Artificial intelligence

Prof. Daron Acemoglu joins Slate’s “Money Talks” podcast to explain his research into pro-worker technologies and how we can not only avoid the AI job apocalypse but also improve workers’ lives by shifting the goal of AI from automation to collaboration. “Artificial intelligence is quite different than human intelligence,” says Acemgou. “And when two things are different, a natural way to combine them is in a complimentary way, not try to replace everything that one does with one type of intelligence using the other type of.”

Prof. Xuanhe Zhao speaks with Tech Briefs reporter Andrew Corselli about his team’s work developing an ultrasound wristband that precisely tracks a wearer’s hand movements in real time and can communicate device these motions to a robot or a virtual environment. “For the future of human society, humanized robots will do lots of different work for us. For that work, we need a dexterous robotic hand,” explains Zhao. “We believe this ultrasound wristband, based on variable imaging, could be the future of really knowing the human hand motions.”

President Emeritus L. Rafael Reif writes for The Boston Globe that with the advent of transformative AI, there is an urgent need for “a bilateral conversation between Washington and Beijing, focused on the shared dangers these technologies pose to each nation and to global stability. Both governments must work toward agreed guardrails, defining not just how this technology should be used but where it must never be applied. Red lines need to be defined, established, and agreed upon.” 

In discussion with Deni Ellis Bechard for Scientific American, Prof. Emeritus Rodney Brooks shares his thoughts on a robot that ran a half marathon faster than a human. “When you see a performance of an AI system or a robot on one thing, that fools us into thinking that it has the same general competence as a human,” says Brooks. “And that’s a mistake people make.” 

Prof. Marzyeh Ghassemi speaks with Mark Herz, host of GBH Morning Edition, about the potential benefits and issues associated with using AI in medicine. “Where I really see a lot of fantastic opportunity is identifying spaces where humans don’t have a fundamental capacity, like early breast cancer detection where it’s a sub-clinical presentation,” says Ghassemi. “These are spaces where humans cannot do or have been proven not to be good at a very specific clinical task. And there, AI can really help close the gap.” 

Prof. Thomas Malone and his colleagues at MIT Sloan have developed a way to analyze work, which may help predict which jobs are likely most vulnerable to AI. The researchers found that “AI mainly threatens workers who manage information. But not all of them,” writes Hiawatha Bray for The Boston Globe. “Malone noted that some industries demand human empathy, a sense of ethics, and a knack for teamwork. That’s why he thinks health care jobs are relatively safe.” 

Prof. Andrew Lo speaks with with Greg Iacurci at CNBC about using AI for personal finances. “One of the things about [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,” said Lo. ″[People] should be using AI for financial planning — but it’s how they use it that’s important.” 

President Sally Kornbluth joins Sloan Senior Lecturer Brian Halligan MBA ’05 on his podcast “Long Strange Trip: CEO to CEO” to chat leadership strategies, AI and education, and MIT's approach to preparing students for life after college. “People talk to me, alums talk to me about how MIT changed their lives. It's not because of some particular class or some particular skill they acquired. It’s the whole environment,” Kornbluth notes. She adds that when it comes to educating students, at MIT "we want them to have the kind of knowledge base and ability to navigate the world that will enable them to do anything they want to do.”

MIT researchers have developed a new traffic navigation system that more accurately reflects travel time by including parking data, reports Catherine Parotta for Boston 25. “What we can do is figure out if you’re best off trying this parking lot first, even if it’s farther than the closest parking lot,” explains Prof. Cathy Wu. Graduate student Cameron Hickert adds that: “We hope that this can help people make better decisions." 

Fortune reporter Nick Lichtenberg highlights research by MIT economists that finds “automation doesn’t affect all parts of a job equally. The critical variable is whether the tasks being automated are the expert parts of a role or the administrative scaffolding around them.” 

The Boston Symphony Orchestra will perform the world premiere of Prof. Tod Machover’s “already and not yet,” reports A.Z. Madonna for The Boston Globe. Madonna notes that Machover, “has a decades-long resume of experimenting with artificial intelligence technology in music-making, such as in the 1987 science fiction opera ‘VALIS.’” 

Prof. Andrew Lo speaks with CNBC reporter Greg Iacurci about using AI systems for financial planning and advice. “The problem that we have to solve is not whether AI has enough expertise. The answer right now is, clearly, AI has the [financial] expertise,” says Lo. “What they don’t have is that fiduciary duty. They don’t have the ability to suffer consequences if they make a mistake to the same degree that a human advisor does.”

Prof. Sinan Aral joins CNBC’s “Squawk Box” to discuss the state of AI data center construction across the U.S. and the impact of new AI technologies on the power grid. “Data center and compute demand is so large and growing,” says Aral. He adds that hybrid models that “combine the benefit of connecting to the [power] grid with the benefit of an energy island model, where you have onsite storage of energy, you have battery and you have onsite generation to offload during peak times. The hybrid model is really good because it gets the best of both worlds.” 

A new working paper by researchers from MIT FutureTech finds that “AI’s march through the labor market looks far less like a sudden catastrophe and far more like a slow, rising flood — serious and accelerating, but not the overnight apocalypse that has dominated headlines and executive anxiety for the past two years,” writes Nick Lichtenberg for Fortune. “Rather than arriving in crashing waves that transform a certain set of tasks at a time,” the researchers write, “progress typically resembles a rising tide, with widespread gains across many tasks simultaneously.”

Two new studies from researchers at MIT and elsewhere have described “the machine-learning algorithms they developed to screen bacterial genomes and identify proteins that are involved in protecting the microorganisms against viral invaders,” reports Miryam Naddaf for Nature. “There’s a hope that maybe there’s a next generation of molecular tools that would come from some of these new systems,” says Prof. Michael Laub.