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 wrong
• The difference between automation and augmentation
• Why "exposure" should probably be called "automation potential"
• The EPOCH framework around AI and its relation to humanity
• The burnout problem: why offloading routine tasks to AI may eliminate the cognitive rest that knowledge workers rely on to sustain performance
• Whether AI empathy is real empathy
• Dream jobs vs. meaningful jobs: why they're not always the same thing
• Why measuring task content across countries matters and what a global labor market taxonomy might actually need to capture

Find the paper by Isabella Loaiza and Roberto Rigobon about the EPOCH framework here

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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 mobility
• How AI sentiment differs across countries
• The Silicon Valley worldview: why the push for AGI and generality reflects specific beliefs about human limitations and who gets to build the future
• The "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 alarming
• Today'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.

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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 mobility
• The Norway brothers study: why migrants earned double what their brothers who stayed earned, and why it had little to do with changing occupations
• What immigrants bring back when they return home and how that shapes sending countries
• How firms fit into immigrant assimilation
• Location and mobility: why immigrants have historically moved to high-productivity cities, whether that's changing, and what remote work means for this pattern
• The gap between public sentiment toward immigration and what economists know about its effects

About 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 Gold

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