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Study: AI chatbots provide less-accurate information to vulnerable users

ai, AI (Artificial Intelligence), Artificial Intelligence, data, ethics, Machine Learning, Media Lab, MIT Sloan School of Management, Research, School of Architecture and Planning

Large language models (LLMs) have been championed as tools that could democratize access to information worldwide, offering knowledge in a user-friendly interface regardless of a person’s background or location. However, new research from MIT’s Center for Constructive Communication (CCC) suggests these artificial intelligence systems may actually perform worse for the very users who could most […]

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3 Questions: Using AI to help Olympic skaters land a quint

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, data, IDSS, Interview, Literature, Mechanical engineering, MIT Sloan School of Management, Research, School of Engineering, Sports and fitness

Olympic figure skating looks effortless. Athletes sail across the ice, then soar into the air, spinning like a top, before landing on a single blade just 4-5 millimeters wide. To help figure skaters land quadruple axels, Salchows, Lutzes, and maybe even the elusive quintuple without looking the least bit stressed, Jerry Lu MFin ’24 developed

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Brian Hedden named co-associate dean of Social and Ethical Responsibilities of Computing

Administration, ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, Education, teaching, academics, Electrical engineering and computer science (EECS), ethics, Faculty, Humanities, MIT Schwarzman College of Computing, MIT Sloan School of Management, Philosophy, School of Engineering, School of Humanities Arts and Social Sciences, Technology and policy

Brian Hedden PhD ’12 has been appointed co-associate dean of the Social and Ethical Responsibilities of Computing (SERC) at MIT, a cross-cutting initiative in the MIT Schwarzman College of Computing, effective Jan. 16.Hedden is a professor in the Department of Linguistics and Philosophy, holding an MIT Schwarzman College of Computing shared position with the Department

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Stone Center on Inequality and Shaping the Future of Work Launches at MIT

ai, AI (Artificial Intelligence), Artificial Intelligence, Democracy, Economics, government, Inequality, Labor and jobs, MIT Sloan School of Management, School of Humanities Arts and Social Sciences, Social media, Special events and guest speakers, Technology and society

The James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work officially launched on Nov. 3, 2025, bringing together scholars, policymakers, and practitioners to explore critical questions about economic opportunity, technology, and democracy.Co-directed by MIT professors Daron Acemoglu, David Autor, and Simon Johnson, the new Stone Center analyzes the forces that contribute to growing income

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MIT in the media: 2025 in review

Administration, Alumni/ae, Artificial Intelligence, Cambridge, Boston and region, Climate change, Community, Computer science and technology, Education, teaching, academics, Equity and inclusion, Faculty, Global, government, Health sciences and technology, Innovation and Entrepreneurship (I&E), MIT Schwarzman College of Computing, MIT Sloan School of Management, Policy, President Sally Kornbluth, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Social justice, Space, Staff, Students

“At MIT, innovation ranges from awe-inspiring technology to down-to-Earth creativity,” noted Chronicle, during a campus visit this year for an episode of the program. In 2025, MIT researchers made headlines across print publications, podcasts, and video platforms for key scientific advances, from breakthroughs in quantum and artificial intelligence to new efforts aimed at improving pediatric health

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Helping power-system planners prepare for an unknown future

Artificial Intelligence, Climate change, Computer modeling, Electric grid, Emissions, Energy, Energy efficiency, infrastructure, Invention, MIT Energy Initiative, MIT Sloan School of Management, Open Source, Policy, Research, Technology and policy

A new computer modeling tool developed by an MIT Energy Initiative (MITEI) research team will help infrastructure planners working in the electricity and other energy-intensive sectors better predict and prepare for future needs and conditions as they develop plans for power generation capacity, transmission lines, and other necessary infrastructure. The tool could reduce the amount

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Exploring how AI will shape the future of work

Artificial Intelligence, Graduate, postdoctoral, Labor and jobs, MIT Sloan School of Management, Profile, Students, Technology and society

“MIT hasn’t just prepared me for the future of work — it’s pushed me to study it. As AI systems become more capable, more of our online activity will be carried out by artificial agents. That raises big questions: How should we design these systems to understand our preferences? What happens when AI begins making

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Optimizing food subsidies: Applying digital platforms to maximize nutrition

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), Algorithms, Alumni/ae, Artificial Intelligence, data, Faculty, Food, India, MIT Sloan School of Management, Policy, Poverty, Profile, Research, Sustainability

Oct. 16 is World Food Day, a global campaign to celebrate the founding of the Food and Agriculture Organization 80 years ago, and to work toward a healthy, sustainable, food-secure future. More than 670 million people in the world are facing hunger. Millions of others are facing rising obesity rates and struggle to get healthy

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AI and machine learning for engineering design

Aeronautical and astronautical engineering, Artificial Intelligence, Civil and environmental engineering, Classes and programs, Computer modeling, Design, Faculty, Invention, Machine Learning, Mechanical engineering, MIT Sloan School of Management, Nuclear science and engineering, School of Engineering, Students

Artificial intelligence optimization offers a host of benefits for mechanical engineers, including faster and more accurate designs and simulations, improved efficiency, reduced development costs through process automation, and enhanced predictive maintenance and quality control.“When people think about mechanical engineering, they’re thinking about basic mechanical tools like hammers and … hardware like cars, robots, cranes, but mechanical engineering

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What does the future hold for generative AI?

Artificial Intelligence, Collaboration, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Industry, Machine Learning, MIT Schwarzman College of Computing, MIT Sloan School of Management, President Sally Kornbluth, Provost, Research, Robotics, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Special events and guest speakers, Startups, Technology and society

When OpenAI introduced ChatGPT to the world in 2022, it brought generative artificial intelligence into the mainstream and started a snowball effect that led to its rapid integration into industry, scientific research, health care, and the everyday lives of people who use the technology.What comes next for this powerful but imperfect tool?With that question in

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