automation

Prof. Daron Acemoglu speaks with CNBC about the potential impact of AI in the workplace. “I think the incentive in the industry… especially with the idea that you have to dominate the market by becoming the largest players, I think those are not helping because those are making us rush down the easiest road, the lowest resistance path, which is often automation,” says Acemoglu. “I don’t think that is going to get us the kind of aspirations that are articulated where we can make blue collar workers, electricians, nurses, teachers much more capable because we have given them tools to be better workers and to make much higher quality services.”

Prof. David Autor speaks with Delphine Strauss of the Financial Times about the risks AI poses to jobs and job quality, but also the technology’s potential to help rebuild middle-class jobs. “The good case for AI is where it enables people with foundational expertise or judgment to do more expert work with less expertise,” says Autor. He adds, “My hope is that we can use AI to reinstate the value of skills held by people without as high a degree of formal education.”

A study by MIT researchers shows that “workers have cost employers a 25% tax rate, while the rate of software and equipment has stood around 5%,” write Diego Areas Munhoz and Samantha Handler for Bloomberg. “This lopsidedness in tax code gives employers more reason to invest in automating goods like machines and computer software instead of workers.”

“Power and Progress,” a new book by Institute Prof. Daron Acemoglu and Prof. Simon Johnson, has been named one of the best new books on economics by the Financial Times. “The authors’ nuanced take on technological development provides insights on how we can ensure the coming AI revolution leads to widespread benefits for the many, not just the tech bros,” writes Tej Parikh.

Writing for The New York Times, Institute Prof. Daron Acemoglu and Prof Simon Johnson make the case that “rather than machine intelligence, what we need is ‘machine usefulness,’ which emphasizes the ability of computers to augment human capabilities. This would be a much more fruitful direction for increasing productivity. By empowering workers and reinforcing human decision making in the production process, it also would strengthen social forces that can stand up to big tech companies.”

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.”

Financial Times correspondent Rana Foroohar spotlights Prof. Daron Acemoglu and Prof. Simon Johnson’s new book, “Power and Progress,” which “explores several moments over the last millennium when technology led to the opposite of shared prosperity.” In the book, Acemoglu and Johnson “take a different approach to the productivity gains of technology and how they get distributed compared with most of their peers.”

Writing for The Hill, Prof. Daniela Rus, director of CSAIL, explores how automation could ease the supply chain crisis. “Automation in these settings doesn’t mean replacing employees, but developing more robust inventory management software and using systems like scanners and conveyors that make our jobs easier,” writes Rus. “This would enable warehouse workers to focus on other more detail-oriented roles, from overseeing the operation of forklifts to improving the efficiencies of distribution centers.”

A new study from researchers at MIT and Dartmouth suggests that the speed of automation should be halved, reports Adi Gaskell for Forbes. Their paper showed that “while investments in automation usually result in higher productivity in firms, and therefore often more employment, it can be harmful to those who are displaced, especially if they have few alternative options,” writes Gaskell.

Graduate student Anna Waldman-Brown writes for Wired about the future of automation technology and how it can impact labor dynamics in the future. “While some scholars believe that our fates are predetermined by the technologies themselves, emerging evidence indicates that we may have considerable influence over how such machines are employed within our factories and offices – if we can only figure out how to wield this power,” writes Waldman-Brown.

TechCrunch reporter Brian Heater spotlights MIT startup Strio.AI, which is aimed at bringing autonomous picking and pruning to strawberry crops.

Prof. David Autor speaks with New York Times columnist Peter Coy about the new book he wrote with Prof. David Mindell and Elisabeth Reynolds, “The Work of the Future: Building Better Jobs in an Age of Intelligent Machines.” Autor explains that: “Most people’s fear of technology is really a fear of capitalism, what the markets will do with the technology. You can’t make a lot of progress if you’re making people poorer at the same time.”

The Economist highlights new work by MIT researchers investigating the impact of automation on the labor market. A study by graduate student Joonas Tuhkuri finds that at Finnish firms “adoption of advanced technologies led to increases in hiring.” Meanwhile a new book by Profs. David Autor, David Mindell and Elisabeth Reynolds concludes that “even if robots do not create widespread joblessness, they may have helped create an environment where the rewards are ‘skewed towards the top.’”

New York Times reporter Steve Lohr spotlights Institute Prof. Daron Acemoglu’s research showing that “excessive automation” has contributed to rising inequality. “We need to redirect technology so it works for people,” says Acemoglu, “not against them.”

Ikigai, an MIT startup, is building automated workflows where human decision making will be a part of the process, reports Ron Miller for Tech Crunch. “What we saw is that there are use cases… [that involve] manual processes in the organizations that were extremely difficult to automate because a fundamental step involved humans making judgements or decisions with data, and where both the data and rules they’re operating on would change very often,” co-founder and CEO Vinayak Ramesh M.Eng ‘18, ‘12 tells Miller.