Research Scientist Maria Jesús Saénz discusses the benefits and barriers to companies adopting AI in their supply chains for a Financial Times article by reporter Lucy Colback. “If you are having humans change their process for automation in order to substitute themselves, this is a very perverse thing,” Saénz says. “They want to keep their salary and might boycott the AI. [They may] be algorithm averse.”
Prof. David Autor speaks with Bloomberg reporter David Westin about the shift toward automation in the workforce and the impact on workers. “There are many ways for us to use AI,” says Autor. “It’s incredibly flexible, malleable, plastic technology. You could use it to try to automate people out of existence. You could also use it to collaborate with people to make them more effective. But I also think that it depends on how we invest, how we build out those technologies.”
Prof. Daron Acemoglu speaks New York Times reporter Karen Weise about workplace automation at Amazon. “Nobody else has the same incentive as Amazon to find the way to automate,” Acemoglu. “Once they work out how to do this profitably, it will spread to others, too.”
Prof. Dylan Hadfield-Menell speaks with CNN reporter Hadas Gold about the need for AI safeguards and increased education on large language models. “The way these systems are trained is that they are trained in order to give responses that people judge to be good,” explains Hadfield-Menell.
In a video for CNN, graduate student Alex Kachkine explains his work developing a method using AI to create a reversible polymer film that could be used to restore damaged oil paintings, making the process faster than manual restoration. Kachkine explains that he hopes his work helps “get more paintings out of storage and into public view as there are many paintings that are damaged that I would love to see and it’s a real shame that there aren’t the resources necessary to restore them.”
Graduate student Alex Kachkine speaks with New York Times reporter Ephrat Livni about his work creating a new AI technique for restoring paintings, and how his research on microchips helped inspire the development. Microchips “require very high degrees of precision,” Kachkine explains. “And it turns out a lot of the techniques we use to achieve that level of precision are applicable to art restoration.” Kachkine adds that he hopes conservators will be able to “leverage the benefits” of the techniques he gleaned from engineering to preserve “really valuable cultural heritage.”
Principal Research Scientist Andrew McAfee speaks with New York Times reporter Steve Lohr about why companies are not yet seeing the economic payoff of AI implementation in the workforce. “It’s not surprising that early A.I. efforts are falling short,” said McAfee. “Innovation is a process of failing fairly regularly.”
Prof. Philip Isola speaks with Fast Company reporter Victor Dey about the impact and use of agentic AI. “In some domains we truly have automatic verification that we can trust, like theorem proving in formal systems. In other domains, human judgment is still crucial,” says Isola. “If we use an AI as the critic for self-improvement, and if the AI is wrong, the system could go off the rails.”
Graduate student Alex Kachkine has developed a new technique that “uses AI-generated polymer films to physically restore damaged paintings in hours,” reports Benj Edwards for Ars Technica. “Kachkine's method works by printing a transparent ‘mask’ containing thousands of precisely color-matched regions that conservators can apply directly to an original artwork,” explains Edwards. “Unlike traditional restoration, which permanently alters the painting, these masks can reportedly be removed whenever needed. So it's a reversible process that does not permanently change a painting.”
Prof. Daniela Rus, director of CSAIL, speaks with Newsweek reporter Marni Rose McFall about the impact of AI on entry level jobs. “We need a strong pipeline of talent that starts with entry-level roles, internships, and hands-on learning opportunities," says Rus. "These early experiences remain essential stepping stones, helping people build technical confidence, domain fluency, and problem-solving skills. And soon, the skills companies will be looking for in entry-level workers is how well they can make the most of AI tools."
Prof. David Autor speaks with Wired reporter Will Knight about the anticipated impact of AI on employment. “If demand for software were like demand for colonoscopies, no improvement in speed or reduction in costs would create a mad rush for the proctologist's office,” says Autor. “But if demand for software is like demand for taxi services, then we may see an Uber effect on coding: more people writing more code at lower prices, and lower wages.”
A study by researchers at MIT explores “worker attitudes surrounding automation,” reports Sage Lazzaro for Fortune. “A lot of factories and other industrial environments have had data around for a long time and haven’t necessarily known what to do with it,” explains Research Scientist Ben Armstrong. “Now there are new algorithms and new software that’s allowing these companies to be a lot more intelligent with using that data to make work better.”
Guardian reporter Ian Sample highlights how graduate student Alex Kachkine has developed a new approach to restoring age-damaged artwork in hours. “The technique draws on artificial intelligence and other computer tools to create a digital reconstruction of the damaged painting,” explains Sample. “This is then printed on to a transparent polymer sheet that is carefully laid over the work.”
Graduate student Alex Kachkine speaks with Nature reporter Amanda Heidt about his work developing a new restoration method for restoring damaged artwork. The method uses “digital tools to create a ‘mask’ of pigments that can be printed and varnished onto damaged paintings,” explains Heidt. The method “reduces both the cost and time associated with art restoration and could one day give new life to many of the paintings held in institutional collections — perhaps as many as 70% — that remain hidden from public view owing to damage.”
Nature spotlights graduate student Alex Kachkine – an engineer, art collector and art conservator – on his quest to develop a new AI-powered, art restoration method, reports Geoff Marsh for Nature. “My hope is that conservators around the planet will be able to use these techniques to restore paintings that have never been seen by the general public,” says Kachkine. “Many institutions have paintings that arrived at them a century ago, have never been shown because they are so damaged and there are no resources to restore them. And hopefully this technique means we will be able to see more of those publicly.”