The benefits of medical AI assistance vary based on user expertise
Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors.
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Laboratory for Information and Decision Systems (LIDS)
Alexander Rakhlin named director of the MIT Statistics and Data Science Center
An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.
Read MoreNew chip could help tiny robots traverse complex environments
Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power.
Read MoreGames people — and machines — play: Untangling strategic reasoning to advance AI
Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.
Read MoreA new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.
Read MoreEvaluating the ethics of autonomous systems
MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.
Read MoreAI system learns to keep warehouse robot traffic running smoothly
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.
Read MoreA better method for identifying overconfident large language models
This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.
Read MoreMIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact
Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.
Read MoreA better method for planning complex visual tasks
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
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