Prof. Sherry Turkle warns against AI systems that simulate deceased partners, making it hard for the bereaved to “let go,” reports Dan Milmo for The Guardian. Breakthroughs in generative AI are enabling realistic conversations, but experts harbor concerns about the vulnerability of users and lack of regulation. “It’s something we are inflicting on ourselves because it’s such a seductive technology,” Turkle says.
Prof. Regina Barzilay spoke at The Futurist Summit: The Age of AI – an event hosted by The Washington Post – about the influence of AI in medicine. “When we're thinking today how many years it takes to bring new technologies [to market], sometimes it's decades if we’re thinking about drugs, and very, very slow,” Barzilay explains. “With AI technologies, you've seen how fast the technology that you're using today is changing.”
Researchers at MIT have found that prospective job applicants who utilized basic AI modules in their application process were, on average, more likely to get hired and receive higher wages, reports Maria Gracia Santillana Linares for Forbes. “[Applicants] with access to the technology are more likely to get hired without any negative implications [from] employers,” says graduate student Emma Wiles.
MIT researchers used tools of computational complexity and mathematical concepts to prove that no analysis of the Super Mario Bros video game level “can say for sure whether or not it can ever be completed,” reports Matthew Sparkes for New Scientist. “The idea is that you’ll be able to solve this Mario level only if this particular computation will terminate, and we know that there’s no way to determine that, and so there’s no way to determine whether you can solve the level,” says Prof. Erik Demaine.
Washington Post reporter Carolyn Johnson spotlights how Prof. Laura Schulz and her colleagues have been exploring why ChatGPT-4 performs well on conversation and cognitive tests, but flunks reasoning tests that are easy for young children. Schulz makes the case that to understand intelligence and create it, childhood learning processes should not be discounted. “That’s the kind of intelligence that really might give us a big picture,” Schulz explains. “The kind of intelligence that starts not as a blank slate, but with a lot of rich, structured knowledge — and goes on to not only understand everything we have ever understood, across the species, but everything we will ever understand.”
Prof. Hal Abelson speaks with Inside Higher Ed reporter Lauren Coffey about AI policies in academia. “We put tremendous emphasis on creating with AI but that’s the sort of place that MIT is,” says Abelson. “It’s about making things. Other places have a very different view of this.”
Tomás Vega SM '19 is CEO and co-founder of Augmental, a startup helping people with movement impairments interact with their computer devices, reports Popular Science’s Andrew Paul. Seeking to overcome the limitations of most brain-computer interfaces, the company’s first product is the MouthPad, leveraging the tongue muscles.“Our hope is to create an interface that is multimodal, so you can choose what works for you,” said Vega. “We want to be accommodating to every condition.”
New York Times columnist Thomas Edsall spotlights recent research by Profs. Daron Acemoglu, David Autor and Simon Johnson, in which they explore whether artificial intelligence could be a beneficial tool for workers. “It is quite possible to leverage generative AI as an informational tool that enables various different types of workers to get better at their jobs and perform more complex tasks,” explains Acemoglu. However, he notes “to turn generative AI pro-worker, we need a major course correction.”
Researchers at MIT have designed an “AI-powered chatbot that simulates a user’s older self and dishes out observations and pearls of wisdom,” reports Ian Sample for The Guardian. “The goal is to promote long-term thinking and behavior change,” says graduate student Pat Pataranutaporn. “This could motivate people to make wiser choices in the present that optimize for their long-term wellbeing and life outcomes.”
Forbes reporter Michael Bernick spotlights Ultranauts, founded by Rajesh Anandan ’95 SM ‘96 and Art Shectman ‘95, which provides software testing services, quality engineering and test automation, data governance, and a recently launched suite of AI products to improve employee performance. The company employees people in 30 states, “75% of whom are neurodivergent.”
Richard Nieva reports on recent newcomers to Forbes’ 2024 Midas List, which features the magazine’s picks for the world’s best capital investors. Wesley Chan SB '00 SM '01 spent 14 years at Google, which “informed his focus on consumer tech startups,” Nieva writes.
Boston Globe reporter James McCown highlights the architectural design of the new MIT Schwarzman College of Computing, noting that it is, “the most exciting work of academic architecture in Greater Boston in a generation.”Dean Daniel Huttenlocher adds: “The building was designed to be the physical embodiment of the college’s mission of fortifying studies in computer science and artificial intelligence. The building’s transparent and open design is already drawing a mix of people from throughout the campus and beyond.”
Prof. Daron Acemoglu’s new study projects just mild economic upside in the U.S. stemming from AI advancement, writes Business Insider’s Filip De Mott. According to Acemoglu, AI-led U.S. GDP growth in the next 10 years will rise just 0.93% to 1.16%, due to uncertainty on how much AI can really advance total factor productivity.
Prof. Regina Barzilay joins The Economist’s “Babbage” podcast to discuss how artificial intelligence could enable health care providers to understand and treat diseases in new ways. Host Alok Jha notes that Barzilay is determined to “overcome those challenges that are standing in the way of getting AI models to become useful in health care.” Barzilay explains: “I think we really need to change our mindset and think how we can solve the many problems for which human experts were unable to find a way forward.”
Current AI models require enormous resources and often provide unpredictable results. But graduate student Ziming Liu and colleagues have developed an approach that surpasses current neural networks in many respects, reports Manion Bischoff for Scientific American. “So-called Kolmogorov-Arnold networks (KANs) can master a wide range of tasks much more efficiently and solve scientific problems better than previous approaches,” Bischoff explains.