Iqbal Dhaliwal, executive director of the Abdul Latif Jameel Poverty Action Lab (J-PAL), speaks with NPR reporter Ari Daniel about the positive social impact that can be brought forth by AI. "As this technical revolution unfolds in real time," says Dhaliwal, "we have a responsibility to rigorously study how these technologies can help or harm people's well-being, particularly people who experience poverty, and scale only the most effective AI solutions."
Prof. Daron Acemoglu highlights the economic and societal implications of integrating automation in the workforce, reports Taylor Nicole Rogers for The Financial Times. “Acemoglu says that robots’ current capabilities mean that those most at risk of being displaced are in blue-collar jobs and lack college degrees, which may make it difficult for them to shift into the high-tech roles likely to be created by automation,” writes Rogers.
Writing for Wired, Prof. Daniela Rus, director of CSAIL, highlights the future of “physical intelligence, a new form of intelligent machine that can understand dynamic environments, cope with unpredictability, and make decisions in real time.” Rus writes: “Unlike the models used by standard AI, physical intelligence is rooted in physics; in understanding the fundamental principles of the real world, such as cause-and-effect.”
Sloan research fellow Michael Schrage speaks with Fortune reporter Sheryl Estrada about the impact of AI on CFO roles. “The ongoing ‘Compound AI’ revolution, which involves approaching AI tasks by combining multiple interacting components, will increasingly transform the CFO role into that of an AI-powered chief capital officer (CCO),” says Schrage. “This is an analytics-driven shift that isn’t optional but imperative for enterprise growth.”
Knowable Magazine reporter Katherine Ellison spotlights Future You, a new program developed by researchers at MIT that “offers young people a chance to chat with an online, AI-generated simulation of themselves at age 60.”
Prof. Daron Acemoglu highlights the importance of adopting alternative technologies in the face of AI advancements, reports Jared Newman for Fast Company. “We need investment for alternative approaches to AI, and alternative technologies, those that I would say are more centered on making workers more productive, and providing better information to workers,” says Acemoglu.
Forbes reporter Joe McKendrick spotlights a study by researchers from the MIT Center for Collective Intelligence evaluating “the performance of humans alone, AI alone, and combinations of both.” The researchers found that “human–AI systems do not necessarily achieve better results than the best of humans or AI alone,” explains graduate student Michelle Vaccaro and her colleagues. “Challenges such as communication barriers, trust issues, ethical concerns and the need for effective coordination between humans and AI systems can hinder the collaborative process.”
In an interview with CNBC, Prof. Max Tegmark highlights the importance of increased AI regulation, specifically as a method to mitigate potential harm from large language models. “All other technologies in the United States, all other industries, have some kind of safety standards,” says Tegmark. “The only industry that is completely unregulated right now, which has no safety standards, is AI.”
Researchers from MIT and elsewhere have found that “AI doesn’t even understand itself,” reports Peter Coy for The New York Times. The researchers “asked AI models to explain how they were thinking about problems as they worked through them,” writes Coy. “The models were pretty bad at introspection.”
Prof. Seth Lloyd speaks with NPR Morning Edition host Adam Bearne about recent advancements in quantum chips and the future of quantum computing. "Quantum computers, their ability to do multiple tasks at once, allows them to explore a much larger range of possibilities than is available to classical computers, which can really only do one thing at a time," says Lloyd.
Prof. David Autor has been named a Senior Fellow in the Schmidt Sciences AI2050 Fellows program, and Profs. Sara Beery, Gabriele Farina, Marzyeh Ghassemi, and Yoon Kim have been named Early Career AI2050 Fellows, reports Michael T. Nietzel for Forbes. The AI2050 fellowships provide funding and resources, while challenging “researchers to imagine the year 2050, where AI has been extremely beneficial and to conduct research that helps society realize its most beneficial impacts,” explains Nietzel.
Prof. Daniela Rus, director of CSAIL, speaks with NBC Boston reporter Colton Bradford about her work developing a new AI system aimed at making grocery shopping easier, more personalized and more efficient. “I think there is an important synergy between what people can do and what machines can do,” says Rus. “You can think of it as machines have speed, but people have wisdom. Machines can lift heavy things, but people can reason about what to do with those heavy things.”
Writing for The New York Times, Prof. Anant Agarwal shares AI’s potential to “revolutionize education by enhancing paths to individual students in ways we never thought possible.” Agarwal emphasizes: “A.I. will never replace the human touch that is so vital to education. No algorithm can replicate the empathy, creativity and passion a teacher brings to the classroom. But A.I. can certainly amplify those qualities. It can be our co-pilot, our chief of staff helping us extend our reach and improve our effectiveness.”
Using a new technique developed to examine the risks of multimodal large language models used in robots, MIT researchers were able to have a “simulated robot arm do unsafe things like knocking items off a table or throwing them by describing actions in ways that the LLM did not recognize as harmful and reject,” writes Will Knight for Wired. “With LLMs a few wrong words don’t matter as much,” explains Prof. Pulkit Agrawal. “In robotics a few wrong actions can compound and result in task failure more easily.”
Researchers from MIT and elsewhere have compared 12 large language models (LLMs) against 925 human forecasters for a three-month forecasting tournament to help predict real-world events, including geopolitical events, reports Tomas Gorny for Forbes. "Our results suggest that LLMs can achieve forecasting accuracy rivaling that of human crowd forecasting tournaments,” the researchers explain.