Artificial intelligence

Prof. David Autor speaks to Financial Times reporter Christian Davies about the increased use of physical AI systems at U.S. manufacturing companies. “[Autor says] that while individual companies might increase headcount as they grow more productive, it is a fallacy to assume this will be replicated across the manufacturing sector as a whole, noting that previous waves of automation in the US have all driven large-scale declines in blue-collar employment,” writes Davies.  

MIT Media Lab researchers found that using large language models for writing assistance was associated with weaker recall and lower ownership of the work produced, writes Forbes’ Glenn Llopis. “Notice the pattern: when AI does too much, the person may retain too little,” writes Llopis.  

Prof. Emeritus Kerry Emanuel speaks to The New York Times’ William J. Broad about the use of AI models in predicting hurricanes. “It’s human beings who have to make these calls,” says Emanuel. “[Eventually] AI will be treated as just another form of guidance” along with satellite images and readings from hurricane hunter aircraft that pierce the tempests. 

Prof. Regina Barzilay, graduate student Aziz Ayed and alumna Sydney Pham ‘24 are featured in an article about AI models and the workforce, written by Nature’s Ben Deighton. “Sometimes models can make sense of unexpected observations, which can guide further iterations of studies,” Pham says. “It’s helpful to understand how the models generate their results.” 

Inside Higher Ed’s Emma Whitford spotlights a new report by MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training that offers recommendations for how AI should be used in education. “Learning works when it’s both challenging and social; knowledge is built through cognitive friction, whether that’s disentangling the steps of a mathematical proof with your study group, adjusting an experiment over and over until it works, or having a spirited argument with a peer (rather than getting ‘the’ answer from AI),” the committee writes.  

A study by researchers from the MIT Media Lab found up to 55% lower neural connectivity in participants who used AI for writing assistance, and flagged children as especially vulnerable, writes Forbes’ Dana Williams. “83% of participants who used a chatbot could not quote a single sentence from an essay they had finished minutes earlier, versus roughly 11% of those who wrote unaided,” Williams notes. “The words were produced, but they never entered a mind.”  

Sloan Senior Lecturer Paul Cheek’s new book, “No One Works Here” is outlined by Forbes’ Joe McKendrick. “The companies that are most likely to fall behind their peers are the ones that insist on keeping a human in the loop for decisions that a machine could have made yesterday,” Cheek writes in his book.  

A 2025 report by MIT researchers found that 62% of accounting professionals worry about errors in AI generated outputs, writes Thomson Reuters. “AI is doing real, meaningful work in tax workflows right now with even greater capabilities coming. But it’s also generating real anxiety,” Thomson Reuters notes.  

Prof. Daniela Rus, Director of MIT CSAIL, and Prof. David Autor, department head of Economics, are featured on Time’s “TIME100 AI 2026” list of 100 innovators, leaders, and thinkers reshaping the world through their advances in AI. “Over three decades, [Rus] has conducted pioneering work in robotics, extending the understanding of what form robots can take,” writes Tharin Pillay, while Steven Freiss describes Autor as “one of the nation’s most vocal and prominent economists aiming to ascertain AI’s potential impacts on labor.” 

MassLive’s Juliet Schulman-Hall covers a new report from the MIT Ad Hoc Committee on AI Use in Teaching, Learning and Research Training about AI and education at MIT. “It’s rare that a successful institution has to take a fresh look at many aspects of its mission,” said President Sally Kornbluth in a letter to the community. “But I’m convinced that the opportunities and risks generative AI poses for our model of education and research now constitute such a watershed for MIT — and for all of higher education.” 

MIT researchers found that purchased AI tools succeed roughly twice as often as comparable in-house builds, Forbes’ Dennis Vorobyov highlights. “[S]o spend the engineering effort where you are genuinely differentiated,” writes Vorobyov. “Budget wise, none of this requires a moonshot, just clarity and sequencing.” 

MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training has released a report on AI and education and recommendations for the Institute moving forward, writes Forbes’ Ron Schmelzer. “President Sally Kornbluth describes the moment as a ‘watershed’ for MIT and higher education,” writes Schmelzer. “The recommendations include redesigned assessments, renewed attention to hands-on learning, explicit AI rules for courses and new communities of practice for faculty.”

Prof. Emeritus Rodney Brooks speaks to Scientific American’s Mary Randolph about humanoid robots interacting with the real world. “When you see a performance of an [artificial intelligence] system or a robot on one thing,” says Brooks, “that fools us into thinking that it has the same general competence as a human. And that’s a mistake people make.” 

A new study by MIT researchers found that it is impossible to draw a direct link between AI diffusion model outputs and an artist’s body of work, writes Gizmodo’s Webb Wright. “If a [diffusion] model generates something, you want to be able to say, ‘Oh, this part of the training data was responsible,'” says Zheng Dai, PhD ’24, lead author on the study. “It’s important for us to understand how these models work to properly study them or regulate them.” 

In a message to campus, President Sally Kornbluth shared a new report by MIT’s Ad Hoc Committee on AI Use that found that “even as AI accelerates and expands discoveries,  it is also driving dramatic changes in campus culture, upending foundational experiences such as study groups, office hours and undergraduate research,” writes the Washington Post’s Susan Svrluga. “For the sake of our students, for the future of MIT and for the shape of our sector and our society,” says Kornbluth, “it’s imperative that we get this right.”