Technology and society

Prof. Samuel Madden joins Tiziana Dearing, host of WBUR’s “Morning Edition,” to discuss the findings of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training. “Cognitive surrender is the idea that people come to rely too heavily on these AI tools for their learning and they start outsourcing the critical thinking and the development of the foundational tools they think they need to succeed in life, to these AI tools,” says Madden. “It’s not just writing, but we see this [cognitive surrender] in our courses as well.”  

In a video interview, Prof. Turkle speaks to CNN’s Madeline Holcombe about how AI chatbots may contribute to feelings of loneliness and isolation in adults. “Technology offered the possibility of feeling like friendship without the demands of vulnerability,” says Turkle. “It turns out you can’t have intimacy or friendship without vulnerability.” 

Prof. Asu Ozdaglar, head of MIT’s Department of Electrical Engineering and Computer Science, and graduate student Julia Schneider ‘26 speak to Spectrum News about MIT’s new Artificial Intelligence and Decision Making major. “Now is definitely the time to study more AI, not less,” says Schneider. “What we need is a bunch of people that are focused and excited and passionate about deeply understanding why these models do what they do.” She adds: “Ultimately I want to work on technology that ends up helping people.”  

Prof. David Autor and his team of researchers found that junior patent attorneys who used AI for assistance showed no net improvement in their skills, reports Andy Mukherjee for Bloomberg. “When researchers subsequently tested everyone on an unassisted, offline task to gauge internalized judgment, the learning gains went entirely to senior lawyers,” writes Mukherjee. “Foundational expertise may be a prerequisite for extracting durable skill from AI-assisted practice,” the researchers noted.  

In The Wall Street Journal’s “Economics Newsletter,” reporter Greg Ip highlights a study by Prof. David Autor that found that AI did not significantly improve the performance of the 133 patent lawyers who participated. “Among junior lawyers, the performance of some got better, others got worse, and on average they were the same. Among senior lawyers, the lowest performers improved, the best didn’t,” writes Ip. “The conclusion: Lawyers don’t acquire durable new skills with AI.” 

Prof. Eric Klopfer, co-chair of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, is spotlighted by The Washington Post’s Susan Svrluga. Klopfer “said in many cases students are turning in homework that is better. And their performance on exams is worse,” writes Svrluga. AI is “the illusion of learning,” says Klopfer.  

Jeffrey Riley, executive director of MIT RAISE’s “Day of AI” K-12 program, speaks to WBUR’s Suevon Lee about the importance of teaching school-aged children AI literacy skills. “Kids need to know about voice clones and deepfakes and plagiarism,” says Riley. “We need to teach kids so that they're healthy skeptics of this technology, that they mistrust and verify the information they're getting from it.”  

MIT researchers are leading a new project documenting what major AI systems say about elections in an effort to understand how the technology influences the democratic process, writes Tiffany Hsu for The New York Times. “AI is becoming part of the way people encounter and make sense of political information, and yet we know relatively little about what that information environment actually looks like, how it differs for different user demographics, political identities and geographies,” says Prof. Chara Podimata, a leader of the project.  

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.  

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.” 

Writing for Forbes, Joseph Coughlin, Director of the MIT AgeLab, describes the importance of considering home security beyond simple intrusion protection in longevity planning. “A longevity-ready home to age-in-place isn't simply a safer, more accessible home,” writes Coughlin. “It is a home surrounded by an architecture of people, technology, and services that can detect, communicate, and respond even when we, or the people who care about us, cannot.” 

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.”

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.” 

Prof. David Gifford and Zheng Dai PhD ’24 discovered that AI diffusion models can replicate the style of an artist even when their work was omitted from datasets, leading to ‘attribution decay,’ writes Fast Company’s Jesus Diaz. “This trend, what the researchers call ‘attribution decay,’ means that artificial intelligence can produce an image that resembles a particular artist’s work, while having no provable causal link to that artist’s actual contribution to the training data,” explains Diaz.