Former MIT Prof. Edward Fredkin, “a pioneer in artificial intelligence and a maverick theorist,” has died at 88, reports Alex Williams for The New York Times. Williams notes that Fredkin, who worked on Project MAC during his time at MIT, was “fueled by a seemingly limitless scientific imagination and a blithe indifference to conventional thinking.” Prof. Gerald Sussman recalls that “Ed Fredkin had more ideas per day than most people have in a month.”
MIT Schwarzman College of Computing Dean Daniel Huttenlocher discusses how artificial intelligence has impacted print media at the Aspen Ideas Festival, reports John Frank for Axios. “Most of us grew up in a world where the word print was something that was authoritative,” says Huttenlocher, of how people will need to be on the lookout for misinformation.
MIT Schwarzman College of Computing Dean Daniel Huttenlocher speaks at the Aspen Ideas Festival on how to regulate AI while maximizing its positive impact, reports NBC. “I think when we think about regulation [of artificial intelligence] we need to think about this in the ways we’ve traditionally thought about things – risk, reward, tradeoffs – and that tends to be domain specific,” says Huttenlocher. “It’s hard to have sort of an abstract notion of this new technology and what the risk [and] reward is across all domains.”
Writing for Bloomberg, Prof. Thomas Malone about the need to adapt copyright laws in the era of generative AI. “One promising possibility is to introduce a new body of law based on the premise that different legal protections are appropriate when these massive AI systems can process vast amounts of information far faster and less expensively than humans can,” writs Malone.
Prof. Marzyeh Ghassemi speaks with Yahoo News reporter Rebecca Corey about the benefits and risks posed by the use of AI tools in health care. “I think the problem is when you try to naively replace humans with AI in health care settings, you get really poor results,” says Ghassemi. “You should be looking at it as an augmentation tool, not as a replacement tool.”
Prof. Kevin Esvelt and his students have found that language-generating AI models could make it easier to create pandemic potential pathogens, reports Kelsey Piper for Vox.
Researchers at MIT have developed a new artificial intelligence system aimed at helping autopilot avoid obstacles while maintaining a desirable flight path, reports Kyle Wiggers for TechCrunch. “Any old algorithm can propose wild changes to direction in order to not crash, but doing so while maintaining stability and not pulping anything inside is harder,” writes Wiggers.
Boston Globe reporter Mike Orcutt spotlights Prof. Silvio Micali and Prof. Shafi Goldwasser for their work developing the theory behind zero-knowledge proofs and their contributions to the field of modern cryptography.
“Power and Progress,” a new book by Institute Prof. Daron Acemoglu and Prof. Simon Johnson, has been named one of the best new books on economics by the Financial Times. “The authors’ nuanced take on technological development provides insights on how we can ensure the coming AI revolution leads to widespread benefits for the many, not just the tech bros,” writes Tej Parikh.
Writing for The New York Times, Institute Prof. Daron Acemoglu and Prof Simon Johnson make the case that “rather than machine intelligence, what we need is ‘machine usefulness,’ which emphasizes the ability of computers to augment human capabilities. This would be a much more fruitful direction for increasing productivity. By empowering workers and reinforcing human decision making in the production process, it also would strengthen social forces that can stand up to big tech companies.”
Graduate student Kartik Chandra writes for Inside Higher Education about how many of this year’s college graduates are feeling anxiety about new AI technologies. “We scientists are still debating the details of how AI is and is not humanlike in its use of language,” writes Chandra. “But let’s not forget the big picture: unlike AI, you speak because you have something to say.”
Neil Thompson, director of the FutureTech research project at MIT CSAIL and a principal investigator MIT’s Initiative on the Digital Economy, speaks with Politico reporter Mohar Chatterjee about generative AI, the pace of computer progress and the need for the U.S. to invest more in developing the future of computing. “We need to make sure we have good secure factories that can produce cutting-edge semiconductors,” says Thompson. “The CHIPS Act covers that. And people are starting to invest in some of these post-CMOS technologies — but it just needs to be much more. These are incredibly important technologies.”
Prof. Daron Acemoglu speaks with VOX Talks host Tim Phillips about his new book written with Prof. Simon Johnson, “Power and Progress.” The book explores “how we can redirect the path of innovation,” Phillips explains.
MIT researchers have developed a new method to make chatbots more factual, reports Gerrit De Vynck for The Washington Post. “The researchers proposed using different chatbots to produce multiple answers to the same question and then letting them debate each other until one answer won out,” explains Vynck. “The researchers found using this ‘society of minds’ method made them more factual.”
MIT researchers have developed a new machine-learning technique that can identify which pixels in an image represent the same material, which could help with robotic scene understanding, reports Kyle Wiggers for TechCrunch. “Since an object can be multiple materials as well as colors and other visual aspects, this is a pretty subtle distinction but also an intuitive one,” writes Wiggers.