Writing for Financial Times, economist Ann Harrison spotlights research by Prof. Daron Acemoglu, Pascual Restrepo PhD '16 and Prof. David Autor, that explores the impact of automation on jobs in the United States. Acemoglu and Restrepo have “calculated that each additional robot in the US eliminates 3.3 workers” and that “most of the increase in inequality is due to workers who perform routine tasks being hit by automation,” writes Harrison.
A study by MIT researchers has uncovered an, “intricate relationship between jobs and the nation’s energy transition,” reports Kaleigh Harrison for Environment + Energy Leader. The study, “presents an unprecedented county-level examination of the U.S., identifying regions most intertwined with fossil fuels – ranging from intensive drilling and mining operations to heavy manufacturing sectors,” writes Harrison. “The findings underscore not only the expected impact on traditional energy bastions but also highlight the broader, often overlooked, implications for areas heavily invested in manufacturing.”
Researchers from MIT have found that our current retirement savings system “largely favors higher-income and white employees,” reports Remy Samuels for Plan Sponsor. The researchers concluded that “employer matching and tax benefits are more unequally distributed than wages,” explains Samuels. “While the median Black and Hispanic earners receive 75 cents and 79 cents, respectively, for every dollar of earnings received by the median white earner, median Black and Hispanic earners receive only about 50 cents for every dollar of matching contributions that median white earners receive.”
Fast Company reporter Kristin Toussaint spotlights how MIT researchers have developed a new map detailing how the shift to clean energy could impact jobs around the country. The researchers found that workers could be most impacted in areas that drill for oil and gas, as well as “regions with a high concentration of manufacturing, agriculture, and construction—all industries that rely heavily on coal, oil, and gas.”
New York Times opinion writer Peter Coy spotlights the MIT Shaping the Future of Work Initiative, a new effort aimed at analyzing the forces that are eroding job quality for non-college workers and identifying ways to move the economy onto a more equitable trajectory. Nothing is “inexorable,” said Prof. Daron Acemoglu during the project’s kickoff event. “The answer in most cases is, AI will do whatever we choose it to do.”
In a new study examining the potential impact of AI on jobs that employ computer vision, MIT researchers found, “a vast majority of jobs previously identified as vulnerable to AI are not economically beneficial for employers to automate at this time,” reports Catherine Thorbecke for CNN. “In many cases, humans are the more cost-effective way, and a more economically attractive way, to do work right now,” says Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL. “What we’re seeing is that while there is a lot of potential for AI to replace tasks, it’s not going to happen immediately.”
A new working paper by MIT researchers finds that artificial intelligence is not currently a cost-effective replacement in jobs where computer vision is employed, reports Saritha Rai for Bloomberg. “Our study examines the usage of computer vision across the economy, examining its applicability to each occupation across nearly every industry and sector,” explains Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL. “We show that there will be more automation in retail and healthcare, and less in areas like construction, mining or real estate.”
A new working paper by MIT researchers focuses on whether human work, including vision tasks, are worth replacing with AI computer vision, reports Jeremy Hsu for New Scientist. “There are lots of tasks that you can imagine AI applying to, but actually cost-wise you just wouldn’t want to do it,” says Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL.
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.
The Economist spotlights new research by Prof. Ivan Werning suggesting a refined economic model to address the post-pandemic economy. Werning’s model adjusts “not just to a shift in demand from services to goods, but to supply-chain disruption, energy shocks and employees in some sectors working from home,” explains The Economist. “As such, inflation moved through the economy in waves, starting in select goods then spreading out.”
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. Julie Shah speaks with Wall Street Journal reporter Lauren Weber about the implementation of automation in the work force. According to Shah, “when companies adopt automation successfully, they end up adding workers as they become more productive and fill more orders,” writes Weber. “And machines’ lack of flexibility has often resulted in what Shah calls ‘zero-sum automation,’ where gains in productivity are canceled out by the need for people to fix or reprogram robots and compensate for their drawbacks.”
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.”