Writing for The Los Angeles Times, Institute Prof. Daron Acemoglu and Prof. Simon Johnson make the case that the development of artificial intelligence should be shifted “toward a focus on ‘machine usefulness,’ the idea that computers should primarily enhance human capabilities. But this needs to be combined with an explicit recognition that any resulting productivity gains must be shared with workers, in terms of higher incomes and better working conditions.”
Boston Globe reporter Robert Weisman spotlights Integrated Biosciences, a startup co-founded by MIT researchers that is using artificial intelligence to identify anti-aging drug candidates. “We’re trying to go after aging and aging-associated disorders,” says postdoc Felix Wong. “We all know loved ones who have suffered from some of these conditions.”
Prof. Marzyeh Ghassemi speaks with NPR host Emily Kwong and correspondent Geoff Brumfiel about how artificial intelligence could impact medicine. “When you take state-of-the-art machine-learning methods and systems and then evaluate them on different patient groups, they do not perform equally,” says Ghassemi.
Research from MIT and elsewhere have developed a mobile app that uses computer-vision techniques and AI to detect post-surgery signs of infection as part of an effort to help community workers in Kirehe, a district in Rwanda’s Eastern province, reports Shefali Malhotra for Science. “The researchers are now improving the app so it can be used across more diverse populations such as in Ghana and parts of South America,” writes Malhotra.
Researchers from MIT and elsewhere have tested the impact of generative AI among 5,000 customer service agents within a Fortune 500 software company, reports Jo Constantz for Bloomberg. “The company’s lowest-skilled workers became 35% faster with the tool,” explains Constantz. “The researchers think this was because the AI essentially transferred top performers’ knowledge to less-experienced colleagues through the automatically-generated recommended responses.”
Prof. Danielle Li, graduate student Lindsey Raymond and Stanford University Prof. Erik Brynjolfsson released an “empirical study of the real-world economic effects of new AI systems,” reports Greg Rosalsky for NPR. The researchers found “AI caused a group of workers to become much more productive.” Rosalsky adds that the study also “shines a spotlight on just how powerful AI is, how disruptive it might be, and suggests that this new, astonishing technology could have economic effects that change the shape of income inequality going forward.”
Researchers from MIT and Stanford have found that “artificial intelligence tools like chatbots helped boost worker productivity at one tech company by 14%” reports Jennifer Liu for NBC Boston. “The study is thought to be the first major real-world application of generative AI in the workplace,” writes Liu. “Researchers measured productivity of more than 5,000 customer support agents, based primarily in the Philippines, at a Fortune 500 enterprise software firm over the course of a year.”
Researchers from MIT and elsewhere have found that experienced workers might be more impacted by ChatGPT, reports Mack DeGeurin for Gizmodo. “Customer support agents using a generative AI conversation assistant in a new study saw a 14% uptick in productivity compared to others who didn’t use the tool,” writes DeGeurin.
Popular Science reporter Jamie Dickman writes that using liquid neural networks, MIT researchers have “trained a drone to identify and navigate toward objects in varying environments.” Dickman notes that: “These robust networks enable the drone to adapt in real-time, even after initial training, allowing it to identify a target object despite changes in their environment.”
Researchers at MIT have developed a new type of autonomous drone that uses advanced neural networks to fly, reports Tony Ho Tran for The Daily Beast. “The new design allows the drone to make better decisions when flying through completely new environments,” writes Tran, “and could have future applications in self-driving cars, search and rescue operations, wildlife monitoring, or even diagnosing medical issues.”
Researchers from MIT and elsewhere published a paper exploring the abilities of language models and how they differ from those of humans, reports Will Knight for Wired. Prof. Josh Tenenbaum says “GPT-4 is remarkable but quite different from human intelligence in a number of ways,” writes Knight. “It lacks the kind of motivation that is crucial to the human mind.”
NBC News highlights how researchers from MIT and MGH have developed a new AI tool, called Sybil, that can “accurately predict whether a person will develop lung cancer in the next year 86% to 94% of the time.” NBC News notes that according to experts, the tool "could be a leap forward in the early detection of lung cancer.”
Prof. Marzyeh Ghassemi speaks with WBUR reporter Geoff Brumfiel about her research studying the use of artificial intelligence in healthcare. “When you take state-of-the-art machine learning methods and systems and then evaluate them on different patient groups, they do not perform equally,” says Ghassemi.
Researchers at MIT have created a four-legged robot called DribbleBot, reports Caroline Goggin for WHDH. The robot “can dribble a soccer ball under the same conditions as humans, using onboard sensors to travel across different types of terrain.”
Popular Science reporter Andrew Paul spotlights how researchers from MIT CSAIL have developed a soccer-playing robot, dubbed DribbleBot, that can handle a variety of real-world terrains. “DribbleBot showcases extremely impressive strides in articulation and real-time environmental analysis. Using a combination of onboarding computing and sensing, the team’s four-legged athlete can reportedly handle gravel, grass, sand, snow, and pavement, as well as pick itself up if it falls.”