Prof. Stuart Madnick speaks with Wall Street Journal reporter Seán Captain about how AI could make scamming easier and more dangerous. AI “raises the level of skepticism that we must have substantially,” notes Madnick. “Procedures will have to be put in place to validate the authenticity of who you are dealing with.”
A study conducted by graduate student Aspen Hopkins and colleagues trained a version of a GPT neural network on the board game Othello “by feeding in long sequences of move in text form”, reports George Musser for Scientific American. “Their model became a nearly perfect player,” writes Musser.
Prof. Cynthia Breazeal, the MIT dean of digital learning, speaks with Education Week reporter Alyson Klein about the importance of ensuring K-12 students are AI literate. “The AI genie is out of the bottle,” says Breazeal. “It’s not just in the realm of computer science and coding. It is affecting all aspects of society. It’s the machine under everything. It’s critical for all students to have AI literacy if they are going to be using computers, or really, almost any type of technology.”
Prof. David Autor speaks with Greg Rosalsky of NPR’s Planet Money about the potential benefits and downsides of AI, sharing his hope that with the right policies in place to help prepare workers AI could be harnessed to help “reinstate the middle class.” Says Autor: "Basically, the middle-skilled workers of the future could be people who have foundational skills in healthcare, in the trades, in travel and services. Then, with the help of AI, they could get really good at these jobs.”
Wired reporter Caitlin Harrington writes that a study by researchers from MIT and Stanford highlights the impact of generative AI tools on workers and raises a “provocative new question: Should the top workers whose chats trained the bot be compensated?”
Soledad O’Brien spotlights how researchers from MIT and Massachusetts General Hospital developed a new artificial intelligence tool, called Sybil, that an accurately predict a patient’s risk of developing lung cancer. “Sybil predicted with 86 to 94 percent accuracy whether a patient would develop lung cancer within a year,” says O’Brien.
Writing for The Los Angeles Times, Institute Prof. Daron Acemoglu and Prof. Simon Johnson make the case that the development of artificial intelligence should be shifted “toward a focus on ‘machine usefulness,’ the idea that computers should primarily enhance human capabilities. But this needs to be combined with an explicit recognition that any resulting productivity gains must be shared with workers, in terms of higher incomes and better working conditions.”
Boston Globe reporter Robert Weisman spotlights Integrated Biosciences, a startup co-founded by MIT researchers that is using artificial intelligence to identify anti-aging drug candidates. “We’re trying to go after aging and aging-associated disorders,” says postdoc Felix Wong. “We all know loved ones who have suffered from some of these conditions.”
Prof. Marzyeh Ghassemi speaks with NPR host Emily Kwong and correspondent Geoff Brumfiel about how artificial intelligence could impact medicine. “When you take state-of-the-art machine-learning methods and systems and then evaluate them on different patient groups, they do not perform equally,” says Ghassemi.
Research from MIT and elsewhere have developed a mobile app that uses computer-vision techniques and AI to detect post-surgery signs of infection as part of an effort to help community workers in Kirehe, a district in Rwanda’s Eastern province, reports Shefali Malhotra for Science. “The researchers are now improving the app so it can be used across more diverse populations such as in Ghana and parts of South America,” writes Malhotra.
Researchers from MIT and elsewhere have tested the impact of generative AI among 5,000 customer service agents within a Fortune 500 software company, reports Jo Constantz for Bloomberg. “The company’s lowest-skilled workers became 35% faster with the tool,” explains Constantz. “The researchers think this was because the AI essentially transferred top performers’ knowledge to less-experienced colleagues through the automatically-generated recommended responses.”
Prof. Danielle Li, graduate student Lindsey Raymond and Stanford University Prof. Erik Brynjolfsson released an “empirical study of the real-world economic effects of new AI systems,” reports Greg Rosalsky for NPR. The researchers found “AI caused a group of workers to become much more productive.” Rosalsky adds that the study also “shines a spotlight on just how powerful AI is, how disruptive it might be, and suggests that this new, astonishing technology could have economic effects that change the shape of income inequality going forward.”
Researchers from MIT and Stanford have found that “artificial intelligence tools like chatbots helped boost worker productivity at one tech company by 14%” reports Jennifer Liu for NBC Boston. “The study is thought to be the first major real-world application of generative AI in the workplace,” writes Liu. “Researchers measured productivity of more than 5,000 customer support agents, based primarily in the Philippines, at a Fortune 500 enterprise software firm over the course of a year.”
Researchers from MIT and elsewhere have found that experienced workers might be more impacted by ChatGPT, reports Mack DeGeurin for Gizmodo. “Customer support agents using a generative AI conversation assistant in a new study saw a 14% uptick in productivity compared to others who didn’t use the tool,” writes DeGeurin.
Popular Science reporter Jamie Dickman writes that using liquid neural networks, MIT researchers have “trained a drone to identify and navigate toward objects in varying environments.” Dickman notes that: “These robust networks enable the drone to adapt in real-time, even after initial training, allowing it to identify a target object despite changes in their environment.”