Artificial intelligence

Prof. Daron Acemoglu speaks with Washington Post reporter Benjamin Guggenheim about his views on advancing AI, and how the technology might impact the labor market over the next decade. “What we saw at the end of ‘25 and the beginning of ‘26 was an acceleration. I think the agentic AI models are certainly much better in terms of a number of tasks, such as coding and other sort of simple cognitive tasks,” says Acemoglu. 

Writing for the Observer, Michael John Gorman, director of the MIT Museum, points to the 1976 Cambridge Experimentation Review Board, a group of citizens tasked with weighing the risks and benefits of DNA splicing technology, as a solution to modern debates over AI. “The dominant assumption in the AI debate is that there are only two options: reckless acceleration or fearful prohibition,” writes Gorman. “Cambridge in 1976 proved there is a third path, and that it runs through the public rather than around it.” 

Prof. Alessandro Acquisti speaks with NPR’s Scott Neuman about privacy issues related to surveillance by autonomous vehicle (AV) companies. “There already exist laws that govern duty to report or even duty to protect [for AV companies],” Acquisti says. “The privacy problems arise when and if driverless carrier companies used such laws or ethical obligations as a pretext for blanket, indiscriminate accumulation of identifiable data for unspecified future purposes.” 

Prof. Jinhua Zhao takes a car ride through Boston with GBH “Curiosity Desk” host Edgar B. Herwick II to discuss the concerns and benefits of self-driving technology entering the city. “We pay a lot of attention to how good AV [Autonomous Vehicle] safety needs to be, but it’s important for us to understand how bad we have been—the current system is [bad],” says Zhao. “When human drivers are aggressive, they actually indeed pose a challenge on AV—which is that AV needs to learn how to be assertive. If you’re too conservative, you’ll just be stuck there going nowhere.”

CNBC’s Greg Iacurci interviews Prof. Andrew Lo about the potential pitfalls of relying on AI for financial advice. “One of the things about LLMs [Large Language Models] that I find particularly concerning is that no matter what you ask it, it’ll always come back with an answer that sounds authoritative, even if it’s not,” says Lo. “When it comes to very, very specific calculations of your own personal situation, that’s where you have to be very, very careful.”

In a Bloomberg article, reporter Robb Mandelbaum highlights the AI-Driven Enterprise Institute (AIDE), a new venture by senior lecturer Paul Cheek, which delivers an indexed ranking of how 337 S&P 500 companies are deploying AI and how their implementation and strategy compares to their competitors. “Everybody now needs to be bringing AI literacy into their organization,” Cheek says. “I want my students going in with a very adaptable mindset that best prepares them to apply AI.”

Prof. David Autor discusses the potential future economic impact of AI in a panel discussion moderated by Wall Street Journal reporter George Anders. “Technology automates, it complements and it creates new expertise and new work,” says Autor. “I don’t think we’re headed into a new world where human judgment, moral reasoning, empathy and know-how have no economic value.” 

The Economist’s “Bartleby Newsletter” spotlights a survey led by Prof. Danielle Li that found American employees were less likely to opt into training AI after learning how their data could be used. "In an experiment, the researchers offered to buy survey data from participants; those who had been shown a video on how data could be used to train AI were less willing to sell,” writes Andrew Palmer. 

Chronicle of Philanthropy reporter Maria Di Mento spotlights how the creation of the MIT Schwarzman College of Computing allowed MIT to develop new “interdisciplinary programs to prepare students for an AI-saturated world and help them understand the social and ethical implications of digital technologies.” Prof. Daniel Huttenlocher, dean of the Schwarzman College of Computing, explains that: “MIT realized that effective education in the age of AI has to look different than it has in the past. Traditional siloing of expertise won’t work when AI is expected to touch nearly every part of people’s lives and is changing the way people in disciplines outside of computing are advancing their work.”

Writing for Forbes about efforts to improve air travel safety, Tanya Eves highlights the Air-Guardian system, an eye-tracking monitor for pilots developed by CSAIL researchers that assists when attention wavers. “In tests, it reduced flight risk and improved navigation success rates,” writes Eves. “It's a model for how the virtual co-pilot relationship should work: not replacement, but a seamless, intelligent partnership that understands when to act and when to stay silent.”

Writing for Forbes, contributor Ron Schmelzer highlights Describe Anything, Anywhere, at Any Moment (DAAAM), a new system developed by MIT researchers that could enable robots to capture details of objects they see while exploring an environment. In the future, the system could allow factory workers to send robotic assistants to find items. DAAAM “lets a robot build a detailed map of a space, attach descriptions to objects in that map, and answer plain English questions later,” Schmelzer explains. 

In an opinion piece for The Washington Post, Senior Fellow Brian Deese and writer Anna Pasnau highlight the potential for AI infrastructure such as large data centers to increase jobs for electricians, welders and plumbers. “AI’s potential as a collaborator — ‘extending human judgment, enabling new tasks, and accelerating skill acquisition’ — is as significant as its capacity to automate,” they write.

Prof. Simon Johnson discusses the impact of AI on jobs in an interview with Financial Times (FT) reporters Delphine Strauss and Sam Fleming for the FT’s “Economists Exchange” series. “We are trying very hard at MIT to find ways to incorporate AI into the curriculum but to push harder on the entrepreneurship angle, the creation of new products and services, the development of critical thinking,” says Johnson.

In an interview with Fortune reporter Nick Lichtenberg, Prof. Daron Acemoglu discusses AI’s economic impact and his book, What Happened to Liberal Democracy. Acemoglu estimates AI will deliver roughly 0.55% in total factor productivity gains. “It’s not that you cannot get big productivity gains from automation. It is that it’s not as easy as sometimes it’s presumed,” says Acemoglu. 

Prof. Eric So joins CBS News Tech Watch to discuss a new Pew Research Center study that reveals 40% of U.S. adults perceive AI’s future impact to be negative, as well as his upcoming book, The Collision: What AI Does to Us. “The growth of AI is simply overwhelming for so many people in terms of the pace of progress. But also, a reflection of the fact that for so much of human history, human level intelligence was our most scarce resource, our most defensible advantage,” says So. “It was why we were paid the salaries that we are. And now AI is increasingly commoditizing that. It’s being mass produced in a way that really causes us to question what’s going on to make us valuable in the future.”