Professor @NYUStern; Director @NYUSternCFM; former Obama CEA Senior Economist for tech & innovation; research on AI, robots, entrepreneurship, strategy
NYC
Joined February 2009
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Rob Seamans retweeted
Couldn't be happier to have @BharatKChandar join our growing Economics of Frontier AI team at GovAI! And equally thrilled that he'll be leading the AI Economic Indicators work at @DigEconLab
If you aren't already following the indicators project, check it out here: digitaleconomy.stanford.edu/…
Happy to share I am now Research Director for AI Economics and Policy at @DigEconLab. As part of new role I will be leading the AI Economic Indicators.
I am also now a Research Fellow at @GovAIOrg. I'm excited to work with them on most important questions in econ of AI.
🎄Christmas has come early!🎄
I have an important message for everyone. It is that Christmas has come early this year, and you get subscribe to @jasonfurman 's new Econvitals!
Jason's charts are awesome, as is his insight.
I've signed up, and I hope you do too.
🎁🎁🎁🎁
Rob Seamans retweeted
Some thoughts about academia, AI, and marketing science. This is an invited commentary based on my recent appointment as an ISMS Fellow. 1/3
pubsonline.informs.org/page/…
Rob Seamans retweeted
Delighted to see the engagement by @RonnieChatterji on this new measure to capture "bottleneck pressure" in tasks and jobs. He and researchers including @Alex_M_Richmond, @daveholtz, @sonnytambe are regularly doing some of the coolest and most novel work in the space of AI and organizational economics.
I would really like to start emphasizing here the amazing work done by so many people at The Burning Glass Institute. I'm hesitant to mention names because I worry I will miss someone :) None of this would be possible without their diligence and care. Doing the kind of mapping we employ in the paper is a huge lift and I am amazed to see the care and expertise with which this has been done.
Our paper starts off with a somewhat counterintuitive framing: how can AI raise the value of something it cannot even do?
The answer lies in complementarities! (check out @lugaricano's book on "Messy Jobs" too, as you will find echoes of this theme there as well!)
The same task can have very different pressure depending on tasks that surround it (Figure 1 from the paper attached). And, how bottlenecked a task is rises in proportion to how much the rest of the job is exposed to AI.
There are several advantages that immediately become clear from the detailed mapping we leverage:
(1) First, we can measure bottleneck pressure at the task level and aggregate up to jobs
(2) Second, we find that about 90 percent of labeled matched task mentions lie outside the posting occupation’s own O*NET task list.
This really makes the postings to task mapping a powerful tool to go beyond what could be achieved by just the O*NET catalog.
Even leaving aside the new work and tasks that AI is creating (which is important to study, and we are!), just the occupation-specific catalog itself misses so much of what the jobs have been asking for.
As AI permeates work, I am hopeful that economists and AI researchers will find this measure useful to report alongside exposure measures, as together they can show:
(1) the scope for AI to perform work and
(2) where improving the work it cannot yet do may pay off more as AI capabilities expand.
PS - The paper ranks many tasks as well as all occupations on the O*NET catalog by this "bottleneck pressure" index. Please check it out!
Many measures of AI exposure ask what AI can do.
This paper asks a different question: where could AI make the remaining human work more valuable?
This is an important distinction. The same task can become a bottleneck in one occupation and not another. Looking inside jobs may tell us much more than assigning an exposure score to the occupation as a whole. This is something my team is working on and I love seeing other studies working on it as well.
Rob Seamans retweeted
A good example of why full automation is never just a matter of AI hitting some capability threshold — how do robotaxi companies deal with riders passed out, having medical emergencies, giving birth (!), vomiting, pooping, or just leaving without closing the car door? Some combination of first responders, remote workers, ground staff, and gig workers, apparently! jalopnik.com/2214767/waymo-r…
Rob Seamans retweeted
AI is the most transformative technology of our era.
That opens up an exciting set of Research opportunities.
@professor_ajay, @akorinek and I lay out nine grand challenges for economists in this new essay.
Transformative AI's potential impact demands new approaches to research on work, growth, inequality, and more.
@erikbryn, @professor_ajay, and @akorinek outline nine "grand challenges" in a new piece for @CACMmag.
Read their full agenda here: cacm.acm.org/research/a-rese…
Rob Seamans retweeted
Many measures of AI exposure ask what AI can do.
This paper asks a different question: where could AI make the remaining human work more valuable?
This is an important distinction. The same task can become a bottleneck in one occupation and not another. Looking inside jobs may tell us much more than assigning an exposure score to the occupation as a whole. This is something my team is working on and I love seeing other studies working on it as well.
Very happy to share a new paper, “Technology Bottlenecks: Measuring Where AI Could Raise the Value of Work It Cannot Yet Do.”
AI exposure measures ask about the work AI is capable of doing. We ask instead where the marginal value of work AI cannot yet do may rise as AI speeds up the rest of the job.
To do so, we employ 288 million U.S. job postings mapped line by line to their closest O*NET tasks and GPT-4 feasibility ratings from Eloundou et al. (2024) to construct a measure, “bottleneck pressure,” for each task in each occupation that posts it.
Using a simple task-based framework, we derive this pressure at the task level, showing that for an AI-infeasible task it is the exposure of the occupation that posts it, so the same task can face very different bottleneck pressure in different jobs.
Reporting bottleneck pressure alongside AI exposure shows both the scope for AI to perform work and where improving the work it cannot do may pay off more as capabilities expand.
Rob Seamans retweeted
Thanks so much @robseamans !! Hopefully a measure many in this space would start using alongside (but not instead of) exposure.
This new paper by @soumitrashukla9 looks like a very interesting and useful addition to the literature -->
This new paper by @soumitrashukla9 looks like a very interesting and useful addition to the literature -->
Very happy to share a new paper, “Technology Bottlenecks: Measuring Where AI Could Raise the Value of Work It Cannot Yet Do.”
AI exposure measures ask about the work AI is capable of doing. We ask instead where the marginal value of work AI cannot yet do may rise as AI speeds up the rest of the job.
To do so, we employ 288 million U.S. job postings mapped line by line to their closest O*NET tasks and GPT-4 feasibility ratings from Eloundou et al. (2024) to construct a measure, “bottleneck pressure,” for each task in each occupation that posts it.
Using a simple task-based framework, we derive this pressure at the task level, showing that for an AI-infeasible task it is the exposure of the occupation that posts it, so the same task can face very different bottleneck pressure in different jobs.
Reporting bottleneck pressure alongside AI exposure shows both the scope for AI to perform work and where improving the work it cannot do may pay off more as capabilities expand.
Rob Seamans retweeted
Very happy to share a new paper, “Technology Bottlenecks: Measuring Where AI Could Raise the Value of Work It Cannot Yet Do.”
AI exposure measures ask about the work AI is capable of doing. We ask instead where the marginal value of work AI cannot yet do may rise as AI speeds up the rest of the job.
To do so, we employ 288 million U.S. job postings mapped line by line to their closest O*NET tasks and GPT-4 feasibility ratings from Eloundou et al. (2024) to construct a measure, “bottleneck pressure,” for each task in each occupation that posts it.
Using a simple task-based framework, we derive this pressure at the task level, showing that for an AI-infeasible task it is the exposure of the occupation that posts it, so the same task can face very different bottleneck pressure in different jobs.
Reporting bottleneck pressure alongside AI exposure shows both the scope for AI to perform work and where improving the work it cannot do may pay off more as capabilities expand.
Rob Seamans retweeted
NEWS: 19 FORMER ECONOMIC AND NATIONAL SECURITY LEADERS ENDORSE THE BIPARTISAN PERMITTING REFORM BILL
Today, a group of former Cabinet members and White House principals across seven Democratic and Republican administrations sent a letter calling on Congress to pass BAAJA. Here are the signatories:
Janet YELLEN, Michael R. POMPEO, Steven T. MNUCHIN, Leon E. PANETTA, Timothy F. GEITHNER, Henry M. PAULSON, Jr., Robert E. RUBIN, Stephen MIRAN, Jared BERNSTEIN, Tyler GOODSPEED, Jason FURMAN, Glenn HUBBARD, Laura D’Andrea TYSON, Michael J. BOSKIN, Jeffrey ZIENTS, Jake SULLIVAN, Brian DEESE, Larry KUDLOW, Allan B. HUBBARD
Key highlights from the letter:
1. “We are not building infrastructure fast enough to remain globally competitive… The median time for a new power plant to move from an interconnection request to commercial operation has more than doubled, from less than two years for projects built between 2000 and 2007 to more than four years for projects built between 2018 and 2024.
2. China has built more high-voltage transmission in the last fifteen years than the U.S. has built in all of its history... In 2024, China accounted for 31.5% of global knowledge- and technology-intensive manufacturing value added, compared with 20.7% for the United States.
3. Federally funded or permitted projects require NEPA review, but private projects often do not, creating a threat of failure precisely where the government is trying to be proactive, strategic, and engaged.
4. A project that spends years awaiting approval must continue carrying development and financing costs while remaining exposed to rising input costs. The IEA reports that prices for utility-scale transformers increased 26% in 2024, while lead times for some transformers have stretched as long as six years.
5. Mining projects also face tremendous uncertainty: a 2026 study by researchers at the Colorado School of Mines found that permitting for modern mining projects takes an average of 5.5 years, rising to 8.9 years for contested projects. The U.S. currently has the second-longest mine development timeline in the world.
6. The Bipartisan American Affordability and Jobs Act is the most significant bipartisan legislative effort that Congress has undertaken in decades to tackle these challenges.
7. BAAJA addresses key constraints stifling American industry by requiring interregional transmission planning, strengthening the federal backstop for nationally significant transmission lines, and creating a faster, more predictable process for connecting new generation to the grid.
8. BAAJA also makes permits more durable by imposing tighter timelines for litigation and limiting frivolous lawsuits that can halt projects indefinitely, while preserving community input and judicial review of substantive agency decisions.”
The letter was organized by @arnabdatta321 on behalf of @IFP and covered exclusively by the WSJ this morning.
Rob Seamans retweeted
My new book, Co-Existence, is out today. It is a guide to how to live & work in a world where AI is sometimes, but not always, better than you.
(And, for the release, I worked with Opus 5.5 to make a quite interesting experience for the book's website: co-existence.ai/)
Rob Seamans retweeted
🧵1/10 Given the recent reactions of mathematicians over rapid advances in AI, I think it is important to remember that technological change has historically been a very personal event for people.
Over the history of technological progress, looms have fallen silent, switchboards have gone dark, and factory lines have shrunk bringing with them a human crisis of identity and what it means to be a master of one's craft.
This is an excellent and succinct take on the labor market impact of AI from someone who follows the data and research very closely -->
Not my primary area of expertise, but I get asked enough about the labor market impact of AI that I thought I'd sketch out my views as of October 2026.
I plan to revisit, modify and update this list periodically.
macromostly.substack.com/p/t…
How you know you can trust what @EconBerger writes:
"I strongly recommend against trusting high-confidence predictions about the future of the labor market (including any in this post)."
Rob Seamans retweeted
Not my primary area of expertise, but I get asked enough about the labor market impact of AI that I thought I'd sketch out my views as of October 2026.
I plan to revisit, modify and update this list periodically.
macromostly.substack.com/p/t…
Rob Seamans retweeted
Brent oil hit $110 a barrel for the first time since May bloomberg.com/news/articles/…
