David Deming

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David Deming

David Deming

@ProfDavidDeming

Danoff Dean of Harvard College @harvard. Isabelle and Scott Black Professor of Political Economy @Kennedy_School. Newsletter - https://t.co/rXOPJD8ct3

Cambridge, MA Katılım Ocak 2017
185 Takip Edilen8.4K Takipçiler
David Deming
David Deming@ProfDavidDeming·
This was fun @DKThomp, thanks for having me!
Derek Thompson@DKThomp

New pod: Something very strange is happening to the labor market for college graduates. Their unemployment is rising much faster than the overall economy—in a way that's unprecedented in the last 40 yrs. And it's not just that. MBA graduates are having a harder and harder time finding work. Law school applications are surging—an ominous sign of labor market weakness, for those who remember 2007. So, what's going on? Harvard economist @ProfDavidDeming and I talk thru the evidence. 1. Maybe we're seeing normal labor-market weakening, in a period of high economic uncertainty. 2. Maybe we're seeing a continuation of the post-2010 flatlining (and mild deterioration) of the college wage premium. 3. Maybe we're seeing white-collar companies pinch pennies by hiring fewer college grads and using Generative AI to make up the difference. open.spotify.com/episode/3Fehyr…

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David Deming
David Deming@ProfDavidDeming·
great article @DKThomp!
Derek Thompson@DKThomp

New essay: Something strange—and possibly worrying—is happening to the job market for college grads: unemployment for recent grads is rising, while law school applications are surging. Maybe it's a sign of Trumpy chaos. Maybe it's a sign of something more structural. So, here's question I'm mildly obsessed with: What economic indicator should we watch closely to know if AI is starting to really change the whole macroeconomy? "When you think from first principles about what generative AI can do, and what jobs it can replace, it’s the kind of things that young college grads have done” in white-collar firms, @ProfDavidDeming told me. “They read and synthesize information and data. They produce reports and presentations.” I agree. I'm not catastrophic about the risk of total disemployment by machines. But I do think Gen-AI is amazing at the precise skillset of paralegals and young i-bankers, consultants, researchers, and coders. So I've been wondering when we'll see recent grad unemployment peel away from the rest of the economy. Well, that's precisely what's happening now. The unemployment rate for recent grads is worse now relative to the overall economy than any time in the last four decades, at least. Is this slam-dunk evidence of AI disruption? As I say in the piece: nope. But it's ... something to watch.

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NBER
NBER@nberpubs·
Leaders who are good at managing artificially intelligent agents are also good at managing humans, from Ben Weidmann, Yixian Xu, and @ProfDavidDeming nber.org/papers/w33662
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Hoover Institution
Hoover Institution@HooverInst·
Who uses generative AI in the workplace? Will the spread of GenAI tools propel a lasting productivity boom in the United States? Harvard University @ProfDavidDeming has some answers that are grounded in data. Watch the latest episode of Economics Applied with host Steven Davis:
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The Atlantic
The Atlantic@TheAtlantic·
The Trump administration’s cuts to university research grants will make America sicker and poorer in the long run, @ProfDavidDeming writes. DOGE should stop "confusing efficiency with ill-conceived budget cuts." theatlantic.com/ideas/archive/…
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The Atlantic
The Atlantic@TheAtlantic·
The Trump administration’s cuts to university research grants will make America sicker and poorer in the long run, @ProfDavidDeming writes. DOGE should stop "confusing efficiency with ill-conceived budget cuts." theatlantic.com/ideas/archive/…
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David Deming
David Deming@ProfDavidDeming·
Slashing science funding is the opposite of efficiency The Trump administration’s cuts to university research grants will make America sicker and poorer in the long run. My latest in The Atlantic (link below):
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Noah Smith 🐇🇺🇸🇺🇦🇹🇼
America is replacing bad jobs with good jobs. From 2016 to 2022, high-skilled jobs soared while low-skill and mid-skill jobs vanished. Overall employment rates went up. Americans are moving from bad jobs to good jobs.
Noah Smith 🐇🇺🇸🇺🇦🇹🇼 tweet media
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David Deming
David Deming@ProfDavidDeming·
@emollick @random_walker “Buried in the paper” = featured on p. 3 of the introduction. Not to mention we explicitly made the calculation to get the facts out there. Grind your axe on someone else, please :)
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Ethan Mollick
Ethan Mollick@emollick·
Not my paper but I don't think this is a fair interpretation of a carefully conducting survey: 1) Your comparison of this being a "glacial pace" of adoption is compared to a baseline from "AI boosters" - who made those predictions? AI has had rapid adoption compared to other technologies by most measures we have, certainly more rapid than most of us studying technology and innovation would expect. There are many other studies finding the same thing, see also Humlum and Vestergaard 2) You seem to be accusing the authors of "burying" information. Hours used is in the introduction! In research on tech adoption going back to Everett, you typically measure who is adopting absolutely, which is what is in the abstract. 3) This is a study of all workers - knowledge workers use AI at a much higher rate, as you might expect, as do students (70% in representative Walton study).
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Arvind Narayanan
Arvind Narayanan@random_walker·
Here's an AI hype case study. The paper "The Rapid Adoption of Generative AI" has been making the rounds based on the claim that 40% of US adults are using generative AI. But that includes even someone who asked ChatGPT to write a limerick or something once in the last month. Buried in the paper is the fact that only 0.5% – 3.5% of work hours involved generative AI assistance, translating to 0.125 – 0.875 percentage point increase in labor productivity. Compared to what AI boosters were predicting after ChatGPT was released, this is a glacial pace of adoption. The paper leaves these important measurements out of the abstract, instead emphasizing much less informative once-a-week / once-a-month numbers. It also has a misleading comparison to the pace of PC adoption (20% of people using the PC 3 years after introduction). If someone spent thousands of dollars on a PC, of course they weren't just using it once a month. If we assume that people spent at least an hour a day using their PCs, generative AI adoption is roughly an order of magnitude slower than PC adoption. static1.squarespace.com/static/60832ec…
Arvind Narayanan tweet media
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