The Economics of Work with Ben Zweig

Epizodes

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  Deena Mousa - What AI Means for the Developing World 19.08.2026 37min

  The standard debate about AI and jobs is a rich-country debate. But for billions of people in low- and middle-income countries, the stakes and the story look completely different.In this episode, Ben sits down with Deena Mousa, program officer at Coefficient Giving and writer on AI and global development, to explore what gets missed when we only think about AI's impact through a Western lens.Topics covered:Why there are still so many radiologists, and what the gap between benchmark performance and real-world clinical performance tells us about AI adoption more broadlyHow automation demand works in reverse: why making scans faster and cheaper expands the complexity of what radiologists are asked to do, not just the volumeWhy low-income countries are in a fundamentally different situation with both their access to AI and how it can address their needs.The service export threat: why the BPO and outsourcing sectors in countries like the Philippines and India may face a more immediate AI disruption than any manufacturing sectorWhy "supply creates its own demand" doesn't automatically work for development, and the Malawi example of why breakout growth is the exception, not the ruleThe difference between low-income and middle-income countries, and why bundling them into "LMICs" obscures the very different things they need to doWhy some Western social progress movements can inadvertently harm the workers they're meant to protectAbout Deena Mousa: Deena Mousa is a program officer at Coefficient Giving, formerly Open Philanthropy, where she focuses on the intersection of AI and global development. She writes on Substack about how transformative technology reshapes economic opportunity across the world.Check out Deena’s substackCheck out Deena on XFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Luis Garicano - Why the Most Valuable Work Is the Hardest to Automate 12.08.2026 50min

  The jobs most protected from AI aren't necessarily the most credentialed ones. They're the ones where tasks are so tightly bundled together that pulling one thread unravels the whole thing.In this episode, Ben sits down with Luis Garicano, LSE professor and author of Messy Jobs, to dig into what makes some work durable, how organizations need to reconfigure around AI, and why Europe may be in serious trouble.Topics covered:Clean vs. messy jobs: why single-task, easily reinforced work is what AI takes firstThe unbundling productivity trade-off: why breaking jobs apart unlocks more growth but also drives wages down as labor supply floods a narrower set of tasksWhy technology without business process reconfiguration produces almost no productivity gainsThe junior professional problem in the current landscapeWhy reduced job mobility might inadvertently push firms back toward German-style on-the-job trainingEurope's stagnation trapAbout Luis Garicano: Luis Garicano is a professor of economics and strategy at the London School of Economics and a former member of the European Parliament. His research focuses on the economics of organizations, technology, and productivity.Check out Luis’s book Messy Jobs here: https://a.co/d/0hvVSmnSCheck out Luis’s substack: https://substack.com/@luisgaricanoFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Ronnie Chatterji - How The Labor Market Looks From Inside Open AI 05.08.2026 44min

  What does it look like to do economics from inside the AI revolution with access to data nobody else has, and questions nobody has figured out how to answer yet?In this episode, Ben sits down with Ronnie Chatterji, chief economist at OpenAI, to pull back the curtain on how economic research gets done at a frontier AI lab.Topics covered:Why the right time horizon for AI economics is a mix of real-time, medium-term, and scenario planningWhy you can't afford to be late to recursive self-improvement even when it feels far awayWhat OpenAI's own labor data is showingThe four-category job framework: which roles are at risk, which will be reorganized, which will expand as prices fall, and which are largely insulatedThe Codex paper: what OpenAI's internal data on agentic coding tool adoption reveals about how long it takes different functions to catch up with one anotherExtensive vs. intensive margin: why 2025 was about getting firms to adopt AI at all, and why 2026 is about measuring how deeply they're using itAI and entrepreneurship: whether the falling cost of starting a business is producing more solo firms, thicker startup markets, or just more noiseWhether AI favors small firms that can now punch above their weight, or large firms with the data, governance, and training capacity to go deeperB2B Signals: what OpenAI's enterprise data set reveals about the gap between power users and median usersThe globalization of AI: which countries are growing fastest in AI usageAbout Ronnie Chatterji: Ronnie Chatterji is the chief economist at OpenAI, where he leads research on AI's impact on jobs, growth, and enterprise. He previously served as chief economist at the U.S. Department of Commerce and as a professor at Duke University's Fuqua School of Business. His research spans entrepreneurship, innovation, and the economics of technology adoption.Check out Ronnie's research at openai.com/signalsFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Bill Easterly - What We Get Wrong About Foreign Aid 30.07.2026 35min

  The story of foreign aid is usually told as a story of insufficient resources. Bill Easterly thinks that misses the point.In this episode, Ben sits down with Bill Easterly, NYU economist and author of four books on development, to dig into why aid so often fails, and why the problem runs deeper than most people are willing to admit.Topics covered:From disappointment to concern: how Easterly's view of foreign aid evolved from "zero effect" to actively harmful, particularly through its support of autocratsThe accountability problem: why aid agencies are accountable to US foreign policy goals rather than to the people they're meant to help, and how that shapes everythingWhy even well-intentioned private philanthropy ends up in the same trapsThe "benevolent autocrat" fallacy: why GDP growth under coercive regimes doesn't constitute developmentWhy development as freedom, not just material income is the right framework, and what historical cases reveal about the limits of GDP-first thinkingThe problem with "we": who gets to be included in that word, what it conceals about power and paternalismCoercion vs. exploitationAbout Bill Easterly: Bill Easterly is a former World Bank economist, professor of economics at NYU and co-director of the Development Research Institute.Check out Bill’s books:The Elusive Quest for GrowthThe White Man’s BurdenThe Tyranny of ExpertsViolent SaviorsFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Isabella Loaiza - Beyond Exposure 23.07.2026 41min

  The dominant framework for measuring AI's impact on jobs may be asking the wrong question entirely.In this episode, Ben sits down with Isabella Loaiza, economist and researcher at MIT, to challenge some of the most widely accepted assumptions in the AI and work debate. From the concept of "exposure" to the narrative of an incoming white-collar bloodbath, Isabella makes the case we're missing a big part of the picture around AI.At the center of the conversation is EPOCH, a framework Isabella developed with her coauthor Roberto to capture the human capabilities that AI is least equipped to replace: Empathy, Presence, Opinion, Creativity, and Hope.Topics covered:Why the "white collar bloodbath" narrative gets AI wrongThe difference between automation and augmentationWhy "exposure" should probably be called "automation potential"The EPOCH framework around AI and its relation to humanityThe burnout problem: why offloading routine tasks to AI may eliminate the cognitive rest that knowledge workers rely on to sustain performanceWhether AI empathy is real empathyDream jobs vs. meaningful jobs: why they're not always the same thingWhy measuring task content across countries matters and what a global labor market taxonomy might actually need to captureFind the paper by Isabella Loaiza and Roberto Rigobon about the EPOCH framework hereFollow Isabella on LinkedInFollow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Jasmine Sun - The Youth's Love/Hate Relationship with AI 16.07.2026 46min

  The backlash against AI among young people appears codependent as they rely on it for more and more, while also being some of its most vocal opponents.In this episode, Ben sits down with Jasmine Sun, writer and journalist covering the AI economy, to explore what youth sentiment toward AI reveals about jobs, inequality, and the world being built around us.Topics covered:Why young people's hostility to AI is rational and what it has to do with affordability, distrust of institutions, and declining faith in upward mobilityHow AI sentiment differs across countriesThe Silicon Valley worldview: why the push for AGI and generality reflects specific beliefs about human limitations and who gets to build the futureThe "permanent underclass" concept: what has to be true for it to happen, why some in AI actually believe it, and why even the moderate version is alarmingToday's teenagers as the first true "AI Generation"About Jasmine Sun: Jasmine Sun is a writer and journalist focused on the economics of AI, work, and inequality. She writes on Substack and has reported extensively on how AI is reshaping early career labor markets, Silicon Valley culture, and the future of economic mobility.Check out Jasmine on Substack and XFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Leah Boustan - What Immigration Tells Us About Economic Opportunity 09.07.2026 37min

  The debate about immigration is usually framed around politics and labor markets. But the deeper story includes mobility. Who gets ahead, how, and why where they start determines so much about where you end up.In this episode, Ben sits down with Leah Boustan, professor at Yale and co-author of Streets of Gold, to dig into what the data on immigration reveals about economic opportunity across generations.Topics covered:Why immigration is an underappreciated driver of global mobilityThe Norway brothers study: why migrants earned double what their brothers who stayed earned, and why it had little to do with changing occupationsWhat immigrants bring back when they return home and how that shapes sending countriesHow firms fit into immigrant assimilationLocation and mobility: why immigrants have historically moved to high-productivity cities, whether that's changing, and what remote work means for this patternThe gap between public sentiment toward immigration and what economists know about its effectsAbout Leah Boustan: Leah Boustan is a professor of economics at Yale University and a research associate at the NBER. She is the co-author, with Ran Abramitzky, of Streets of Gold: America's Untold Story of Immigrant Success, which uses newly digitized historical records to trace the economic trajectories of immigrants and their descendants across generations.Check out Leah's book Streets of GoldFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  John Boudreau - Are Business Leaders Listening to HR Theory? 02.07.2026 46min

  Finance has net present value. Operations has bottleneck theory. What does HR have?In this episode, Ben sits down with John Boudreau, professor emeritus at USC and one of the most influential thinkers in the history of human resource management, to explore a question he has spent 40 years trying to answer: why do leaders who make rigorous, model-driven decisions about financial and operational assets continue to rely on gut instinct when it comes to people?Topics covered:Why leaders who would never make a capital investment without a discounted cash flow model routinely make multi-million dollar talent decisions on instinctThe bottleneck problem: why investing equally in every role is as irrational as improving every stage of a production line simultaneouslyWhy economists were studying tasks long before HR wasWhy AI pilots aren't experiments: the difference between watching what happens and actually measuring itWhat it would take to create generally accepted principles for people decisions, and why codified principles matter more than codified measuresWhy the word "job" may be the single biggest obstacle to clear thinking about the future of workAbout John Boudreau: John Boudreau is Professor Emeritus and Senior Research Scientist at the University of Southern California's Marshall School of Business. He is the author of more than 200 articles and ten books, including Beyond HR, Retooling HR, and Reinventing Jobs, and is widely regarded as one of the founding thinkers of the people analytics movement.Follow John on LinkedInFollow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Dan Hamermesh - Time, Beauty, and What Economics Gets Wrong About Work 25.06.2026 40min

  Keynes predicted we'd be working 15-hour weeks by now. So what went wrong? Does it even matter?In this episode, Ben sits down with Dan Hamermesh, one of the most prolific and wide-ranging labor economists of the past half century, to explore questions the field rarely asks: Why do Americans work more than anyone else in the rich world? What do we actually do with leisure when we get it?Topics covered:Why cutting work hours wouldn't make us poor, and why policy, not technology, might be the only realistic path to changeThe "greedy jobs" debate, and what's driving long hours at the topWhat people do with extra leisure timeThe coordination failure at the heart of overworkAbout Dan Hamermesh: Dan Hamermesh is an economist whose career has spanned more than five decades, with foundational contributions to labor economics, the study of time use, and the economics of beauty and discrimination. He is the author of Beauty Pays and Spending Time, among other books, and has been a professor at the University of Texas at Austin, Barnard, and elsewhere.Check out Dan's books Beauty Pays and Spending TimeFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Rachel Lipson - Bridging Business, Education, and Policy to Build a Better Workforce 18.06.2026 43min

  What does it take to connect the worlds of academia, government, and industry around workforce development? The answer requires someone fluent in all three.In this episode, Ben sits down with Rachel Lipson, researcher at Harvard, fellow at Brookings and the Aspen Institute, and author, to explore what's working (and what isn't) in America's approach to training workers for the jobs of today and tomorrow.Topics covered:Why business, education, and policy need to operate togetherThe CHIPS Act as a workforce policy outlier: how it flipped the government's default from antipoverty lens to competitiveness and innovationWhy demand-side workforce policy is so rare in the U.S.The Tesla and Austin Community College case: how a company-college partnership went from a soft PR commitment to a proven productivity driverWhy subsidizing firm-specific training isn't a corporate giveawayWhat community colleges can offer that on-the-job hiring can'tHow to think about preparing the next generation for jobs that don't exist yetAbout Rachel Lipson: Rachel Lipson is a researcher and policy entrepreneur working across Harvard, Brookings, and the Aspen Institute, with a focus on workforce development, social mobility, and the relationship between education and economic opportunity. She is the author of a forthcoming book examining how employers and training institutions can better work together to build a skilled workforce.Follow Rachel on LinkedInFollow Ben on LinkedInFollow us on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Daniel Rock - What Automation Means for How We Organize Jobs 11.06.2026 42min

  What happens to a job when AI touches it? The answer depends on something most frameworks aren't designed to measure.In this episode, Ben sits down with Daniel Rock, assistant professor at Penn and co-founder of Work Helix, to dig into AI exposure.Topics covered:What "AI exposure" measuresWhy tasks are "assemblages," not atoms, and what that means for how we think about job changeThe task chaining paper: why the sequence in which tasks are automated matters as much as which tasks get automatedWhy the handoff costs of breaking work into steps also have handoff benefits and when human checkpoints create value rather than frictionJobs as equilibrium objects: why there may never be a complete theory of how tasks get bundled into jobs, and what we can learn from the attemptWhat academics can learn from entrepreneurs and vice versaWhy the green shoots of AI's impact on science and medicine point toward something much bigger than productivity gains at workAbout Daniel Rock: Daniel Rock is an assistant professor at the Wharton School of the University of Pennsylvania and co-founder of Work Helix. His research sits at the intersection of economics, organizational behavior, and artificial intelligence, with a focus on how technology changes work and how firms can measure and manage that change.Follow Daniel on LinkedInPapers discussed:Weak Bundle, Strong BundleTask ChainingFollow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Alexis Fink - The Science of Making Work Not Suck 04.06.2026 43min

  Most conversations about the future of work focus on technology. This one focuses on people.In this episode, Ben sits down with Alexis Fink, organizational psychologist and president of SIOP — the Society for Industrial-Organizational Psychology — to explore what over a century of behavioral science actually tells us about how work gets done, why organizations succeed or fail, and what leaders get dangerously wrong about their own people.Alexis brings a perspective that's rarely heard in economics conversations: one grounded not in incentives and market forces, but in how humans actually behave under pressure, in teams, and inside complex organizational systems.Topics covered:What industrial-organizational psychology isWhy meetings are almost always done wrong and what a genuinely good one looks likeWhy AI adoption metrics are measuring the wrong metricsThe elevator analogy: why the real potential of AI isn't doing existing things faster, it's enabling things that were never possible before"Brain fry" and cognitive vigilance, and how pushing people harder with AI tools may produce diminishing, even negative, returnsWhy strategic workforce planning is one of the most underrated practices in business, and why so few companies actually do it wellAbout Alexis Fink: Alexis Fink is an organizational psychologist, people analytics leader, and president of SIOP, the Society for Industrial-Organizational Psychology. She has led people analytics and workforce strategy functions at some of the world's largest tech companies and is one of the leading voices on the intersection of behavioral science, organizational design, and the future of work.Follow Alexis on LinkedInFollow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Nick Bloom - The New Geography of Work 28.05.2026 36min

  Five years after the pandemic reshaped where and how we work, where have we actually landed?In this episode, Ben sits down with Nick Bloom, professor of economics at Stanford and the world's leading researcher on remote and hybrid work. Drawing on surveys of hundreds of thousands of workers across many countries,Nick unpacks what the data actually shows about productivity, innovation, and the future of the office.Topics covered:Where work-from-home rates have settled since the pandemic peakWhy culture, not technology, explains why some countries went back to the office while others didn'tThe "personal trainer effect": why being in the same room still matters for concentration and collaborationWhy forcing people back five days a week drives up attrition by a third and costs firms more than they saveThe U-shaped relationship between age and office preference, and what it means for how companies should design their policiesWhat good management actually looks like, and why so much bad management persists even when better practices are well understoodThe "donut effect": how hybrid work is reshaping cities and suburbsAbout Nick Bloom: Nick Bloom is the William D. Eberle Professor of Economics at Stanford University and co-founder of WFH Research. He is one of the most cited economists in the world on the subjects of management practices, and the future of work, and is the author of the upcoming book The Triple Win.Follow Nick on LinkedIn and on XFollow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  Al Roth - Moral Economics and Repugnant Transactions 21.05.2026 46min

  What makes a transaction repugnant? And why does society allow some controversial markets to flourish while banning others that seem far less harmful?In this episode, Ben sits down with Al Roth, Nobel laureate and professor of economics at Stanford, to explore the hidden moral architecture beneath the markets we take for granted, and the ones we don't allow at all. Drawing on his new book Moral Economics, Al makes the case that good policy can't be built on moral intuition alone.Topics covered:What "repugnant" actually means in relation to transactionsSurrogacy, gene editing, and AI companions: where the line between protection and paternalism blursThe coercion vs. exploitation distinction: is banning a market for poor people's benefit sometimes just denying them an opportunity?How public opinion and legislation divergeWhy labor markets are fundamentally different from commodity marketsHow the internet (and now AI) has flooded job markets with applications and destroyed the information value of applyingWhat the economics job market's "signaling" system can teach LinkedIn, dating apps, and corporate hiring alikeAl Roth is a Professor of Economics at Stanford University and a recipient of the Nobel Memorial Prize in Economic Sciences. He is the author of Who Gets What — and Why and Moral Economics, and is one of the world's leading researchers in market design and matching theory.Follow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  David Autor - How Technology Affects Work 14.05.2026 47min

  In this episode, Ben sits down with David Autor, professor of economics at MIT, to explore how technology transforms work at every level from individual tasks to entire industries.Topics covered:Why transformative technologies require organizational reinvention, not just adoptionThe "expertise framework": how the same automation can be a force multiplier for one worker and a threat to another, depending on where their specialized skills sitOccupational licensing as a double-edged sword: consumer protection vs. a barrier to adaptationWhether AI will complement high-skilled workers, substitute for low-skilled ones, or eventually do both, and what the evidence actually shows so farThe skills that will remain valuableWhy we are dangerously under-invested in helping workers transitionDavid Autor is Ford Professor of Economics at MIT and co-director of the MIT Work of the Future task force. He is among the most cited economists in the world on the topics of labor markets, inequality, and technological change.Follow us on LinkedInFollow Ben on LinkedInSign up for our NewsletterVisit our website for more informationGet in touch with us at info@reveliolabs.com
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  The Economics of Work - Trailer 13.05.2026

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