Labor and jobs

Prof. Danielle Li and graduate student Lindsey Raymond speak with NPR hosts Wailin Wong and Adrian Ma about how generative artificial intelligence could impact the workplace based on their research examining how an AI chatbot affected workers at customer contact centers. “A lot of what customer service is, is about managing people's feelings 'cause people come, they're tired or whatever,” says Li. “And so in some sense there's kind of this sort of human soft skills component that these technologies are able to capture in a way that prior technologies couldn't.”

Prof. Daron Acemoglu speaks with VOX Talks host Tim Phillips about his new book written with Prof. Simon Johnson, “Power and Progress.” The book explores “how we can redirect the path of innovation,” Phillips explains.

J. Daniel Kim PhD ’20 and Minjae Kim SM ’17 PhD ‘18 have found that young companies “were less likely than similar companies to change their line of business or location” after the departure of a founder, reports Kevin Lewis for The Boston Globe. “Companies that did change their line of business tended to perform better, especially around recessions,” explains Lewis. “This supports the notion that the loss of a founder tends to impede necessary change.”  

Bloomberg reporter Adrian Wooldridge spotlights a new book titled “Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity” by Prof. Simon Johnson and Prof. Daron Acemoglu. “The authors’ main worry about AI is not that it will do something unexpected like blowing up the world,” writes Wooldridge. “It is that it will supercharge the current regime of surveillance, labor substitution and emotional manipulation.”

Institute Prof. Daron Acemoglu discusses AI and the labor market, the history of technological progress and Turkey with Financial Times columnist Rana Foroohar. “I think the skills of a carpenter or a gardener or an electrician or a writer, those are just the greatest achievements of humanity, and I think we should try to elevate those skills and elevate those contributions,” says Acemoglu. “Technology could do that, but that means to use technology not to replace these people, not to automate those tasks, but to increase their productivity.” 

Prof. Daron Acemoglu speaks with Wired reporters Gideon Lichfield and Lauren Goode about his new book with Prof. Simon Johnson, “Power and Progress.” Acemoglu explains that: “The way I would put it is, don't think of your labor as a cost to be cut. Think of your labor as a human resource to be used better, and AI would be an amazing tool for it. Use AI to allow workers to make better decisions.”

Guardian reporter Will Hutton spotlights “Power and Progress,” a new book by Institute Prof. Daron Acemoglu and Prof. Simon Johnson that makes the case that “the political struggle has consistently aimed to contain excessive inequality of wealth, and act collectively to share prosperity. It is successive waves of transformative technologies above all that bring the productivity gains that create great wealth, only for it to be captured by the incumbent elite.”

Researchers from MIT and elsewhere have found chance encounters among employees of different companies can kickstart innovation, reports Bart Ziegler for The Wall Street Journal. Researchers explained that such chance meetings “may spark a conversation that leads to a transfer of knowledge or a collaboration,” writes Ziegler.

Prof. Yossi Sheffi, director of the MIT Center for Transportation and Logistics, speaks with David Wade of WBZ News about AI and the future of work. "Jobs will change, clearly some jobs will disappear. I don't want to minimize it," says Sheffi. “Some jobs will disappear, but this is a very small number. Most of the impact of technology is to assist."

Prof. David Autor speaks with Greg Rosalsky of NPR’s Planet Money about the potential benefits and downsides of AI, sharing his hope that with the right policies in place to help prepare workers AI could be harnessed to help “reinstate the middle class.” Says Autor: "Basically, the middle-skilled workers of the future could be people who have foundational skills in healthcare, in the trades, in travel and services. Then, with the help of AI, they could get really good at these jobs.”

Wired reporter Caitlin Harrington writes that a study by researchers from MIT and Stanford highlights the impact of generative AI tools on workers and raises a “provocative new question: Should the top workers whose chats trained the bot be compensated?”

Researchers from MIT have found that “although women received higher performance ratings than their male colleagues, they received 8.3% lower ratings for potential than men,” reports Caroline Castrillon for Forbes. “Because those ratings strongly predict promotions, female employees were 14% less likely to be promoted than male ones,” writes Castrillon.

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.”

Prof. Simon Johnson and Prof. Yossi Sheffi speak with Boston 25 about the potential impact of AI on the labor market. “We need people to have what’s called soft skills,” says Sheffi. “They need to be able to convince people, manage people, work with people, partner with people.” Johnson notes while there are still fields that are safe bets, but notes that the speed with which [AI] is moving and currently the acceleration is really dramatic.”

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.”