Prof. Abhijit Banerjee shares advice with Nature reporter Helen Pearson for those in science careers looking to find “satisfaction from their work – and make a difference to the world.” Banerjee attributes “his own career to a series of happy accidents,” writes Pearson. Banerjee says, “a lot of it is accidents that make us who we are…sometimes we learn something about ourselves as a result of them.”
Prof. Jon Gruber speaks with GBH hosts Jim Braude and Margery Eagan about the impact of political corruption on economics worldwide. The United States “has an incredibly dedicated, professionalized civil government,” says Gruber. “People go into government and spend much of their careers serving really the public good.”
Writing for Forbes, Research Scientist, Christian Catalini, founder of the Cryptoeconomics Lab, discusses the future of crypto. “We've now been waiting for crypto's "killer app" for over a decade, just like AI was waiting for its ChatGPT moment,” writes Catalini. “By focusing on utility instead of speculation, crypto can finally deliver on its long-awaited promise.”
Quartz reporter Michelle Cheng spotlights a working paper by Prof. David Autor which shows that “AI could enable more workers to perform higher-stakes, decision-making tasks that are currently relegated to highly-educated workers such as doctors and lawyers.” As Autor explains, “in essence, AI used well can assist with restoring the middle-skill, middle-class heart of the US labor market that has been hollowed out by automation and globalization.”
Axios reporter Courtenay Brown spotlights a new report by researchers from MIT and the Brookings Institute that finds poorer counties in the U.S. with lower employment rates have, “attracted a large share of the hundreds of billions of dollars allocated for clean energy projects, semiconductor mega-factories and more.” Brian Deese, an Innovation Fellow at MIT, explains that: “Distressed communities are attracting new clean energy and semiconductor investment at roughly twice the rate of traditional private investment. If this trend continues, it has the potential to change the economic geography of the country and create economic opportunity in parts of this country that too many people have written off in the past.”
Reuters reporter Timothy Appell spotlights a new study by researchers from MIT and the Brookings Institution that finds, “a surge of factory building fueled by Biden administration investments in ‘strategic sectors’ such as clean energy and semiconductors has so far flowed disproportionately to U.S. counties with relatively distressed economies and notably has not tracked ‘Democratic geography.’”
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.”
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 reporter Ana Swanson spotlights a working paper co-authored by Prof. David Autor which suggests “the sweeping tariffs that former President Donald J. Trump imposed on China and other American trading partners were simultaneously a political success and an economic failure.” Autor and his colleagues found that “the aggregate effect on U.S. jobs of the three measures — the original tariffs, retaliatory tariffs and subsidies granted to farmers — were ‘at best a wash, and it may have been mildly negative.’”
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.”
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.”
Bloomberg reporter Boyan Ivanchev spotlights research by Prof. Drazen Prelec and Prof. Duncan Simester that finds, “credit card buyers were willing to pay over 100% more for tickets, due to the behavioral pattern that psychologically causes the credit card buyer to perceive the purchase as a type of deferred payment, and therefore, not immediately feel the psychological discomfort, as when letting this amount go when paying cash.”
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. Jessika Trancik speaks with Associated Press reporter Alexa St. John to discuss electric vehicle emissions and ownership costs. Trancik notes, “buyers should consider total cost of ownership, which for an EV is generally less than that of a gas-powered counterpart due to savings on maintenance and fuel.”