Research Scientist Neil Thompson speaks with New York Times reporter Hank Sanders about the economic and social impact of AI technology in the fast-food industry. Thompson explains that “voice A.I. is inaccurate often enough that it requires some level of human oversight, which decreases cost savings,” writes Hank.
Wall Street Journal reporter Justin Lahart spotlights the work of Prof. David Autor, an economist whose “thinking helped change our understanding of the American labor market.” Harvard Prof. Lawrence Katz says Autor has “probably been the most insightful and influential scholar of the labor market” in decades. “To me, the labor market is the central institution of any society,” says Autor. “The fastest way to improve people’s welfare is to improve the labor market.”
Prof. Daron Acemoglu speaks with Greg Rosalsky of NPR’s Planet Money about AI’s potential effect on jobs, specifically the translation business. “I think how good AI has become is often exaggerated,” says Acemoglu. “But there is pretty much nothing that humans do as meaningful occupation that generative AI can now do. So in almost everything it can at best helps humans, and at worst, not even do that.”
Researchers at MIT and elsewhere have “outlined the costs and benefits of artificial intelligence in health care, education and the workforce,” reports Ruth Reader, Daniel Payne, and Carmen Paul for Politico. The researchers say “policymakers should study the real-world implications of the technology and consider using AI to inform policy,” writes Politico.
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.
A new paper by Prof. Daron Acemoglu and Prof. Simon Johnson uses the impact of automation in the textile industry to predict potential similar effects from AI, writes Bloomberg’s Andy Mukherjee. Noting the parallels between the Indian textile industry and disruption currently underway in tech outsourcing, the economists write “the impact of automation on workers today is more complex than an automatic linkage from higher productivity to better wages.”
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.”
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.”
An essay co-authored by Prof. Simon Johnson in Project Syndicate argues that for all the predictions about AI’s effect on the workforce, the most likely outcome is that many people will face pressure to change jobs as the labor market adjusts. Policymakers must focus on human capital, he writes, and “shared prosperity can flow from new technology, but only if its adoption is accompanied by upgraded human skills and more proactive worker redeployment.”
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.
Financial Times reporter Robin Wigglesworth spotlights Prof. Daron Acemoglu’s new research that predicts relatively modest productivity growth from AI advances. On generative AI specifically, Acemoglu believes that gains will remain elusive unless industry reorients “in order to focus on reliable information that can increase the marginal productivity of different kinds of workers, rather than prioritizing the development of general human-like conversational tools,” he says.
Writing for the Financial Times, Jon Hilsenrath revisits lessons from the occupational shifts of the early 2000s when probing AI’s potential impact on the workplace. He references Prof. David Autor’s research, calling him “an optimist who sees a future for middle-income workers not in spite of AI, but because of it…creating work and pay gains for large numbers of less-skilled workers who missed out during the past few decades.”
Prof. David Autor is a guest of Meghna Chakrabarti on WBUR’s On Point, discussing his research on the potential impact of AI on the workforce. Autor says “AI is a tool that can enable more people with the right foundational training and judgment to do more valuable work.”
The Hill reporter Tobias Burns spotlights the efforts of a number of MIT researchers to better understand the impact of generative AI on productivity in the workforce. One research study “looked as cases where AI helped improved productivity and worker experience specifically in outsourced settings, such as call centers,” explains Burns. Another research study explored the impact of AI programs, such as ChatGPT, among employees.
Writing for Project Syndicate, Institute Prof. Daron Acemoglu and Prof. Simon Johnson draw upon the work of economist David Ricardo and his insights on the Industrial Revolution to explore how to respond to the challenge posed by AI to good jobs. “It is still possible to have pro-worker AI, but only if we can change the direction of innovation in the tech industry and introduce new regulations and institutions,” they write.