Luis Garicano - Why the Most Valuable Work Is the Hardest to Automate

Luis Garicano - Why the Most Valuable Work Is the Hardest to Automate

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 first
  • The unbundling productivity trade-off: why breaking jobs apart unlocks more growth but also drives wages down as labor supply floods a narrower set of tasks
  • Why technology without business process reconfiguration produces almost no productivity gains
  • The junior professional problem in the current landscape
  • Why reduced job mobility might inadvertently push firms back toward German-style on-the-job training
  • Europe's stagnation trap

About 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/0hvVSmnS

Check out Luis’s substack: https://substack.com/@luisgaricano

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Jaksot(23)

Ernie Tedeschi - What the Productivity Numbers Say About AI

Ernie Tedeschi - What the Productivity Numbers Say About AI

Productivity growth in the US has jumped by about a percentage point since 2023. That's a big deal. Whether AI is the cause, or just the context, is a much harder question to answer than most commenta...

7 Loka 43min

Mike Spence - What a Nobel Laureate Thinks AI Does to Education

Mike Spence - What a Nobel Laureate Thinks AI Does to Education

The theory of labor market signaling changed how economists think about education, hiring, and information. Fifty years later, AI is rewriting the conditions that made the theory work.In this episode,...

30 Syys 1h

Anna Stansbury - Worker Power, Wages, and What's Gone Wrong in the American Labor Market

Anna Stansbury - Worker Power, Wages, and What's Gone Wrong in the American Labor Market

The labor share of income has dropped from roughly two thirds to below sixty percent since the early 1980s. The US looks like an outlier even among rich countries.In this episode, Ben sits down with A...

23 Syys 49min

Paul Osterman - The Disposable Worker: How Firms Learned to Stop Investing in People

Paul Osterman - The Disposable Worker: How Firms Learned to Stop Investing in People

The unspoken employment contract, characterized by stable jobs, career ladders, wages that rose with productivity, didn't dissolve overnight. Firms chipped away at it deliberately, and the result is a...

16 Syys 52min

David Deming - What's Happening to Young Workers, and What College Should Do About It

David Deming - What's Happening to Young Workers, and What College Should Do About It

For the first time in recent history, new college graduates have a higher unemployment rate than the general population. The causes are tangled, the implications are serious, and universities are caug...

9 Syys 48min

Ioana Marinescu - Why Workers Are Underpaid, and What We Could Do About It

Ioana Marinescu - Why Workers Are Underpaid, and What We Could Do About It

Most people earn less than they're worth. Not because they're not productive, but because the labor market isn't nearly as competitive as it could be.In this episode, Ben sits down with Ioana Marinesc...

2 Syys 51min

Roberto Rigobon - Why We're Getting Worse at Measuring

Roberto Rigobon - Why We're Getting Worse at Measuring

The economy is changing faster than our ability to track it. And the data sources we rely on most, like surveys, official statistics, and government indices, were designed for a world that no longer e...

26 Elo 57min

Deena Mousa - What AI Means for the Developing World

Deena Mousa - What AI Means for the Developing World

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 ...

19 Elo 37min

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