05/22/2026
Technology usually creates jobs for young, skilled workers. Will AI do the same? https://news.mit.edu/2026/technology-creates-jobs-young-skilled-workers-ai-0521
Technology usually creates jobs for young, skilled workers. Will AI do the same?
New tech-enabled jobs have historically been filled by young, college-educated workers, and a lot of innovation-based new work is driven by demand, according to a new study of the postwar U.S.
05/21/2026
Building AI models that understand chemical principles https://news.mit.edu/2026/building-ai-models-with-chemical-principles-connor-coley-0520
Building AI models that understand chemical principles
MIT Associate Professor Connor Coley develops and deploys computational models to design new chemical compounds and predict reaction pathways that could generate those compounds.
05/20/2026
Justin Solomon appointed associate dean of engineering education https://news.mit.edu/2026/justin-solomon-appointed-associate-dean-engineering-education-0519
Justin Solomon appointed associate dean of engineering education
Justin Solomon, associate professor in the MIT Department of Electrical Engineering and Computer Science, has been appointed associate dean of engineering education in the MIT School of Engineering.
05/15/2026
Two from MIT named 2026 Knight-Hennessy Scholars https://news.mit.edu/2026/knight-hennessy-scholars-0514
Two from MIT named 2026 Knight-Hennessy Scholars
MIT master's student Sunshine Jiang and alumnus Rupert Li are recipients of the 2026 Knight-Hennessy Scholarship program. They will receive funding to support their graduate studies at Stanford University.
05/14/2026
Q&A: Expanding MIT’s global reach through Universal Learning https://news.mit.edu/2026/qa-expanding-mit-global-reach-through-universal-learning-0512
Q&A: Expanding MIT’s global reach through Universal Learning
Universal Learning is a new MIT Open Learning initiative preparing global learners to tackle complex challenges through interdisciplinary thinking. Combining MIT faculty expertise with AI-powered tools, its modular programs are designed to be accessible, flexible, and practical.
05/08/2026
Study: Firms often use automation to control certain workers’ wages https://news.mit.edu/2026/study-firms-often-use-automation-control-certain-workers-wages-0507
Study: Firms often use automation to control certain workers’ wages
A new study shows that rather than use automation to pursue maximal efficiency, U.S. firms have often used it to replace employees who enjoy a “wage premium,” earning higher salaries than other comparable workers.
05/07/2026
Games people — and machines — play: Untangling strategic reasoning to advance AI https://news.mit.edu/2026/untangling-strategic-reasoning-to-advance-ai-gabriele-farina-0505
Games people — and machines — play: Untangling strategic reasoning to advance AI
MIT Assistant Professor Gabriele Farina explores his approach to untangling strategic reasoning to advance AI.
05/02/2026
Beacon Biosignals is mapping the brain during sleep https://news.mit.edu/2026/beacon-biosignals-maps-brain-during-sleep-0501
Beacon Biosignals is mapping the brain during sleep
Beacon Biosignals is creating a model to help diagnose and treat brain disorders, based on data collected while people sleep at home. The firm was founded by MIT alumnus Jake Donoghue and former MIT researcher Jarrett Revels.
04/30/2026
Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models https://news.mit.edu/2026/smarter-way-to-debias-ai-vision-models-0429
Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models
A new debiasing approach called WRING resolves the "Whac-a-Mole dilemma" of existing debiasing approaches that can create or amplify existing biases.
04/25/2026
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone https://news.mit.edu/2026/mit-scientists-build-worlds-largest-collection-olympiad-level-math-problems-open-0424
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
MIT CSAIL scientists have compiled the largest high-quality dataset of proof-based math problems ever created. It can help researchers test AI models’ mathematical reasoning, while capturing the full range of mathematical perspectives and problem-solving traditions within the global math community...
04/23/2026
Teaching AI models to say “I’m not sure” https://news.mit.edu/2026/teaching-ai-models-to-say-im-not-sure-0422
Teaching AI models to say “I’m not sure”
MIT CSAIL's “Reinforcement Learning with Calibration Rewards” technique improves AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.