Researchers at MIT have released a new working paper that aims to quantify the severity and speed with which AI systems could replace human workers, reports Hiawatha Bray for The Boston Globe. The paper concluded that “it’s not enough for AI systems to be good at tasks not performed by people,” explains Bray. “The system must be good enough to justify the cost of installing it and redesigning the way a job is done.”
A new working paper by MIT researchers predicts “only 23% of wages linked to vision-related tasks could be feasibly cost-effectively replaced by AI,” reports Gil Press for Forbes. The researchers “argue that their findings apply also to generative AI or the automation of language-related tasks,” writes Press.
Wall Street Journal reporter Lindsey Choo spotlights Principal Research Scientist Matthias Winkenbach and his work developing an AI model to help delivery drivers find the best routes. The model would “take into consideration complex real-world constraints,” such as allowing drivers to, “choose a route that may not be the shortest but allows them to park more conveniently or unload packages in safer spaces,” writes Choo.
Researchers at MIT have discovered how a new computational imaging algorithm can capture user interactions through ambient light sensors commonly found in smartphones, reports Davey Winder for Forbes. “By combining the smartphone display screen, an active component, with the ambient light sense, which is passive, the researchers realized that capturing images in front of that screen was possible without using the device camera,” explains Winder.
Alicia Chong Rodriguez SM ’17, SM ’18 founded Bloomer Tech, a health tech startup that aims to improve health care diagnostics for women using medical-grade data to develop new therapies and care models, reports Carol Eisenberg for The Washington Post. Rodriguez and her colleagues "developed, patented and tested flexible washable circuits to turn articles of clothing into devices that can relay reams of information to the wearer’s smartphone,” writes Eisenberg.
Writing for Wired, Institute Prof. Daron Acemoglu predicts that expectations for generative AI will need to recalibrated during the year ahead. Acemoglu notes that he believes in 2024, “generative AI will have been adopted by many companies, but it will prove to be just ‘so-so automation’ of the type that displaces workers but fails to deliver huge productivity improvements.”
Prof. Jessika Trancik speaks with Associated Press reporter Alexa St. John to discuss electric vehicle emissions and ownership costs. Trancik notes, “buyers should consider total cost of ownership, which for an EV is generally less than that of a gas-powered counterpart due to savings on maintenance and fuel.”
Writing for Wired, research scientist Kate Darling highlights the importance of addressing the fundamentally human behaviors that have been incorporated into AI chatbots. “Research in human-computer and human-robot interaction shows that we love to anthropomorphize—attribute humanlike qualities, behaviors, and emotions to—the nonhuman agents we interact with, especially if they mimic cues we recognize,” writes Darling. “And, thanks to recent advances in conversational AI, our machines are suddenly very skilled at one of those cues: language.”
Prof. David Autor speaks with Bloomberg about the future of generative AI and the technology’s potential impact on productivity and the labor market. “When we interact with AI, we need to learn how to treat it not as authoritative, but as a guide to support decision making, and that’s really critical,” says Autor.
MIT researchers have found that job applicants who used AI to improve spelling and grammar on their resumes were eight percent more likely to be hired, reports Bryan Robinson for Forbes. “If you take two identical workers with the same skills and background, the one with the better-written resume is more likely to get hired,” explains graduate student Emma van Inwegen. “The takeaway is that employers actually care about the writing in the resume; it’s not just a correlation.”
Prof. Canan Dagdeviren and her team have developed a wearable ultrasound patch that can be used to screen for breast cancer at home, reports Grace Browne for Wired. “Dagdeviren wants to give people the opportunity to know what’s happening inside their bodies every day, the same way we check the weather forecast,” writes Browne.
Researchers from MIT have developed, “nanoelectronics they hope can one day enter the brain and treat conditions like Alzheimer’s by monitoring some of these brain patterns,” reports Elizabeth Hlavinka for Salon. “Their device, which they call Cell Rover, serves as a sort of antenna that can help external devices monitor cells.”
Former Postdoc Rana el Kaliouby speaks with Boston Globe reporter Janelle Nanos about her work focused on infusing emotional intelligence into AI. “I’m an optimist, but I’m a realist as well, and I can see where this can go wrong,” says Kaliouby. “I think one of the biggest concerns around AI is bias and how we’re building bias into these models and then deploying them at scale everywhere around the world.”
Dynamic Labs, co-founded by Itai Turbahn '11 and Yoni Goldberg '09, MEng '10, offers “tech for crypto and non-crypto companies alike to create seamless login experiences backed by digital wallets,” reports Marco Quiroz-Gutierrez for Fortune. “The firm’s wallet-based business is twofold,” explains Quiroz-Gutierrez. “It offers a customizable all-in-one service that can either push the crypto wallet technology to the background for less savvy users or put it front and center for Web3 natives.”
Prof. Manolis Kellis speaks with USA Today reporter Josh Peter about the potential impact of AI in developing undetectable performance-enhancing drugs (PEDs). "The most feasible approach would be using generative AI to alter existing PEDs that trigger drug tests in a way that makes those drugs undetectable by current testing technology,” Kellis notes.