The Genius Trap

Tyler Cowen once said over lunch “I don’t know why I don’t agree with everything Greg Mankiw says. He’s much smarter than me.” He was being entirely earnest and it doesn’t seem on it’s face a crazy question. Yes, with a little reflection is easy to observe that smart people are wrong sometimes, but there’s nonetheless a probabilistic logic to it. If someone is smarter than me, I should just adopt all of their ideas which are, on average, more likely to be correct than those I form on my own, therefore increasing my average “correctness” through pure imitation, adoption, and replication. Almost none of us do this, thank the gods of ecological rationality and group selection, thus preserving the wisdom of crowds and the robustness of our collective wisdom, but I think it’s still worth revisiting how intelligence correlates with “correctness.” Specifically, I’m taking this as my opportunity to run a little thought experiment I like to call “The Genius Trap.” I apologize if there is a pre-existing thought experiment associated with someone famous. I haven’t read nearly enough philosophy.

To start, let’s make some gratuitous, outright rude reductions of people. People will be characterized by two attributes: how often they make correct assessments of the information being considered, which we will call “wisdom”, and how complex of an abstract system they can hold in their head while maintaining the consistency and coherence of each individual element, which we will refer to as “intelligence.” Now, it’s easy to observe that some people are wise but not intelligent, or vice versa, but that’s trite. To make things interesting, let’s assume that wisdom and intelligence are positively correlated. Some people will be low in both (“slow”), others will be medium (“average”), and a few blessed folks will be both highly wise and highly intelligent (“geniuses”).

Now typically in a thought experiment we leave everything in the realm of adjectives (high, low, slow, genius, etc), but bear with me here because this experiment benefits from assigning hard numerical paramaters. Let’s say that slow people are correct 85% of the time but can only only a 2 element system in their head. Average people are correct 90% of the time and can consider and evaluate an 32 element system. No need for symmetry here, let’s really go all-in on geniuses, and say they are correct 95% of the time and can hold a 1024 element system in their head. Following so far? Geniuses are carrying around 2^10 element models in their head, each element of which is correct 95% of the time.

You ever play “Mousetrap”?


Rube Goldberg Machines (RGMs) make for useful allegorical references, but why are some funny and others just sweaty metaphors? An RGM is an overly complex device drawn or conceived for comedic effect. They are purposefully absurb in their individual design elements, but what is key is that, if the events proceed as planned the intended result will actually occur. The metaphorical intent is usually that the complexity is unnecessary, but what makes an RGM funny is precisely that it would work if events proceeded as expected. The audience, of course, knows with certainty born of experience that there is absolutely no way this machine will function because anything with high levels of complexity and narrow tolerances for deviation will always fail. Comedic irony comes for us all.

It is in this manner that the opinions, most notably the politics, of really smart people can go so entirely off the rails. Recall our slow individual. Sure, they’re only right 85% of the time, but in a two elemement model of the world that still gets you home intact 72.25%. And for most of daily life, a two element model is more than sufficient to get you through your day hale and hearty. But alas, our poor geniuses, they cannot help themselves. The world is a rich and complex place of which they want to unlock the deepest mysteries. And why not? Point by point their lived experience is confronting all of the exam questions they knew the correct answers to when others were obviously mistaken. The rub, of course, is that being right 95% of the time can’t survive in the face of a 10 element model, for which their understanding remains pure and intact only 59.87% of the time. By the standards of a daily life, they have been reduced to dullards, clumsily shouting their world view at those without the luxury of ignoring them.

It is precisely because they are capable of holding in their heads and considering the ramifications of fantastically complex mental models of the world, each element itself well considered and defended, brilliant people can find themselves with very specific opinions that stand no chance of being remotely correct. The solution, of course, is social. It’s friends and coworkers who challenge you, pointing out your foolishness in fun and good faith. It’s the the academy, going through every line of your proof with a fine toothd comb, sometimes perhaps taking a little too much glee in pointing out your errors (often, in turn, making errors of their own), but the system persists and science proceeds in no small part because of the wisdom of crowds.

Some of the worst political ideas in history have come from geniuses, but as a light consumer of intellectual biography, it’s interesting how often the very worst ideas happen after the world decides someone is a genius, isolating them in a web of fame, worship, self-regard, and, in our modern era, extreme wealth. In many ways, it’s the opposite of herding, where the mechanics of herd safety disables the wisdom of crowds. Less common, do doubt, than herding simply because of the tautologically lesser prevalence of extreme intelligence, but nonetheless important.

Which is a long-winded waying of saying that the trap is not in being a genius, per se, but in being a genius alone. Of becoming surrounded by yes men or moving to an off the grid cabin in the woods. Of building a steel cocoon of your own narcissism, formulating ever more complex models within models, each mistake compounding and eroding your mind like intellectual termites. Avoiding the genius trap is not to limit yourself or the complexity of your thinking, but simply to open yourself to the criticism of others, particularly those invested in neither your brilliance or your censure. To wholly avail yourself of the possibility that the mouse trap might never fall because you are completely and utterly wrong.

Every good is a bundle

I had an interesting dinner with two macroeconomists, Paulo Lins and Michael Navarrette. A follow-up conversation led to me skimming this paper, which dives into the regional heterogeneity of food inflation. Now inflation is not something we typically think of having particularly local or granular heterogeneity (“inflation is everywhere and always a monetary phenomena”, etc, etc), but it’s important to remember that the biggest difference between chalkboard inflation and real-life inflation is measurement.

Economic data is something we often take for granted, in no small part because it’s the substrate from which so much economic research is grown. To fight over it almost feels like nihlism. But just because we aren’t fighting about it doesn’t mean that measurement is easy. It is, in fact, brutally challenging for a host of reasons. Now, a lot of those reasons come down to the demand for immediacy in measurements, which can in turn be dealt with through updates over time. But there’s a deeper challenge that we shouldn’t lose sight of.

Every good is a bundle.

A tomato is a vegetable that is secretly a fruit. Sometimes the price is higher, sometimes it’s lower. But here’s the rub: sometimes when the price is higher it’s secretly lower, and vice versa. Sometimes it’s the same, only it’s not. Sometimes that modestly increased price is secretly a catastrophic increase threatening marinara all across the nation.

Yesterday the tomatoes I bought were 3 for $2. Today they were 2 for $1.50. A modest 11% increase in price. Ah, but see, it isn’t.

The tomatoes today are a little smaller. They came from farther away, representing a seed line that is more tolerate of travel and refrigeration. They are less uniform in color, more acidic, less sweet. Diving deeper, we find that the cost for a 100 lbs of tomatoes purchased in bulk were unchanged. There was, however, less variety to be chosen from because those crates of bulk tomatoes were increasingly curated to fit the needs of Sysco, the chief purveyer for mid to lower tier restaurants, which needs them more for median-customer approved red sauces than spinach salads and bruschetta.

So, dear reader, I ask you – did the price of tomatoes go up? For me, they certainly did. For the median American they barely budged. For Pizza Hut they may have actually gone down!

It’s easy to see how complex goods are bundles of attributes, but it’s amazing how products as commodified as sand or amino acids for livestock feed can quickly become bundles once you put yourself in the shoes of the customers for those goods. When quality, timing, and uniformity enter the mix, damn near every good becomes a rich bundle of attributes for which profit-maximizing suppliers are working diligently to not just meet the needs of their customers, but serve the terms of the explicit and implicit contracts from which any deviation brings the spector of margin-spoiling transaction costs. There’s a lot of gravity at the status quo. Which, in a way, is simple rediscovering menu costs, but with the important distinction that just because the number on the menu hasn’t changed doesn’t mean the price hasn’t. The menu is a lie.

So, yeah, measurement is hard.

Sport rivalries work best when the hate isn’t real

Mexico plays England tonight in the World Cup and I will be rooting for Mexico. Which is interesting considering that Harry Kane is one of my favorite global players to watch and Mexico, for most of my life, as been the primary rival for the US Men’s National Team (who play Monday night against Belgium, another household dilemma since my wife used to run a Belgian restaurant).

I could go on about this, but Ryan Rosenblatt covers it ably. The rivalry was fun so long as it stayed on the pitch. After 12 years of racist political rhetoric about Mexico and Mexicans, it’s no fun to root against them. Combined with the fact that the team plays genuinely enjoyable soccer (relative to the broad standard of international soccer, which I am contractually obligated to note is aesthetically inferior to 95% of club soccer), I would love to see Mexican soccer fans collectively lose their minds advancing deep in the tournament.

There is a broader theme this World Cup of wonder and awe at the sense of camaderie amongt fans from 48 different countries and the communities hosting them. Which is wonderful and the World Cup as an institution deserves a lot of credit (the Cup itself, mind you, not FIFA- they’re as corrupt as they come), but honestly I think this is the result of just a lot of people coordinating to travel at the same time.

The reality is and always has been that most people don’t carry any (or, at least, much) nationalistic hate in their hearts, and certaintly not the ones willing to the incur the discomfort of flying to a different part of the world. The hate isn’t real. It’s mostly a fugazi, a masquerade carried out because it’s materially and politically profitable for a few hundred and the only source of identity and pride for a few thousand. The World Cup, by comparison, is a collective endeavor of a few million, and once you get to those numbers, it’s mostly folk who like having a good time with other folk.

Rural Americans benefit the most from immigration

This is a near-perfect policy experiment showing us, once again, that immigration is not only a net gain for all, but an absolute gain in the rural communities that have become the most politically resistant to immigration.

🗣️ Published today in @aeajournals.bsky.social. Ethan Lewis and I use a visa lottery, as a nationwide randomized experiment, to test the effects of foreign labor on US firms and workers. doi.org/10.1257/app….A concise summary from @nber.org —> http://www.nber.org/digest/20221…

Michael Clemens (@mclem.org) 2026-06-26T16:49:16.587Z

Further summary:

You can learn economics in the most unexpected places.

Economics is everywhere, but I find endless enjoyment in watching others learn about economics in unexpected places. In this case, it’s in the largest Dungeons and Dragons subreddit, where a particularly long-playing and supremely powerful group of adventurers get the bright idea to institute a tax…on magic. What could possibly go wrong?

Well, that is precisely the discussion that emerges. All the things that will and should go wrong if you decide to place a tax on what is essentially the wellspring of all technology and welfare in their world. All healthcare, production, sanitation, agriculture, public safety, etc etc. It all comes back to magic. And these hearty and hale adventurers think it would nice to rake in a few extra million gold pieces by placing, and presumably enforcing, a tax on it.

What’s fascinating is to walk through the comments and watch the crowd collectively puzzle out all the ways this is going to backfire, only to then march through ways the world is going to collectively respond and eventually rebel. There’s a reason why most tax discussions eventually become, at the very least, targeted and, at their very best, highly nuanced. Because it is no small decision how a society should best leverage taxation as a means to solve a problem. Do we want to tax the rich? Ok, what’s the line at rich? Do we want to eliminate regressive taxes targeting the poor? Ok, but is this only a tax or is it doing something else as well?

In this world of magic and mayhem, we see our heroic players stumble into literally the worst possible thing you could ever tax: the entire body of technology. Not labor, not capital, not income, not capital gains…no, they target the single most important input into all of economic growth and human welfare. From a pedagogical point of view, this is <chef kisses fingers> perfection. Absolutely no notes. I’m not kidding when I say that, if I was still teaching Principles of Economics, I would build a class discussion around this exact thread.

And special shout out the commenter to worked through the economic, political, and ecumenical consequences in real time:

It’s economics all the way down, apparently even into the depths of The Nine Hells.

The joy is in the noise

The Knicks won the NBA championship and the Canes won the Stanley Cup. The World Cup is here, with all of its grim authoritarian appeasement and absolutely incredible drama. It all serves as a reminder that so much of the joy is in the noise, the inability to forecast, both as individuals and collectively in the market, what will happen. Make no mistake, the hockey playoffs are grossly unfair as a measure of who exactly is the best hockey team (that was the Colorado Avalanche who were unceremonially swept in the conference finals). Pucks bounce, refs make mistakes, goalies get hot. Any knockout tournmanent is outrageously unfair to identify the best soccer/football team. Dominating teams losing 1-0 on a fluke goal is sufficiently frequent as to be commonly referred to as “getting footballed”.

And that, to be exceptionally clear, is the point. Sports remain an opportunity to watch something that is not only unscripted, but highly difficult to forecast with any sense of certainty. Upsets are joyful not just because they are unexpected, but because they happen just often enought that you don’t feel a fool hoping and cheering for one.

With all of the growing concern over sports gambling and prediction sites, I do wonder what people are more upset about. The self-debasement of individuals eroding their financial security in pursuit of a not-so-cheap high? Or the threat to unpredictability as the incentives of actors inside and outside the games being rearranged to undermine what is supposed to be a random number generator with a multi-agent human engine purposed towards creation of drama unpolluted by audience service and manipulation.

Because here’s the thing. People want to get hurt. They want the disappointmen of losing. Of failing. Or coming up just short. Of giving it away when victory was all but assured. They want that so that when things finally do work out they can wholly and earnestly give themselves away to celebration of something that really actually happened as a product of forces we cannot control. Movies, televisions, books, they all want to give you happy endings so you’ll come back. If they don’t they know what someone else will.

But sports? Sports cannot be bullied by the customer into any such contract because any competition there always and forever has to be a loser. And as a sports fan you will lose. Sometimes a lot. Sometimes for your entire life. But you keep coming back because the noise in the system says that you might win next time. You might get a lucky bounce. A hot goalie. Or a generationally great guard so grotesquely undervalued by another team that for the cost of having the 46th highest salary in the league, you get to have an NBA finals MVP lead you to your first championship in 53 years.

The joy is in the noise. Congrats to any and all Knick fans, especially my Aunt Jean, a dyed in the wool New Yorker who’s been waiting a long time for this.

A thought on the SpaceX IPO

The SpaceX IPO is set for June 12th, with an anticipated market cap after day one between $1.5 and $2.5 trillion. Most of that valuation is based on the prospect of dominating the market for satellites, putting data centers in space, and the endless demand for computing power from AI. It is essentially an AI-related market power play.

I have no speculative insight into the value of SpaceX stock as an investment, but I am an inveterate, unrepentant consumer of irony. An IPO is a speculative investment, but it’s also the act of becoming a publicly held company. A large part of being a public company is getting the accounting right. Modern accounting has all kinds of informational value, but from the point of view of large companies it’s mostly about minimimizing taxes while maximizing perceived value. Both of those ambitions include strong incentives for malfeasance, which is why we have audits, financial regulation, and the IRS. The IRS and financial regulation have been defanged, however, mostly due to a lack of personnel from aggressive destaffing, at least some of which you can lay at the feet of DOGE. You can’t audit a massive company effectively without accountants.

Or can you?

I can’t think of a technical task that is more perfectly suited to AI than auditing a public company’s accounts and SEC filings. You feed AI a billion previous filings, all of the associated laws and regulations, and then flag all the records previously found in violation. Then you feed it new ones and say “show me the violations and discrepancies in rank order of dollar value.” A hundred good accountants using a dedicated AI, that’s exactly the kind of story that leads to the order of magnitude increase in labor output that the biggest proponents of AI are looking for.

Never forget that the event that initially popped the dotcom bubble was Microstrategy getting caught cooking the books.

I know you can’t write history like a novel, but “IRS, previously destaffed by Musk-headed DOGE, is forced to use AI enabled audits and finds massive revenue discrepancies, leading to panicked sell-off of Musk-headed IPO record holding company and kicking off AI stock sell-off”…that’s too easy, right?

Tall poppies don’t get the calls

Ask anyone who grew up playing basketball as the tallest player on the court and they will, each and every one of them, tell you that players were allowed to foul them harder and more often. If you were tall you didn’t get the calls, full stop. Why? We could sort through a host of mechanisms, but they all boil down to “Being tall is an unfair advantage. It’s only fair that I, the shorter opposing player, am allow to slap you, chop you, kick you, trip you, grab you.” To be honest, I don’t think this is a particularly shocking phenomenon. “Tall poppies get cut down” is a cultural cliche for a reason. What is interesting is that it persists even amidst billions of dollars in market incentives pushing in the other direction.

The latest version is happening right now as the Oklahoma City Thunder are currently doing their best to end Victor Wembanyama’s nascent career each and every night, and the referees seem uninterested in realigning the incentives otherwise. At the moment the Spurs are currently up 65-43 in game 4 of the series. If the series goes 7, there’s at least a 20% change Wembanyama doesn’t make it to the end. Will they break his foot smashing down on it, break his leg tripping him, or dislocate his shoulder yanking down on it from a leveraged position? Don’t know, but they’re doing their best to make it happen.

Caitlin Clark came into the WNBA as the single greatest talent prospect in the history of women’s basketball. The abuse she suffers is well documented. Wayne Gretzky was the greatest hockey player of all time, but he was arguably only allowed to reach his potential because Bobby Orr’s careers was cut in half by a league that allowed teams to abuse him with little to know punishment. Bobby Orr’s sin was that he was such a better skater than everyone else that, if allowed to play without constant grabbing, hooking, and abuse tantamount to aggravated assault, he would have walked away with too many goals, wins, and Stanley Cups. It wasn’t fair that he was so much better, so they let the players even the odds. Having watched him limp away after only 7.5 seasons, the NHL took the unofficial position that Gretzky’s teammates (specifically, Dave Semenko and Marty McSorley) held carte blanche to assault anyone who touched Gretzkey. While perhaps not a culture-shifting solution, Gretzky did have a 20 year career that brought hockey to new heights of popularity, so it was ostensibly effective.

But none of that gets at the underlying economics. Elite players bring big audiences to sporting events, which in turn, brings in big money for everyone. The owners, players, and everyone in between gets richer when elite players shine under the biggest lights. So why chop them down? Well, first we have a collective action problem to solve, because, yes, the entire market benefits from superstars, but their opposition during the course of play in any one game have the individual incentives to do whatever they can get away with to win. That’s why we have referees, commissioners, and a players union: to solve those collective action problems. All of those rules and institutions are in place specifically to align incentives and bargain for outcomes that maximize welfare. So why aren’t they working?

When you find cliches at the front of your mind, decent chance you’re running up against psychology and behavioral economics. And as Victor Wembanyama is learning each and every night of the playoffs, “tall poppies get cut down”. It’s not fair that he’s the first 7’5″ player with elite NBA level skills to ever play the game. You know, I was never a fan of watching Shaq play basketball per se, but I always knew he should have scored at least 40 points every night. Yes, he committed 7 offensive fouls every game, but he also received 25 fouls that went uncalled. Players were allowed to maul him because it was unfair he was so much bigger, stronger, and more athletic. His career was only as long as it was because his body could endure the abuse. There has never been another player in NBA history who could have survived even 3 seasons receiving the abuse he did.

Putting aside simple behavioral explanations, we also should consider the possibility that NBA team owners and players are so far down the diminishing marginal returns to wealth, that the median participant would actually prefer to earn less money in order to maximize their own chance at winning a championship. They want parity, of a sort. Parity, but only once the playoffs arrive. The regular season is too long and everyone does, in fact, want to make money, so the abuse is minimal, but once the playoffs arrive, the collective preference is for parity delivered via weaker rule enforcement. There are only so many elite players, but everyone is capable of low-level violence. This preference for postseason parity may also explain why Oklahoma City’s best player, Shai Gilgeous-Alexander, has the reputation for simulating being fouled on every play. If you’re going to get fouled no matter what, you might was well maximize the probability of getting a foul call by forcing the referee to be observed observing the incident.

And, to be clear, parity may in fact be revenue maximizing. Just look at the NFL – the entire structure is designed to maximize the number of franchises who believe at the beginning of the season that their team has a chance to win it all. The players are relatively anonymous compared to NBA superstars, but fans are mostly there to root for laundry, and in the NFL, so long as that laundry doesn’t say NY Jets on it, there’s at least a glimmer of hope. Counter point, just look at the NFL. They understood that each team, especially once the playoffs started, had strong incentives to try to end the opposing quarterbacks career on each and every play. So the NFL introduced a battery of rules to protect quarterbacks, and it seems to have worked.

So maybe I’ve come full circle. Maybe this is what the NBA wants. But I really, really it’s hope not. Wemby is special. I’d like to see the very most of what he can become.

Economic history as it’s happening is alway relative

This is the chart that I’ve been thinking about today.

The US government has been able to borrow on the cheap for most of it’s existence, with the exception of 70s and 80s when stagflation put the clamp down. Treasury rates are soaring right now…or at least, it feels that way because for most of my adult life the United States has been viewed as arguably the safest borrower in history. What follows are in some ways the only two questions that matter for the US economy. Is the US government a reliable institution? Is economic growth going to keep pace with inflation? The answer to each question (and their subcomponents) is, of course, unknown, but the market seems to think the net of that question is going in the wrong direction.

That said, for all of the neverending parade of (sometimes unintential) nostalgia that seems to pollute the discourse, wow, 1975-1985 was not exactly macroeconomically “aspirational”.

Will AI kill the research paper?

Will AI kill the research paper?. I don’t know, probably not. But I do know that what has constituted a research paper has changed many times before and will change many times again.

Before the the 1940’s, economics research papers were largely prose. Analytic in nature, sure, but prose. Some graphs, maybe a box. A little math, but math largely for the sake of demonstrating logical relationships. Then Samuelson hit, reframed economics as thermodynamics and differential calculus. What was previously a research paper was was now a polemic, a monograph at best. Thought experiments were out, high theory was in.

This era of high theory flourished in the 70s, the math changed, and at some point computers arrived with the possibility of data sufficiently rich and numerous you couldn’t just plot all of the observations in Figure 1. That data couldn’t stand on its own, though. To be a credible publication you really needed to bundle your analysis with some theory that generated testable predictions. Pure theory papers gave way to an era of applied imperialism as economic models found themselves applied to every quantified context under the social scientific sun.

Causal identification became a thing of interest, and we got really good at telling stories again. Specifically, stories about instrumental variables. You needed a story to convince anyone, but we told so many that some folks started to notice that these stories were often pretty weak. That, in part, turned up the heat on a credibility revolution that was already in swing, which meant now you needed even better data and you needed to defend you identification strategy to the death. What was a paper before was now an embarassment you should probably consider retracting (nb: no one retracted anything, but that doesn’t mean people were suggesting it behind their backs).

Which kept rolling in data set after data set until we woke up one day and realized you either need to go out in the world and create your own actual experiment (nothing quasi- about it) or you needed to cultivate access to better…no, better…no, the very best-est, most detailed and granular administrative data ever, preferably a universe if possible. Data so perfect as to allow for contributions unassailable in their legitimacy. Do you have friends at the Danish Census? If you want tenure you should probably start flirting with someone at the Danish Census.

So a paper was a paper. Until it wasn’t a paper anymore. Until that wasn’t a paper anymore. Until that wasn’t a paper. The Recursive Dundee Theory of Research*, if you will. They all met the criteria of a contribution, until they didn’t.

So what does this mean for AI and research papers now? Well, if we look to thermodynamics in the 40s and cheap computing power in the 90’s for analogues, then I’d say it’s going to reshape the criteria for a contribution in no small part because it lowers the cost of mediocrity. Mediocre analysis will no doubt persist, but it will shift over into blog posts and journals no one ackowledges as legitimate. Do remember, please, that mediocrity is a relative concept. The quality of blog posts and publications in scam journals will likely massively improve as what can be accomplished in an afternoon’s work is radically increased. Don’t worry, I have no intention of improving beyond my current warm bath of blogging unremarkableness, but others will likely cave in to the pressure.

What about the papers in top journals, though? The papers Tyler is presumably talking about. Will AI kill those economic research papers? Probably not, but it will likely improve it significantly. Why? For the same reason that Michael Kremer says that technology and quality of life improve with the size of the human population. More people means more ideas, and there is nothing more important to economic growth than the sheer number of ideas. And no, I do not mean ideas generated by AI’s. I mean the raw number of researchers with the capacity to make major contributions is increasing dramatically because we’re all getting research assistants. We’re all getting copy editors. We’re all getting support. That’s how AI is going to change the research paper: by giving more ideas the support they need to reach the light of publication. The bar is going to get higher for the same reason that the level of sports improve as you widen the geography they pull from. There’s someone at a directional state school who didn’t get the placement they deserved out of grad school. Sure they have to teach a 3-3 load, but they’re licking their chops right now because they don’t need an army of grad assistants. Summer is here and they’ve got everything they need to make a contribution.

Or I don’t know. Maybe AI will do all of our thinking in 50 years. Forecasting technology beyond 5 years is like forecasting weather beyond 5 days: I can’t do it and neither can you.**

*Apologies to Justin Wolfers and all my Aussie friends for a bit of cultural appropriation. I promise to put some Vegemite on toast while enjoying a flat white and explaining Aussie Rules Football to a friend within 90 days.

**Except for Neal Stephenson. That guy’s the Warren Buffet of Sci Fi forecasting. Maybe he’s the one in a billion person actually experiencing one in a billion level luck, but that doesn’t make it any less impressive.