and their applications in education.
Researchers have created a method to help workers collaborate with artificial intelligence systems.
Researchers develop a way to test whether popular methods for understanding machine-learning models are working correctly.
The more social behaviors a voice-user interface exhibits, the more likely people are to trust it, engage with it, and consider it to be competent.