Episode summary
Alex Imas on Why Economists Might Be Getting AI Wrong
Odd Lots
· · Hosts: Tracy Alloway, Joe Weisenthal · Guests: Alex Imas
Summary
Alex Imas argues that economists may be underestimating how different AI could be from earlier general-purpose technologies because the speed of adoption matters as much as the eventual destination. He says the key issue is not just whether AI raises productivity, but whether the gains arrive fast enough for workers, firms, and public policy to adapt before large-scale displacement hits. In his view, years matter more than decades if tasks become automatable quickly.
He distinguishes between simple job-exposure measures and a task-based framework. A job may look highly exposed, but if AI only automates a subset of separable tasks, workers can shift toward complementary tasks and become more productive. He also stresses demand elasticity: in some sectors, like software, cheaper output could lead to much more demand and even more hiring, while in others the same productivity gains could mean fewer workers.
Imas says the most vulnerable work is likely where tasks are highly verifiable and automation can run through an entire workflow, such as truck driving and warehouse operations. He also thinks new tasks will emerge, and that AI companies may already have the data needed to study them. But he is skeptical that productivity gains will automatically accrue to workers, and says expanding capital ownership may be a better response than relying on labor to absorb the shock.
Key takeaways
- Imas says the biggest mistake may be focusing on AI’s long-run productivity gains while ignoring how fast those gains can translate into unemployment.
- He argues that job exposure metrics are too crude because a job’s tasks can be highly complementary, so automating one task does not always eliminate the job.
- He sees truck driving and warehouse work as especially exposed because AI can potentially automate both the digital workflow and the surrounding logistics.
- He thinks software engineering could see either more hiring or downsizing, depending on whether demand for code becomes more or less elastic.
- Imas says a plausible policy response is to expand ownership of capital, including something like a universal basic ETF, if labor gets replaced quickly.
Notable quotes
“I think that I feel like a lot of economists and just people in general, I think aren't talking enough about is speed”
“If we're on the order of like years or like 5 or 6 years, we're not going to have time to see that pretty little graph”
“it's the fact that a human job is a bunch of different tasks, right”
“the extent of that complementarity of how these tasks are related depend will determine the extent to which automation is going to affect the labor market”
“If labor is replaced by capital, then what's going to help people is formerly you were a labor in labor now universal basic universal basic ETF”
How the episode opens
How confident are we that productivity gains from AI actually accrue to workers who can then spend some money on whatever product or service is scarce at the moment, or important to them? I would say not that confident. There's several scenarios out there, and I think that I feel like a lot of economists and just people in general, I think aren't talking enough about is speed.
You talk about that if things are fast we need public policy. We need the, the, the new jobs aren't going to come fast enough. Training isn't going to happen fast enough where you're going to get, you know, things are going to get fully automated very quickly and people are going to become unemployed.
There's not going to be enough time in the economy to see that pretty little graph of agriculture shrinking and services increasing. That took a long time. Right.
This is decades. If we're on the order of like years or like 5 or 6 years, we're not going to have time to see that pretty little graph. We are going to need to think about how do we support the people who are becoming unemployed.
And you know, many very smart people have made suggestions on how to do that. I think my personal, I wouldn't say favor, but I think the thing that makes more sense to me is somehow expanding the ownership of capital. If labor is replaced by capital, then what's going to help people is formerly you were a labor in labor now universal basic universal basic ETF.
It is UTC. Hello and welcome to another episode of the Odd Lots podcast, I’m Joe Weisenthal. And I’m Tracy Alloway.
Tracy, it may have changed a little bit in recent weeks or months, but I think by and large, if you talk to economists about the long term impact of AI, particularly on jobs, by and large it seems like they point to history.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai and labor
- job displacement risk
- productivity gains
- ai development speed
- public policy
Companies and tickers mentioned
- META
- Meta
Watch the episode
Watch “Alex Imas on Why Economists Might Be Getting AI Wrong” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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