Cracking the case of Arctic sea ice breakup
A distributed sensor network may help researchers identify the physical processes contributing to diminishing sea ice in the planet’s fastest-warming region.
In bias we trust?
Explanation methods that help users determine whether to trust machine-learning model predictions can be less accurate for disadvantaged subgroups, a new study finds.
Artificial intelligence predicts patients’ race from their medical images
Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.
Is it topological? A new materials database has the answer
Searchable tool reveals more than 90,000 known materials with electronic properties that remain unperturbed in the face of disruption.
Living better with algorithms
Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.
Zero-trust architecture may hold the answer to cybersecurity insider threats
MIT Lincoln Laboratory study explores a new approach to securing systems.
Technique protects privacy when making online recommendations
Researchers devise an efficient protocol to keep a user’s private information secure when algorithms use it to recommend products, songs, or shows.
MIT to launch new Office of Research Computing and Data
Professor Peter Fisher will lead effort to grow and enhance computing infrastructure and services for MIT’s research community.
Artificial intelligence system learns concepts shared across video, audio, and text
A machine-learning model can identify the action in a video clip and label it, without the help of humans.
3 Questions: Designing software for research ethics
PhD candidate Jonathan Zong found a lack of systems that earn and maintain public trust in large-scale online research — so he made one himself.
Estimating the informativeness of data
MIT researchers can now estimate how much information data are likely to contain, in a more accurate and scalable way than previous methods.
A new state of the art for unsupervised computer vision
MIT CSAIL scientists created an algorithm to solve one of the hardest tasks in computer vision: assigning a label to every pixel in the world, without human supervision.
Frequent encounters build familiarity
PhD student Paige Bollen finds urban street networks that encourage encounters among strangers link to lower ethnic tensions and anti-immigrant hostility.
MIT Schwarzman College of Computing unveils Break Through Tech AI
New program strives to bridge the talent gap for underrepresented groups in the tech industry.
Emery Brown earns American Institute for Medical and Biological Engineering Pierre Galletti Award
AIMBE's highest honor recognizes MIT professor's contributions to neural signal processing, anesthesiology advances.