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Robert Wiblin: Hi listeners, this is the 80,000 Hours Podcast, the show about the world’s most pressing problems and how you can use your career to solve them. I’m Rob Wiblin, Director of Research at 80,000 Hours.

I found today’s episode really fun and expect most subscribers will be interested even if it’s not directly related to their career.

If you find the conversation entertaining or informative, think about forwarding it to someone with a strong view about the value of education so they can enjoy it too.

Just a quick reminder that if you’re in Australia or the Netherlands and want to go to local effective altruism conferences this year, you’ll need to apply to go soon at eaglobal.org.

Here’s Bryan.

Robert Wiblin: Today, I’m speaking with Bryan Caplan. Bryan is a Professor of Economics at George Mason University, and a blogger for EconLog. He’s the author of The Case Against Education: Why The Education System is a Waste of Time and Money, Selfish Reasons to Have More Kids: Why Being a Great Parent is Less Work and More Fun Than You Think, and The Myth of the Rational Voter: Why Democracies Choose Bad Policies.

He’s been published in more newspapers and magazines than I can be bothered to name. He earned his B.A. in Economics from UC Berkeley and got a PhD. in Economics from Princeton. Though, I guess he’s gonna tell us that, that doesn’t matter too much.

Bryan Caplan: Yes and no.

Robert Wiblin: Will Wilkinson described him as playful, ebullient, sportingly-argumentative, and dressed unfashionably for comfort. So, thanks for coming on the podcast, Bryan.

Bryan Caplan: Great to be here again.

Robert Wiblin: So, we planned to talk about the implications of your work for listener’s career plans. And an essay you wrote a while back, about the risk of global totalitarianism. But first, what is the core argument that you’d make in The Case Against Education?

Bryan Caplan: A core argument is that, a lot of the payoff from education comes not from learning useless skills in school, but rather, just from showing off. Convincing employers that you’re worthwhile, basically jumping through hoops, and getting lots of stickers on your forehead. While, selfishly speaking, it really doesn’t make very much difference why exactly your education pays. But, from a social point of view, or from an effective altruism point of view, it matters tremendously, because if you go to school, if you were actually learning how to do new productive things, then your gain is society’s gain. But, if what you’re doing is looking better than other people, then your gain is really, the rest of society’s loss.

Essentially, I just go through the case for why it seems like so much of education is signaling and then try to recalculate. What is the social return to education versus the selfish return, once we have factored in this theory of what the new mechanism is? Well, alternate theory. Not really new.

Robert Wiblin: Right, right. What are the top few pieces of supporting evidence for this signaling theory of education?

Bryan Caplan: Ultimately, I just start with the curriculum and just go back to all the classes you’ve taken and just ask yourself, when do you use this stuff in real life, if ever? There’s just so many courses where almost everyone when they aren’t trying to defend a theory, they are supposed to believe, they just admit, yeah I just studied a ton of stuff, that not only never happened to come up, but was foreseeably ultra unlikely to ever come up. And you know what? It didn’t.

You know? Like, trigonometry. You spend a year studying trigonometry and if you ever dare to raise your hand and say, “When are we gonna use this in real life?”, you’d get a sneer from the teacher. “Oh you’ll see”, and I ask, “Well, have you seen?” How much is real life about trigonometry? Yeah, I guess it’s not at all, for almost anybody. So, we just, looking at the curriculum and just going through it and just seeing how much of the coursework that you’ve done, just very foreseeably, you’re never going to use again in real life. Looking at college majors, also. Just seeing how many of them seemed to be tied to almost no job, other than being a teacher of that very subject. That’s really where I start.

Then, there’s a lot of just observations that people have from their time in school. Things like, it seems like people are much more focused on getting good grades than actually learning anything.

Robert Wiblin: Right.

Bryan Caplan: So, how many times have you deliberately sought out the easy A? The teacher who goes and will give you an A, in exchange for doing no work and learning nothing. Seems like students are very interested in tracking those people down. Very unusual that someone says, “Yeah, I’ll only take him if he teaches a ton of useful material.”

One fun piece of support for this, on the Rate My Professor website, at least in the past they had a rating for easiness, but no rating for job relevance. It seems like, wow, people seem a lot more interested in the easiness than the job relevance. Also, like another primordial fact is that, if you want to get the best education in the world for free, you can. Just say, suppose you think it’s Princeton. Just move to Princeton and start attending classes unofficially. Don’t enroll, don’t pay any money, and just start learning. You’ll see there’s almost no effort made to prevent people from learning, from getting a Princeton education for free.

Unfortunately, just one little thing that you won’t have at the end of four years, and that is of course, grades and diploma. So, it seems like because of this, almost no one bothers to take advantage of this seemingly incredible opportunity. You know just another fact is the way that people forget so much of what they learn in school, and in fact you would often forget so much, you would no longer be able of passing a class you got an A in years ago. And yet employers regard failing and forgetting as two very different things.

If you’re being paid for the skills that you acquired, failing and forgetting are the same. But on the other hand if you’re getting paid for impressing people, then failing and forgetting are very different. Because almost everybody forgets but, if you did well in a class, and then forgot it, that says something about your willingness and ability to learn. So it convinces employers that they should hire you.

Then I also go into four sub-bodies of research. All which I say confirm the signaling model, and we can go into all those if you want.

Robert Wiblin: So, listeners won’t be surprised to hear The Case Against Education is a bit controversial, even among people who study education.

Bryan Caplan: That … I would say especially, actually.

Robert Wiblin: Especially, yeah, right. Well it’s very sacred for them. So if you were right, what would be the main implications for society?

Bryan Caplan: The implication for society is spend less on education. The idea that because education raises individual earnings, that it is a good social investment, is just wrong. If I’m right, that idea that is so prevalent, the idea that you go take a look, and you see more people with better education get better jobs. So if we all get more education, we all get better jobs, right? And the signaling model says, “No, wrong.” This is just a case like standing up at a concert to see better, which works fine for an individual, but is totally counterproductive for society.

So I mean essentially, this means a totally new view on what is a good way to invest taxpayer dollars, right? It’s a totally new theory of economic development. It’s so popular in development to just pour money into education and then modernize. And signaling model says, “No, that’s not a good way to modernize at all.” It’s actually going to burn up a lot of useful tax dollars and time, in what is really a mostly zero sum. So yeah, those are the big implications. I also talk about, the value of vocational education, and how … You know, I mean there’s good evidence that selfishly we actually underrate it. Especially for kids who really do not like school, and are not likely to finish, and are likely to end up in jail, vocational education is a lot better for them, selfishly speaking.

But then from a social point of view, even more important because vocational education and whatever else it does, what it does for private earnings, at least it’s teaching tangible skills, that people go out and use in the real world.

Robert Wiblin: Okay, so you’ve explained … You’ve gone into a lot of detail on the case in the book and various other interviews and a whole lot of articles online. So I’ll stick up a link to one of those. I think that the EconTalk episode is perhaps the best source for people who are really interested in hearing, kind of you describe the evidence at length.

Bryan Caplan: Yeah, yeah.

Robert Wiblin: Because I’ve only got you for so long, I was hoping to sustain a bit more of the time on objections.

Bryan Caplan: Great.

Robert Wiblin: So, in estimating the magnitude of signaling’s effect in education, you rely quite a bit on the sheepskin premium. Do you want to explain what that is for the listeners?

Bryan Caplan: Yeah sure. Alright yeah, so sheepskin effect … In a pure human capital world, that is if the only reason why education raised your earnings was that it raised your skills. Then if you happen to be one class short of graduation, that should have only a very tiny effect upon your earnings. Because there’s only a tiny difference in the amount you know. Whether you have all your classes for a degree, or if your one class short. On the other hand, if part of what you’re doing with your education is signaling, and especially if one of the things your signaling is conformity, that you’re willing to just go along with social expectations. Then there could actually be a discrete jump, where finishing that last class could give you a very big pay off.

So in the book, I go over all the studies that I could find on this, and essentially every single one done in the last 25 years finds that there is a much bigger payoff for graduation from both high school and the bachelor’s degree, than there is for the earlier years. Right. And in the book I go and actually average out all the results, and I find that for high school on average … Again, almost all these are from the U.S., maybe one or two studies from Canada. But almost all the studies find that senior year is worth about as much as the first three years combined. And then, for college … That’s in percentage terms. So it’s even bigger than it seems. And then for college, in percentage terms, it looks like finishing senior year is worth about twice as much as the first three years combined. Which again, is a very large difference.

Robert Wiblin: So that seems like pretty good evidence, on its face, that signaling is a large fraction of what’s going on. And I certainly don’t disagree that signaling is an important function that education provides, but I can’t help but feel there’s something not entirely convincing about that specific number that’s generated by just saying, well the sheepskin effect is signaling, and the rest mostly isn’t, or at least partially isn’t. So it seems like you end up comparing someone who just graduates against someone who drops out just before graduation to estimate this like premium from that final year. From getting the piece of paper. Which is where the term sheepskin comes from. Cause originally diploma were printed on sheepskins–

Bryan Caplan: Yes, yes. Your animal rights people may not be happy, but I have nothing to do with this, not my fault.

Robert Wiblin: Usually not printed on sheep anymore I imagine. Two things that occur to me, won’t the sample of people who drop out just before graduating, be fairly small, making the estimate of incomes of people who dropped out last minute kind of imprecise. And also, isn’t the kind of group that drops out just before the final class, or before final year, kind of an odd group, right? Because they were so close to getting this enormous award, and they decided not to. So possibly they got sick, possibly there were serious problems in their life that prevented them from graduating. Or even if not, I mean at that point they’re signaling that despite the enormous amount of money that they might expect to make by graduating, they decided not to do it. Which suggest perhaps a lack of conscientiousness, or poor judgement on their part.

So perhaps, that’s what employers are looking at when they say, “Well, you did three years, really? And then you stopped? What is wrong with you?”

Bryan Caplan: Right, although, hmm. So I guess there are a few things that are getting packaged together. One thing is that as you might expect, people have tried putting in different controls for ability to see whether it’s just the abler people finish. And out of the studies that do this, usually they find that controlling for ability reduces both the graduation gain and the annual gain. But again, if you think of sheepskin just as basically the ratio of those two, than the ratio seems very stable actually to … The main ability control they actually use is, measures intelligence, although that’s also the main one that actually seems to make difference when you’re doing the estimate.

Meaning you could back away, and say that there’s just some unmeasured thing that we just don’t have any measure for and that would destroy the results. Honestly, for all observational kind of metrics, you can never rule that out. But I think it is fair to say, that look the main thing we know works, doesn’t change the result, at all. You know the idea that this is all artifactual, or even primarily artifactual, seems hard to believe. It seemed like you were actually moving into a specific signaling story which, would actually make sense. Which is that what do employers think of someone who does three years and then gives up? They think, “My god, what’s wrong with you that you would do this?”

Robert Wiblin: Right.

Bryan Caplan: Although I think that, you can just flip it around and they say when someone does graduate, they say “Oh, look at what’s right with this person.” So it seems that in terms of being quantitatively wrong, I don’t see why that comparison is off. It’s just sort of saying, like how much of a difference do people see between the three year and the four year versus in terms, not of what they have of the skills they’ve acquired, but in terms of what kind of person that they are.

Robert Wiblin: So that is still a signaling story, but it’s a signaling story in which the sheepskin effect perhaps exaggerates the impact of graduation relative to learning. Because the group that’s just short of graduating is peculiar in this particular way.

Bryan Caplan: Okay, so the other thing is, usually what I’m actually doing because, most studies don’t actually give you return per year. They don’t say freshman return , sophomore, junior, senior. Usually what they’ll do is give you a sheepskin and they’ll give you annual. So we’re not basing this comparison upon just graduaters versus people who do three years. It’s based upon graduaters versus people who do zero … Zero two or three years.

Robert Wiblin: I see.

Bryan Caplan: Basically you’re lumping the one, two and three year people all together into one category. So again, it’s not nearly as heavy selected… There are a few papers that actually do exactly what you’re talking about. Those actually find that every year is its own return. So every year is special. Senior year is still by far the most special. Then actually, there’s a paper too that finds that freshman year is special, it’s like the second most important year. Basically this, you can think of this as the signal between someone who at least tries to do a year, and someone who doesn’t.

Robert Wiblin: I thought that could be bad. That they go to university for one year and then dropping out would look worse than someone who just tries to do something else, and doesn’t even like try and fail.

Bryan Caplan: At least in modern U.S., I think the stigma against someone who doesn’t even try college is pretty great. So that makes sense to me. In the second year, so-so. In the third year, then, that’s normally found to be worthless. Again I think that is … You’re right, it’s a small number of people, maybe 3% of the population, something like that. But it’s a small number of people that is operating under a very negative stigma, where they do a whole extra year, and then employers are so baffled by this decision to give up, that it seems that third year pays zip.

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80,000 Hours Podcast Transcripts Dataset

Dataset Description

This dataset contains transcripts from the 80,000 Hours Podcast, a show about the world's most pressing problems and how you can use your career to solve them. The podcast features in-depth interviews with experts about their research and work addressing global priorities.

Complete transcripts from 80,000 Hours podcast episodes as of March 11 2025
Individual text files for each episode
Combined file with all transcripts
Metadata including episode titles

Dataset Creation

Source

The transcripts were collected from the 80,000 Hours Podcast website using a Python script with BeautifulSoup for HTML parsing. The collection process respected the website's server resources by implementing:

Appropriate delays between requests
User-agent rotation
Exponential backoff when needed

Methodology

Transcripts were extracted from the HTML content of individual podcast episode pages and cleaned to remove unnecessary formatting and speaker indicators. The collection process preserved the chronological order of episodes and maintained paragraph structure.

Potential Uses

This dataset may be useful for:

Natural Language Processing research
Topic modeling and trend analysis in effective altruism and longtermism
Information retrieval from expert discussions
Training summarization models on long-form interview content
Analyzing discourse around global priorities research

Ethics & Limitations

These transcripts are sourced from publicly available content on the 80,000 Hours website.
The dataset is intended for research and educational purposes.
Users should be aware that the transcripts may contain discussions of complex ethical topics, hypothetical scenarios, and expert opinions on sensitive issues.
The data represents views expressed by podcast guests and hosts, which may not represent consensus views in their respective fields.

Citation & Attribution

If you use this dataset in your research or projects, please cite both this dataset and the original 80,000 Hours Podcast:

@misc{80000_hours_podcast_transcripts,
  title={80,000 Hours Podcast Transcripts Dataset},
  author={Christian Glass},
  year={2025},
  howpublished={\url{https://huggingface.co/datasets/chanfriendly/80000_hours_podcast_transcripts}}
}

And acknowledge the source:

"Transcripts from the 80,000 Hours Podcast (https://80000hours.org/podcast/)"