Prof. Sherry Turkle speaks to Scientific American’s Brianne Kane about her forthcoming book, “Artificial Intimacy: Who We Become When We Talk to Machines.” “Social media got us into the attention economy, but chatbots are more toxic because they’re coming after the attachment economy,” says Turkle. “They’re coming after who you think you love, who you think you can count on, what you think empathy is.”
In a Scientific American article by reporter Joseph Howlett, Prof. Naomi Sweeting discusses the potential pitfalls of consulting artificial intelligence in mathematics. “I view math as part of a vast and beautiful human project,” says Sweeting. “It's this huge endeavor that puts us in communication with thousands of years of human thinking.”
Prof. Sherry Turkle’s latest book “Artificial Intimacy: Who We Become When We Talk to Machines,” is highlighted as one of the best new science books of September 2026 by New Scientist’s Liz Else. In her new book, Turkle explores how machines “are producing a generation more alienated, depressed and lonely than ever – and less equipped to reverse course, as machine relationships offer no practice for getting along with people,” writes Else.
MIT researchers have developed an AI-powered robotic therapy system that combines wearable force sensors and camera recordings of physical therapists’ movements to provide personalized therapy to patients, writes Newsweek’s Claudia Tanner. “Robotic assistance will allow patients to practice exercises more often while still receiving support tailored to their abilities,” says Johannes Lachner, who completed this work as a postdoctoral fellow at MIT. “Our goal is to take a step toward more accessible and personalized physical rehabilitation, giving more patients the opportunity to regain movement and independence.”
Writing for The Boston Globe, President Emeritus L. Rafael Reif describes the need to develop a universal “moral floor,” like the Ten Commandments, which provide clear guidelines for the use of AI. “Today, people are creating and developing intelligence that is much more capable, in narrow ways, than our own,” Reif explains. “We owe humanity the same discipline to civilize AI before it is too late: Write down what lines must never be crossed, make the list short enough to remember, and hold every actor building it, and using it, accountable for its actions.”
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.”