
“We need to both ensure humans reap AI’s benefits and that we don’t lose control of the technology,” says senior Audrey Lorvo.

Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.

As the Director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), Rus leads over 1,700 researchers in pioneering innovations to advance computing and improve global well-being.

Researchers at MIT, NYU, and UCLA develop an approach to help evaluate whether large language models like GPT-4 are equitable enough to be clinically viable for mental health support.

A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.

Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.

The technique could make AI systems better at complex tasks that involve variability.

The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.

Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.