AI Personality Extraction from Faces: Labor Market Implications
Human capital—encompassing cognitive skills and personality traits—is critical for labor market success, yet the personality component remains difficult to measure at scale. Leveraging advances in artificial intelligence and comprehensive LinkedIn microdata, we extract the Big 5 personality traits from facial images of 96,000 MBA graduates, and demonstrate that this novel “Photo Big 5” predicts school rank, compensation, job seniority, industry choice, job transitions, and career advancement. Using administrative records from top-tier MBA programs, we find that the Photo Big 5 exhibits only modest correlations with cognitive measures like GPA and standardized test scores, yet offers comparable incremental predictive power for labor outcomes. Unlike traditional survey-based personality measures, the Photo Big 5 is readily accessible and potentially less susceptible to manipulation, making it suitable for wide adoption in academic research and hiring processes. However, its use in labor market screening raises ethical concerns regarding statistical discrimination and individual autonomy.
That is from a new paper by Marius Guenzel, Shimon Kogan, Marina Niessner, and Kelly Shue. I read through the paper and was impressed. Of course since this is machine learning, I can’t tell you what the five traits are in any simple descriptive sense. But this is somewhat of a comeback for physiognomy, which even DeepSeek tells me is a pseudoscience. Via tekl, a fine-looking fellow if there ever was one.
Ukrainian bond data correction
In the previous post, I cited data showing that Ukrainian bond prices had fallen over the last few months. But it seems that data source was faulty, and the value of Ukrainian bonds has been rising, including recently. You can find some sources here. Apologies for the error!
I thank JoshB. for drawing this to my attention. He writes in the comments on that previous post: “Ukrainian local debt is not widely traded but according to bloomberg data it has done nothing but rally over the last four months. The UKRGB 19.7 8/25 that the linked website claims to be quoting is trading 99.13 dollar price, up from 90 in the fall. The USD external bonds are much more widely traded and they have definitely rallied over the past few months – it has been a popular hedge fund trade. The UKRAIN 1.75 2/29 for example are now $73 up from $61 pre election. The thesis has been that the Ukraine external debt stock is small relative to reconstruction needs and the country will desire market access so it makes sense to favorably restructure the external bond holders. I’m skeptical personally, but the premise of the original post that Ukraine debt is going down in price is wrong.”
Ukraine bond yields
Right now in the neighborhood of 46%. Right before the election they were roughly at 34%. That is for the one-year bond.
Addendum: This post is based on some apparently faulty data, here is a correction.
Friday assorted links
How the System Works
Charles Mann is worried that so few of us have any notion of the giant, interconnected systems that keep us alive and thriving. His new series, How the System Works at the The New Atlantis, is a primer to civilization. As you might expect from Mann, it’s beautifully written with arresting facts and images:
The great European cathedrals were built over generations by thousands of people and sustained entire communities. Similarly, the electric grid, the public-water supply, the food-distribution network, and the public-health system took the collective labor of thousands of people over many decades. They are the cathedrals of our secular era. They are high among the great accomplishments of our civilization. But they don’t inspire bestselling novels or blockbuster films. No poets celebrate the sewage treatment plants that prevent them from dying of dysentery. Like almost everyone else, they rarely note the existence of the systems around them, let alone understand how they work.
…Water, food, energy, public health — these embody a gloriously egalitarian and democratic vision of our society. Americans may fight over red and blue, but everyone benefits in the same way from the electric grid. Water troubles and food contamination are afflictions for rich and poor alike. These systems are powerful reminders of our common purpose as a society — a source of inspiration when one seems badly needed.
Every American stands at the end of a continuing, decades-long effort to build and maintain the systems that support our lives. Schools should be, but are not, teaching students why it is imperative to join this effort. Imagine a course devoted to how our country functions at its most basic level. I am a journalist who has been lucky enough to have learned something about the extraordinary mechanisms we have built since Jefferson’s day. In this series of four articles, I want to share some of the highlights of that imaginary course, which I have taken to calling “How the System Works.”
We begin with our species’ greatest need and biggest system — food.
and here’s one telling fact from the first essay:
Today more than 1 percent of the world’s industrial energy is devoted to making ammonia fertilizer. “That 1 percent,” the futurist Ramez Naam says, “roughly doubles the amount of food the world can grow.”
Addendum: Tom Meadowcroft from the comments: I teach chemical engineers, who are expert at understanding, designing and managing processes, and will be running many of these civilizational processes after they graduate. Even amongst that group of very bright thinkers, there is remarkably little knowledge as to how we achieve clean water, reliable electricity, fuel for transport and industry, dispose of sewage, and grow and distribute food. These same young adults can all tell you about colonial mindsets, how the world is going to burn, and how various groups are victimized. Our K-12 education system has very warped priorities and remarkably ignorant people at the front of the classroom.
Passive listeners on Spotify
I have been reading the new Liz Pelly book Mood Machine: The Rise of Spotify and the Costs of the Perfect Playlist. It is a very intelligent and well done book, though it is more pessimistic than I am about the future of music.
One central lesson of the book is just how many “passive” music listeners there are. In an earlier era they might have been content with muzak, even on the car radio (my father used to do that). But with Spotify, and many other related internet music services, the passive listeners can be very readily identified. They do not mind being fed AI-produced slop, or payola-driven songs in their feeds. For instance, some song producers, often serving up musical slop, will accept lower royalty rates in return for algorithmic promotion. The passive listeners accept this arrangement without complaint — maybe they just want background mood, or maybe they are not listening at all, and do not want the music to be too intrusive.
Obviously Spotify, or whichever service one has in mind, can track your behavior in this regard. Passive listeners can expect a stream of very low quality in the future, meaning quality as I would define it, not as they would.
Is it bad if so many listeners are passive? Well, it is not my ideal of the ideal philosophic republic.
Still, given that they exist I like the idea of setting them aside, segregated into their own easily-manipulated club. After all, they don’t seem to care about Chuck Berry and Brian Eno. Insofar as we succeed in segregating them, I would think many of the remaining algorithms become better and more in tune with what their users want. After all, the noise from the passive listeners has been removed from the calculations.
So I think of algorithms as a way of rewarding the good guys, and avoiding some of the pooling equilibria. What you call musical “slop,” I call the separating equilibrium.
How to teach people how to work with AI
I have a very concrete and specific proposal for teaching people how to work with AI. It is also a proposal for how to reform higher education.
Given them some topics to investigate, and have them run a variety of questions, exercises, programming, paper-writing tasks — whatever — through the second or third-best model, or some combination of slightly lesser models.
Have the students grade and correct the outputs of those models. The key is to figure out where the AIs are going wrong.
Then have the best model grade the grading of the students. The professor occasionally may be asked to contribute here as well, depending on how good the models are in absolute terms.
In essence, the students are learning how to grade and correct AI models.
Just keep on doing this.
Of course the students need to learn subject matter as well, but perhaps this process should be what…one-third of all higher education?
You might think the models are too good for human grading and correction to matter at all, whether now or in the future. That may be true at some point. That is the same scenario, however, where it does not matter what we teach the students. Might as well teach them for the world-states in which they are of some use at all.
This is all apart from the PhD you might get in gardening, but even there I think you will need to spend some time learning how to correct and judge AI models.
Income inequality in the Nordics
Our analysis suggests that income equality in the Nordics is primarily driven by a significant compression of hourly wages, reducing the returns to labor market skills and education. This appears to be achieved through a wage bargaining system characterized by strong coordination both within and across industries. This finding contrasts with other commonly cited explanations for Nordic income equality, such as redistribution through the tax-transfer system, public spending on goods that complement employment, and public policies aimed at equalizing skills and human capital distribution.
That is from a new NBER working paper by Magne Mogstad, Kjell G. Salvanes, and Gaute Torsvik.
Thursday assorted links
Steel Tariffs in Two Pictures
Recall Principle 2 of Three Simple Principles of Trade Policy, Businesses are Consumers Too. Case in point, steel. Justin Wolfers summarizes an analysis of Trump’s 2018 steel tariffs:
Going back further we have a good analysis from Lydia Cox of the Bush steel tariffs. Even though the tariffs were temporary, they led to a rearrangement of supply chains which led to long-lasting declines in exports and employment in steel using industries.
Place Effects on Fertility Decision: Evidence from Mover Design
This paper investigates the causal impact of place-based factors on fertility decision using mover design and data from the Panel Study of Income Dynamics (1968-2019). We find that moving to a state with a 1 percentage point higher birth rate increases the probability of childbirth by 0.9 percentage points, with cumulative effects reaching 3.8 percentage points three years post-move. The response demonstrates concentration among first births and exhibits systematic variation across demographic characteristics—with particularly pronounced effects observed among white women who are married, younger, and have higher income levels. Our variance decomposition shows the contribution of place effects to fertility variance increased from 4.7 percent to 26.0 percent before and after the Great Recession, with geographical variation in contraceptive access and healthcare infrastructure showing the strongest correlations with these place effects. This research emphasizes the importance of considering contextual factors in fertility research and policy interventions.
That is from a new paper by Hantao Wu and Man Zhu. Via the excellent Kevin Lewis.
Will stablecoins herald a broader-based dollarization?
That is the topic of my latest Bloomberg column. Here is one excerpt:
Stablecoins are programmable crypto assets that promise conversion into some currency, typically US dollars. Currently, they are the fastest-growing sector of crypto. Stablecoin usage is up 84% since August 2023 and is now at a peak of $224 billion. The sympathetic stance of President Donald Trump’s administration toward crypto is likely to help growth further.
It is noteworthy that, measured by market capitalization, perhaps as much as 99% of stablecoins are denominated in dollars. That is a much higher share than is found in standard international trade and finance. This shows that, if monetary institutions were started all over again from scratch — which is part of what crypto is doing — the market would opt largely for dollars.
Traders in many less well governed countries want to partake in dollar-based economies, but they do not always have ready access to dollar-based banking in the way that Americans do. Their domestic banking systems may be unreliable or be regulated to discourage dollar dominance. Traders may also be afraid of US regulations, which operate through sanctions and restrictions on dollar-denominated transactions. “Know your customer” regulations, for example, can make interacting with US financial institutions very costly.
So foreigners are increasingly turning to stablecoins, which they can access quickly and directly through apps. Stablecoins are not much regulated now, but eventually regulation will emerge in many countries. That said, there will likely be more and less regulated versions of stablecoins for a long time to come. For that reason, another advantage of stablecoins — at least for individual traders, if not always for broader society — is that traders will be able to choose the level of regulation they desire.
Several countries have dollarized in recent years — including Panama, Ecuador and El Salvador — and none seems to regret it. President Javier Milei in Argentina has pledged dollarization, and that proved to be a popular campaign promise, although it remains to be seen if he can summon the resources to pull it off.
The simplest scenario is that people outside developed nations use stablecoins more and more. Their economies will become partly “dollarized” — or if you wish to use an even less elegant term, “stablecoinized,” with the stablecoins backed by dollars. People in those economies will get more used to thinking and calculating in terms of dollars, even for their domestic transactions. Dual-currency economies may become more common, with both a domestic currency and dollar-backed stablecoins. Over time, fearing the redemption risks associated with stablecoins, many nations will opt for outright dollarization, either full or partial. In some cases, the dollar might end up predominating.
Worth a ponder, and this is yet another scenario where crypto proves useful.
Wednesday assorted links
Why it is hard for the Executive to disobey the judiciary
An excellent thread from Dilan Esper. Excerpt:
I have pointed out already that Elon Musk has massive economic interests in cases currently before the federal courts. That is reason enough he would have to obey an order or resign if Trump demanded he not do so. A federal court could default him on those suits.
But more generally federal courts can issue writs that can be levied on bank accounts and properties. These could effectively freeze the assets of ANY noncompliant government official. Yes, even the President. And no, President Trump couldn’t order then unfrozen.
There is more at the link. Retweeted by Alex T.
The danger of Trump disobeying court orders
Ilya Somin covers this question over at Volokh Conspiracy. I receive many queries about this, some of them panicky and anguished. I haven’t covered it, mostly because I don’t feel I have enough insights into the relevant matters of constitutional law, or for that matter what is going on inside the administration (for instance, how should one interpret those Vance tweets?)
I can tell you what I would find useful. If you are especially pessimistic on this front, which are the securities prices that would indicate an actual constitutional problem? Particular equities? Interest rates? The value of the dollar? Measures of volatility? Something else? Don’t restrict yourself to the absolute level of share prices, surely there are favored and disfavored companies and sectors, right?
I am allergic to the view that “fascism could come and market prices would not even budge.” In fact, I think it is extremely skeptical and subversive of democracy, or shall I better say a constitutional republic. I think fascism, or a constitutional collapse, would be a terrible outcome in a variety of very practical ways, in addition to its moral failings. At the very least it would matter for many particular enterprises.
In a variety of other contexts, such as tariffs, market prices have been super-sensitive to the actions of the Trump administration. So people, on this question, which exactly are the measurable, market price indicators? After all, you don’t want to be like those doomster AI skeptics who think no one can trade on the (supposed) truth.
In the comments section, I am not interested in your blah blah blah opinion full of adjectives. Just tell me which prices please. I do see this issue as constituting a real risk, if perhaps a sometimes exaggerated one. So I will follow those market prices with great interest. I just need to know what they are.
Addendum: In an excellent Substack today Matt Yglesias notes: “Republicans, meanwhile, are making very little forward progress on their legislative agenda.”