Prof. Pattie Maes speaks with Wired reporter Reece Rogers about the potential benefits and challenges posed by AI agents. “The way these systems are built, right now, they're optimized from a technical point of view, an engineering point of view,” says Maes. “But, they're not at all optimized for human-design issues.”
Noubar Afeyan PhD '87 and a member of the MIT Corporation speaks with Boston Globe reporter Aaron Pressman about the future of artificial general intelligence (AGI) and “superintelligent” AI. “Humans have long developed tools, microscopes, mass spectrometers, you name it, to help them be able to understand nature better,” says Afeyan. “Now one of the tools, in the case of machine [learning], we’re elevating to the level of a whole new intelligence.”
Prof. Daron Acemoglu speaks with Financial Times reporter Rana Foroohar about the impact of automation on the labor market. “It’s likely that the short- to midterm gains from AI will be distributed unequally, and will benefit capital more than labor,” says Acemoglu.
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."
Researchers at MIT and elsewhere have found “that investors who use OpenAI’s GPT-4o to summarize earnings calls realize higher returns than those who don’t,” reports Kyle Wiggers for TechCrunch. “The researchers recruited investors and had GPT-4o give them AI summaries aligned with their investing expertise,” explains Wiggers. “Sophisticated investors got more technical AI-generated notes, while novices got simpler ones.”
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.”
MIT Humanist Chaplain Greg Epstein discusses key insights from his new book, “Tech Agnostic: How Technology Became the World’s Most Powerful Religion, and Why It Desperately Needs a Reformation,” with Fast Company. “One of the biggest blessings skeptical Humanism can offer a world of tech-certainty, in which AI chatbots freely and frequently hallucinate garbage answers and advice (like Google Gemini’s suggestion to use glue to keep cheese from sliding off pizza), is that it’s honorable to admit not knowing an answer,” explains Epstein.
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.”
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.”
Liquid AI, an MIT startup, is developing technology that “holds the same promise of writing, analyzing, and creating content as its rivals while using far less computing power,” reports Aaron Pressman for The Boston Globe.
A new study by researchers at MIT and elsewhere has found that “87% of people say employees in their organization are confused to a certain degree about where to turn for data and tech services and issues,” reports Rachel Curry for CNBC. “Most of the organizations whose leaders responded to the survey had multiple executive roles in the tech and data spaces,” explains Curry.