MIT researchers found that AI assisted work leads to the ‘diversity collapse’ of a brand’s voice, and users that rely on AI to do their thinking lose skills over time, highlights Forbes’ Michelle O'Connor. “Judgment, taste and the instinct to catch when something’s off isn’t a soft skill you can afford to lose,” writes O’Connor. “The MIT data is the first hard evidence of that.”
Prof. Max Tegmark speaks to Fox Business about the need for government regulations on AI. AI agents “have goals; they’re actively pursuing them and being incredibly creative about getting things done, even if it wasn’t the way you wanted,” says Tegmark. “Put that together with robotic bodies, and you’ve got yourself a species. If they’re vastly smarter than us, which is the goal of these companies, then they can not only do hacking, they can go online and hire a bunch of humans to work for them.”
A recent study by MIT researchers found that AI chatbots easily generated misleading election-related answers, images and videos, writes Emily Condon for USA Today. “This, along with other findings from our study, suggests that in an ongoing election with little authoritative information for models to rely on, AI may not be as helpful in pushing back against unsubstantiated rumors and misinformation,” the researchers explain.
Prof. Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing, joins Fox Business to discuss why he feels humans should be held accountable for AI’s failures. “The key thing to remember is we cannot [and] we should not be treating AI as if it’s something that has control or has responsibility. That rests with us,” Huttenlocher emphasizes.
A new report published in part by MIT FutureTech finds that AI does not significantly accelerate scientific research, writes Peter Hall for the Scientific American. “As the experiments become larger or more complex, so, too, do the models that simulate them, and the data to train those models is hard to come by,” Hall explains. “Robots handling real-world materials raise safety questions that are unknown to software.”
Prof. Daniel Huttenlocher, dean of MIT’s Schwarzman College of Computing, joins Fox News’ “Fox and Friends” to discuss his views on the role of human responsibility in AI’s evolution. “With conventional software, when you program something, you give the machine precise instructions of what to do, so the humans developing it have a much more concrete understanding of what it can and can’t do,” says Huttenlocher. “With an AI system instead, it’s learned much more general skills and what you tell it to do is achieve some sort of a goal, but you don’t tell it the specific way it should achieve that goal. We can’t control it [AI] in the same ways that we control traditional software, but that doesn’t mean we shouldn’t control it and that we can’t control it, it’s just different.”
Prof. Gary Gensler joins CNBC’s “Squawk Box” to discuss the AI race and shares his suggestions for government regulations. “I do feel that there’s a need for more responsible regulation of artificial intelligence,” says Gensler. “These existential risks [conflicts of interest, explainability, and bias], however you measure them, are much harder to control because you’ve got the competition between Chinese model developers, [and] U.S. model developers.”
The 2003 Cohn-Elkies method “for finding upper bounds on the density of sphere packings,” established by MIT Prof. Henry Cohn and Harvard University’s Noam Elkies, is highlighted by Jack Murtagh for the Scientific American. “Their recipe is almost mechanical: come up with a mathematical function, feed the function into their method, and an upper bound pops out,” writes Murtagh. “They provided the field with a machine: identify the right inputs, churn it through their method, and a breakthrough in sphere packing might emerge.”
Prof. Dylan Hadfield-Menell speaks to The Boston Globe’s Joshua Miller about his concerns with the current state of AI systems and how they are optimized. “The parts [of AI systems] that are imitating the ways that humans use language, those parts of the systems actually are quite correctable. They’re still pretty unpredictable, but they do seem quite flexible,” says Hadfield-Menell. “On the other hand, there’s reinforcement learning, task-focused behavior, that can often be quite sticky. They [AI systems] seem to really want to push towards task completion.” He adds: “If you have a powerful optimization-driven system pointed at some goal, it can often do a lot of unexpected things that can have a lot of impact.”
Prof. Shafi Goldwasser and Prof. Vinod Vaikuntanathan founded the Institute for Responsible Superintelligence (RESI), “to develop mathematical principles and protocols to ensure AI models behave as intended,” writes Aaron Pressman for The Boston Globe. “You patch them [AI models] up, you test them, you patch them to make sure that they can perform to the best ability, but also not do damage,” says Goldwasser. “That’s probably not enough attention, given the fact that these things are going to become what we call super intelligent.”
Members of MassLive’s “25 Most Influential Innovators of 2026” list, which includes President Sally Kornbluth and a number of other MIT faculty and alumni, gathered at the MIT Museum to “discuss the forces shaping the future of innovation in Massachusetts,” writes reporter Tréa Lavery. “MIT Provost Anantha Chandrakasan said about half of undergraduate students at the school are studying some form of computing, and enrollment in those courses has gone up in recent years, prompting professors and administrators to rethink how they incorporate AI into their teaching,” writes Lavery.
In an article for The Wall Street Journal, Prof. Daniel Huttenlocher, dean of MIT’s Schwarzman College of Computing writes that: “AI is an extremely powerful and beneficial technology. But accountability for its actions remains with the people and institutions that grant it the power to act, and so does everything that follows: the duty to justify the arrangement, to watch it, to correct it and to stop it when necessary.”
MIT alumni Tom Brown ‘10, co-founder of Anthropic, and Edwin Chen ‘08, founder of Surge AI, are highlighted among the 10 youngest billionaires on the 2026 “Forbes 400 List,” by reporter Alicia Park. Brown “was lead author of the 2020 paper introducing GPT-3, the language model that demonstrated such systems could write fluently and triggered the current investment boom in artificial intelligence,” writes Park. Chen’s Surge AI, “employs people to label data, as well as rate and correct AI-generated answers to train models.”
Good Owners-dogGPT, a chatbot guide designed for dog parents that wasco-founded by alumni Darin Bellisario PhD ‘15 and Raja Rajcic ’20, is featured by The Boston Globe’s Marcela García. “What happens today when [dog owners] go looking for information? They go to Google,” says Bellisario. “You find dozens of videos and blog posts and articles that are either contradictory or outdated or inaccurate, or whatever the algorithm or the ranking wants to show you.”
The Boston Globe’s Hiawatha Bray spotlights Prof. Max Tegmark speaking at the “Pro-Human Assembly” in Washington, an event advocating for government regulations on AI, sponsored by Tegmark’s Future of Life Institute. “We are here today because we know that what’s up next is a fork in the road,” said Tegmark at the assembly. “We know that the future of AI is not inevitable. It is for us to decide.”