Prof. David Autor speaks with PBS host Walter Isaacson about the fear surrounding AI’s impact in the workforce and his view that AI could provide new opportunities for middle class workers. “Most of the time, technology is good for the elite and not so good for everybody else,” says Autor. “[AI] is a case where the technology might compete a little bit more with the elite and enable more people to do valuable work,” resulting in higher wages and more job opportunity for the middle class.
Fast Company reporter Shalene Gupta spotlights new research by Prof. David Autor that finds “about 60% of jobs in 2018 did not exist 1940. Since 1940, the bulk of new jobs has shifted from middle-class production and clerical jobs to high-paid professional jobs and low-paid service jobs.” Additionally, the researchers uncovered evidence that “automation eroded twice as many jobs from 1980 to 2018 as it had from 1940 to 1980. While augmentation did add some jobs to the economy, it was not as many as the ones lost by automation.”
Prof. David Autor speaks with New York Times reporter Steve Lohr about his hope that AI can be harnessed to become “worker complementary technology,” enabling individuals to take on more highly skilled work and find better paying jobs. “I do think there is value in imagining a positive outcome, encouraging debate and preparing for a better future,” Autor explains. “This technology is a tool, and how we decide to use it is up to us.”
Prof. David Autor speaks with Bloomberg’s Odd Lots podcast hosts Joe Weisenthal and Tracy Alloway about how AI could be leveraged to improve inequality, emphasizing the policy choices governments will need to make to ensure the technology is beneficial to humans. “Automation is not the primary source of how innovation improves our lives,” says Autor. “Many of the things we do with new tools is create new capabilities that we didn’t previously have.”
Prof. David Autor and Prof. Daron Acemoglu speak with New York Times columnist Peter Coy about the impact of AI on the workforce. Acemoglu and Autor are “optimistic about a continuing role for people in the labor market,” writes Coy. “An upper bound of the fraction of jobs that would be affected by A.I. and computer vision technologies within the next 10 years is less than 10 percent,” says Acemoglu.
Washington Post columnist Eduardo Porter spotlights various MIT research efforts aimed at ensuring that AI is used to empower human workers rather than replace them. Prof. David Autor notes: “AI, if used well, can assist with restoring the middle-skill, middle-class heart of the U.S. labor market that has been hollowed out by automation and globalization.”
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.
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.
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.”