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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.

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.

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.

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.

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.

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.

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.

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.

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.

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...

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.