Dermatologists and general practitioners are somewhat less accurate in diagnosing disease in darker skin, a new study finds. Used correctly, AI may be able to help.

Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.

In China, the use of AI-driven facial recognition helps the regime repress dissent while enhancing the technology, researchers report.

A collaboration between MIT and Miami-Dade County has students working with city planning officials to understand why people wait patiently for a bus — and why they bail.

The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.

Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.

New research ties inaccuracies in pulse oximeter readings to racial disparities in treatment and outcomes.

“Interpretability methods” seek to shed light on how machine-learning models make predictions, but researchers say to proceed with caution.

Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.

A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.