text:
# Love in a time of quarantine

Feb 14JDN 2459260

This is our first Valentine’s Day of quarantine—and hopefully our last. With Biden now already taking action and the vaccine rollout proceeding more or less on schedule, there is good reason to think that this pandemic will be behind us by the end of this year.

Yet for now we remain isolated from one another, attempting to substitute superficial digital interactions for the authentic comforts of real face-to-face contact. And anyone who is single, or forced to live away from their loved ones, during quarantine is surely having an especially hard time right now.

I have been quite fortunate in this regard: My fiancé and I have lived together for several years, and during this long period of isolation we’ve at least had each other—if basically no one else.

But even I have felt a strong difference, considerably stronger than I expected it would be: Despite many of my interactions already being conducted via the Internet, needing to do so with all interactions feels deeply constraining. Nearly all of my work can be done remotely—but not quite all, and even what can be done remotely doesn’t always work as well remotely. I am moderately introverted, and I still feel substantially deprived; I can only imagine how awful it must be for the strongly extraverted.

As awkward as face-to-face interactions can be, and as much as I hate making phone calls, somehow Zoom video calls are even worse than either. Being unable to visit someone’s house for dinner and games, or go out to dinner and actually sit inside a restaurant, leaves a surprisingly large emotional void. Nothing in particular feels radically different, but the sum of so many small differences adds up to a rather large one. I think I felt it the most when we were forced to cancel our usual travel back to Michigan over the holiday season.

Make no mistake: Social interaction is not simply something humans enjoy, or are good at. Social interaction is a human need. We need social interaction in much the same way that we need food or sleep. The United Nations considers solitary confinement for more than two weeks to be torture. Long periods in solitary confinement are strongly correlated with suicide—so in that sense, isolation can kill you. Think about the incredibly poor quality of social interactions that goes on in most prisons: Endless conflict, abuse, racism, frequent violence—and then consider that the one thing that inmates find most frightening is to be deprived of that social contact. This is not unlike being fed nothing but stale bread and water, and then suddenly having even that taken away from you.

Even less extreme forms of social isolation—like most of us are feeling right now—have as detrimental an effect on health as smoking or alcoholism, and considerably worse than obesity. Long-term social isolation increases overall mortality risk by more than one-fourth. Robust social interaction is critical for long-term health, both physically and mentally.

This does not mean that the quarantines were a bad idea—on the contrary, we should have enforced them more aggressively, so as to contain the pandemic faster and ultimately need less time in quarantine. Timing is critical here: Successfully containing the pandemic early is much easier than trying to bring it back under control once it has already spread. When the pandemic began, lockdown might have been able to stop the spread. At this point, vaccines are really our only hope of containment.

But it does mean that if you feel terrible lately, there is a very good reason for this, and you are not alone. Due to forces much larger than any of us can control, forces that even the world’s most powerful governments are struggling to contain, you are currently being deprived of a basic human need.

And especially if you are on your own this Valentine’s Day, remember that there are people who love you, even if they can’t be there with you right now.

# A new chapter in my life, hopefully

Jan 17 JDN 2459232

My birthday is coming up soon, and each year around this time I try to step back and reflect on how the previous year has gone and what I can expect from the next one.

Needless to say, 2020 was not a great year for me. The pandemic and its consequences made this quite a bad year for almost everyone. Months of isolation and fear have made us all stressed and miserable, and even with the vaccines coming out the end is still all too far away. Honestly I think I was luckier than most: My work could be almost entirely done remotely, and my income is a fixed stipend, so financially I faced no hardship at all. But isolation still wreaks its toll.

Most of my energy this past year has been spent on the job market. I applied to over 70 different job postings, and from that I received 6 interviews, all but one of which I’ve already finished. Then, if they liked how I did in those interviews, I will be invited to another phase, which in normal times would be a flyout where candidates visit the campus; but due to COVID it’s all being done remotely now. And then, finally, I may actually get some job offers. Statistically I think I will probably get some kind of offer at this point, but I can’t be sure—and that uncertainty is quite nerve-wracking. I may get a job and move somewhere new, or I may not and have to stay here for another year and try again. Both outcomes are still quite probable, and I really can’t plan on either one.

If I do actually get a job, this will open a new chapter in my life—and perhaps I will finally be able to settle down with a permanent career, buy a house, start a family. One downside of graduate school I hadn’t really anticipated is how it delays adulthood: You don’t really feel like you are a proper adult, because you are still in the role of a student for several additional years. I am all too ready to be done with being a student. I feel as though I’ve spent all my life preparing to do things instead of actually doing them, and I am now so very tired of preparing.

I don’t even know for sure what I want to do—I feel disillusioned with academia, I haven’t been able to snare any opportunities in government or nonprofits, and I need more financial security than I could get if I leapt headlong into full-time writing. But I am quite certain that I want to actually do something, and no longer simply be trained and prepared (and continually evaluated on that training and preparation).

I’m even reluctant to do a postdoc, because that also likely means packing up and moving again in a few year (though I would prefer it to remaining here another year).

I have to keep reminding myself that all of this is temporary: The pandemic will eventually be quelled by vaccines, and quarantine procedures will end, and life for most of us will return to normal. Even if I don’t get a job I like this year, I probably will next year; and then I can finally tie off my education with a bow and move on. Even if the first job isn’t permanent, eventually one will be, and at last I’ll be able to settle into a stable adult life.

Much of this has already dragged on longer than I thought it would. Not the job market, which has gone more or less as expected. (More accurately, my level of optimism has jumped up and down like a roller coaster, and on average what I thought would happen has been something like what actually happened so far.) But the pandemic certainly has; the early attempts at lockdown were ineffective, the virus kept spreading worse and worse, and now there are more COVID cases in the US than ever before. Southern California in particular has been hit especially hard, and hospitals here are now overwhelmed just as we feared they might be.

Even the removal of Trump has been far more arduous than I expected. First there was the slow counting of ballots because so many people had (wisely) voted absentee. Then there were the frivolous challenges to the counts—and yes, I mean frivolous in a legal sense, as 61 out of 62 lawsuits were thrown out immediately and the 1 that made it through was a minor technical issue.

And then there was an event so extreme I can barely even fathom that it actually happened: An armed mob stormed the Capitol building, forced Congress to evacuate, and made it inside with minimal resistance from the police. The stark difference in how the police reacted to this attempted insurrection and how they have responded to the Black Lives Matter protests underscores the message of Black Lives Matter better than they ever could have by themselves.

In one sense it feels like so much has happened: We have borne witness to historic events in real-time. But in another sense it feels like so little has happened: Staying home all the time under lockdown has meant that days are alway much the same, and each day blends into the next. I feel somehow unhinged frrom time, at once marveling that a year has passed already, and marveling that so much happened in only a year.

I should soon hear back from these job interviews and have a better idea what the next chapter of my life will be. But I know for sure that I’ll be relieved once this one is over.

# I dislike overstatement

Jan 10 JDN 2459225

I was originally planning on titling this post “I hate overstatement”, but I thought that might be itself an overstatement; then I considered leaning into the irony with something like “Overstatement is the worst thing ever”. But no, I think my point best comes across if I exemplify it, rather than present it ironically.

It’s a familiar formula: “[Widespread belief] is wrong! [Extreme alternative view] is true! [Obvious exception]. [Further qualifications]. [Revised, nuanced view that is only slightly different from the widespread belief].”

Here are some examples of the formula (these are not direct quotes but paraphrases of their general views). Note that these are all people I basically agree with, and yet I still find their overstatement annoying:

Bernie Sanders: “Capitalism is wrong! Socialism is better! Well, not authoritarian socialism like the Soviet Union. And some industries clearly function better when privatized. Scandinavian social democracy seems to be the best system.”

Richard Dawkins: “Religion is a delusion! Only atheists are rational! Well, some atheists are also pretty irrational. And most religious people are rational about most things most of the time, and don’t let their religious beliefs interfere too greatly with their overall behavior. Really, what I mean to say that is that God doesn’t exist and organized religion is often harmful.”

Black Lives Matter: “Abolish the police! All cops are bastards! Well, we obviously still need some kind of law enforcement system for dealing with major crimes; we can’t just let serial killers go free. In fact, while there are deep-seated flaws in police culture, we could solve a lot of the most serious problems with a few simple reforms like changing the rules of engagement.”

Sam Harris is particularly fond of this formula, so here is a direct quote that follows the pattern precisely:

“The link between belief and behavior raises the stakes considerably. Some propositions are so dangerous that it may even be ethical to kill people for believing them. This may seem an extraordinary claim, but it merely enunciates an ordinary fact about the world in which we live. Certain beliefs place their adherents beyond the reach of every peaceful means of persuasion, while inspiring them to commit acts of extraordinary violence against others. There is, in fact, no talking to some people. If they cannot be captured, and they often cannot, otherwise tolerant people may be justified in killing them in self-defense. This is what the United States attempted in Afghanistan, and it is what we and other Western powers are bound to attempt, at an even greater cost to ourselves and to innocents abroad, elsewhere in the Muslim world. We will continue to spill blood in what is, at bottom, a war of ideas.”

Somehow in a single paragraph he started with the assertion “It is permissible to punish thoughtcrime with death” and managed to qualify it down to “The Afghanistan War was largely justified”. This is literally the difference between a proposition fundamentally antithetical to everything America stands for, and an utterly uncontroversial statement most Americans agree with. Harris often complains that people misrepresent his views, and to some extent this is true, but honestly I think he does this on purpose because he knows that controversy sells. There’s taking things out of context—and then there’s intentionally writing in a style that will maximize opportunities to take you out of context.

I think the idea behind overstating your case is that you can then “compromise” toward your actual view, and thereby seem more reasonable.

If there is some variable X that we want to know the true value of, and I currently believe that it is some value x1 while you believe that it is some larger value x2, and I ask you what you think, you may not want to tell me x2. Intead you might want to give some number even larger than x2 that you choose to try to make me adjust all the way into adopting your new belief.

For instance, suppose I think the probability of your view being right is p and the probability of my view being right is 1-p. But you think that the probability of your view being right is q > p and the probability of my view being right is 1-q < 1-p.

I tell you that my view is x1. Then I ask you what your view is. What answer should you give?

Well, you can expect that I’ll revise my belief to a new value px + (1-p)x1, where x is whatever answer you give me. The belief you want me to hold is qx2 + (1-q)x1. So your optimal choice is as follows:

qx2 + (1-q)x1 = px + (1-p)x1

x = x1 + q/p(x2-x1)

Since q > p, q/p > 1 and the x you report to me will be larger than your true value x2. You will overstate your case to try to get me to adjust my beliefs more. (Interestingly, if you were less confident in your own beliefs, you’d report a smaller difference. But this seems like a rare case.)

In a simple negotiation over dividing some resource (e.g. over a raise or a price), this is quite reasonable. When you’re a buyer and I’m a seller, our intentions are obvious enough: I want to sell high and you want to buy low. Indeed, the Nash Equilibrium of this game seems to be that we both make extreme offers then compromise on a reasonable offer, all the while knowing that this is exactly what we’re doing.

But when it comes to beliefs about the world, things aren’t quite so simple.

In particular, we have reasons for our beliefs. (Or at least, we’re supposed to!) And evidence isn’t linear. Even when propositions can be placed on a one-dimensional continuum in this way (and quite frankly we shoehorn far too many complex issues onto a simple “left/right” continuum!), evidence that X = x isn’t partial evidence that X = 2x. A strong argument that the speed of light is 3*108 m/s isn’t a weak argument that the speed of light is 3*109 m/s. A compelling reason to think that taxes should be over 30% isn’t even a slight reason to think that taxes should be over 90%.

To return to my specific examples: Seeing that Norway is a very prosperous country doesn’t give us reasons to like the Soviet Union. Recognizing that religion is empirically false doesn’t justify calling all religious people delusional. Reforming the police is obviously necessary, and diverting funds to other social services is surely a worthwhile goal; but law enforcement is necessary and cannot simply be abolished. And defending against the real threat of Islamist terrorism in no way requires us to institute the death penalty for thoughtcrime.

I don’t know how most people response to overstatement. Maybe it really does cause them to over-adjust their beliefs. Hyperbole is a very common rhetorical tactic, and for all I know perhaps it is effective on many people.

But personally, here is my reaction: At the very start, you stated something implausible. That has reduced your overall credibility.

If I continue reading and you then deal with various exceptions and qualifications, resulting in a more reasonable view, I do give you some credit for that; but now I am faced with a dilemma: Either (1) you were misrepresenting your view initially, or (2) you are engaging in a motte-and-bailey doctrine, trying to get me to believe the strong statement while you can only defend the weak statement. Either way I feel like you are being dishonest and manipulative. I trust you less. I am less interested in hearing whatever else you have to say. I am in fact less likely to adopt your nuanced view than I would have been if you’d simply presented it in the first place.

And that’s assuming I have the opportunity to hear your full nuanced version. If all I hear is the sound-byte overstatement, I will come away with an inaccurate assessment of your beliefs. I will have been presented with an implausible claim and evidence that doesn’t support that claim. I will reject your view out of hand, without ever actually knowing what your view truly was.

Furthermore, I know that many others who are listening are not as thoughtful as I am about seeking out detailed context, so even if I know the nuanced version I know—and I think you know—that some people are going to only hear the extreme version.

Maybe what it really comes down to is a moral question: Is this a good-faith discussion where we are trying to reach the truth together? Or is this a psychological manipulation to try to get me to believe what you believe? Am I a fellow rational agent seeking knowledge with you? Or am I a behavior machine that you want to control by pushing the right buttons?

I won’t say that overstatement is always wrong—because that would be an overstatement. But please, make an effort to avoid it whenever you can.

# Signaling and the Curse of Knowledge

Jan 3 JDN 2459218

I received several books for Christmas this year, and the one I was most excited to read first was The Sense of Style by Steven Pinker. Pinker is exactly the right person to write such a book: He is both a brilliant linguist and cognitive scientist and also an eloquent and highly successful writer. There are two other books on writing that I rate at the same tier: On Writing by Stephen King, and The Art of Fiction by John Gardner. Don’t bother with style manuals from people who only write style manuals; if you want to learn how to write, learn from people who are actually successful at writing.

Indeed, I knew I’d love The Sense of Style as soon as I read its preface, containing some truly hilarious takedowns of Strunk & White. And honestly Strunk & White are among the best standard style manuals; they at least actually manage to offer some useful advice while also being stuffy, pedantic, and often outright inaccurate. Most style manuals only do the second part.

One of Pinker’s central focuses in The Sense of Style is on The Curse of Knowledge, an all-too-common bias in which knowing things makes us unable to appreciate the fact that other people don’t already know it. I think I succumbed to this failing most greatly in my first book, Special Relativity from the Ground Up, in which my concept of “the ground” was above most people’s ceilings. I was trying to write for high school physics students, and I think the book ended up mostly being read by college physics professors.

The problem is surely a real one: After years of gaining expertise in a subject, we are all liable to forget the difficulty of reaching our current summit and automatically deploy concepts and jargon that only a small group of experts actually understand. But I think Pinker underestimates the difficulty of escaping this problem, because it’s not just a cognitive bias that we all suffer from time to time. It’s also something that our society strongly incentivizes.

Pinker seems to briefly touch this insight (p. 69), without fully appreciating its significance: “Even when we have an inlkling that we are speaking in a specialized lingo, we may be reluctant to slip back into plain speech. It could betray to our peers the awful truth that we are still greenhorns, tenderfoots, newbies. And if our readers do know the lingo, we might be insulting their intelligence while spelling it out. We would rather run the risk of confusing them while at least appearing to be soophisticated than take a chance at belaboring the obvious while striking them as naive or condescending.”

What we are dealing with here is a signaling problem. The fact that one can write better once one is well-established is the phenomenon of countersignaling, where one who has already established their status stops investing in signaling.

Here’s a simple model for you. Suppose each person has a level of knowledge x, which they are trying to demonstrate. They know their own level of knowledge, but nobody else does.

Suppose that when we observe someone’s knowledge, we get two pieces of information: We have an imperfect observation of their true knowledge which is x+e, the real value of x plus some amount of error e. Nobody knows exactly what the error is. To keep the model as simple as possible I’ll assume that e is drawn from a uniform distribution between -1 and 1.

Finally, assume that we are trying to select people above a certain threshold: Perhaps we are publishing in a journal, or hiring candidates for a job. Let’s call that threshold z. If x < z-1, then since e can never be larger than 1, we will immediately observe that they are below the threshold and reject them. If x > z+1, then since e can never be smaller than -1, we will immediately observe that they are above the threshold and accept them.

But when z-1 < x < z+1, we may think they are above the threshold when they actually are not (if e is positive), or think they are not above the threshold when they actually are (if e is negative).

So then let’s say that they can invest in signaling by putting some amount of visible work in y (like citing obscure papers or using complex jargon). This additional work may be costly and provide no real value in itself, but it can still be useful so long as one simple condition is met: It’s easier to do if your true knowledge x is high.

In fact, for this very simple model, let’s say that you are strictly limited by the constraint that y <= x. You can’t show off what you don’t know.

If your true value x > z, then you should choose y = x. Then, upon observing your signal, we know immediately that you must be above the threshold.

But if your true value x < z, then you should choose y = 0, because there’s no point in signaling that you were almost at the threshold. You’ll still get rejected.

Yet remember before that only those with z-1 < x < z+1 actually need to bother signaling at all. Those with x > z+1 can actually countersignal, by also choosing y = 0. Since you already have tenure, nobody doubts that you belong in the club.

This means we’ll end up with three groups: Those with x < z, who don’t signal and don’t get accepted; those with z < x < z+1, who signal and get accepted; and those with x > z+1, who don’t signal but get accepted. Then life will be hardest for those who are just above the threshold, who have to spend enormous effort signaling in order to get accepted—and that sure does sound like grad school.

You can make the model more sophisticated if you like: Perhaps the error isn’t uniformly distributed, but some other distribution with wider support (like a normal distribution, or a logistic distribution); perhaps the signalling isn’t perfect, but itself has some error; and so on. With such additions, you can get a result where the least-qualified still signal a little bit so they get some chance, and the most-qualified still signal a little bit to avoid a small risk of being rejected. But it’s a fairly general phenomenon that those closest to the threshold will be the ones who have to spend the most effort in signaling.

This reveals a disturbing overlap between the Curse of Knowledge and Impostor Syndrome: We write in impenetrable obfuscationist jargon because we are trying to conceal our own insecurity about our knowledge and our status in the profession. We’d rather you not know what we’re talking about than have you realize that we don’t know what we’re talking about.

For the truth is, we don’t know what we’re talking about. And neither do you, and neither does anyone else. This is the agonizing truth of research that nearly everyone doing research knows, but one must be either very brave, very foolish, or very well-established to admit out loud: It is in the nature of doing research on the frontier of human knowledge that there is always far more that we don’t understand about our subject than that we do understand.

I would like to be more open about that. I would like to write papers saying things like “I have no idea why it turned out this way; it doesn’t make sense to me; I can’t explain it.” But to say that the profession disincentivizes speaking this way would be a grave understatement. It’s more accurate to say that the profession punishes speaking this way to the full extent of its power. You’re supposed to have a theory, and it’s supposed to work. If it doesn’t actually work, well, maybe you can massage the numbers until it seems to, or maybe you can retroactively change the theory into something that does work. Or maybe you can just not publish that paper and write a different one.

Here is a graph of one million published z-scores in academic journals:

It looks like a bell curve, except that almost all the values between -2 and 2 are mysteriously missing.

If we were actually publishing all the good science that gets done, it would in fact be a very nice bell curve. All those missing values are papers that never got published, or results that were excluded from papers, or statistical analyses that were massaged, in order to get a p-value less than the magical threshold for publication of 0.05. (For the statistically uninitiated, a z-score less than -2 or greater than +2 generally corresponds to a p-value less than 0.05, so these are effectively the same constraint.)

I have literally never read a single paper published in an academic journal in the last 50 years that said in plain language, “I have no idea what’s going on here.” And yet I have read many papers—probably most of them, in fact—where that would have been an appropriate thing to say. It’s actually quite a rare paper, at least in the social sciences, that actually has a theory good enough to really precisely fit the data and not require any special pleading or retroactive changes. (Often the bar for a theory’s success is lowered to “the effect is usually in the right direction”.) Typically results from behavioral experiments are bizarre and baffling, because people are a little screwy. It’s just that nobody is willing to stake their career on being that honest about the depth of our ignorance.

This is a deep shame, for the greatest advances in human knowledge have almost always come from people recognizing the depth of their ignorance. Paradigms never shift until people recognize that the one they are using is defective.

This is why it’s so hard to beat the Curse of Knowledge: You need to signal that you know what you’re talking about, and the truth is you probably don’t, because nobody does. So you need to sound like you know what you’re talking about in order to get people to listen to you. You may be doing nothing more than educated guesses based on extremely limited data, but that’s actually the best anyone can do; those other people saying they have it all figured out are either doing the same thing, or they’re doing something even less reliable than that. So you’d better sound like you have it all figured out, and that’s a lot more convincing when you “utilize a murian model” than when you “use rats and mice”.

Perhaps we can at least push a little bit toward plainer language. It helps to be addressing a broader audience: it is both blessing and curse that whatever I put on this blog is what you will read, without any gatekeepers in my path. I can use plainer language here if I so choose, because no one can stop me. But of course there’s a signaling risk here as well: The Internet is a public place, and potential employers can read this as well, and perhaps decide they don’t like me speaking so plainly about the deep flaws in the academic system. Maybe I’d be better off keeping my mouth shut, at least for awhile. I’ve never been very good at keeping my mouth shut.

Once we get established in the system, perhaps we can switch to countersignaling, though even this doesn’t always happen. I think there are two reasons this can fail: First, you can almost always try to climb higher. Once you have tenure, aim for an endowed chair. Once you have that, try to win a Nobel. Second, once you’ve spent years of your life learning to write in a particular stilted, obscurantist, jargon-ridden way, it can be very difficult to change that habit. People have been rewarding you all your life for writing in ways that make your work unreadable; why would you want to take the risk of suddenly making it readable?

I don’t have a simple solution to this problem, because it is so deeply embedded. It’s not something that one person or even a small number of people can really fix. Ultimately we will need to, as a society, start actually rewarding people for speaking plainly about what they don’t know. Admitting that you have no clue will need to be seen as a sign of wisdom and honesty rather than a sign of foolishness and ignorance. And perhaps even that won’t be enough: Because the fact will still remain that knowing what you know that other people don’t know is a very difficult thing to do.

# 2020 is almost over

Dec27 JDN 2459211

I don’t think there are many people who would say that 2020 was their favorite year. Even if everything else had gone right, the 1.7 million deaths from the COVID pandemic would already make this a very bad year.

As if that weren’t bad enough, shutdowns in response to the pandemic, resulting unemployment, and inadequate fiscal policy responses have in a single year thrown nearly 150 million people back into extreme poverty. Unemployment in the US this year spiked to nearly 15%, its highest level since World War 2. Things haven’t been this bad for the US economy since the Great Depression.

And this Christmas season certainly felt quite different, with most of us unable to safely travel and forced to interact with our families only via video calls. New Year’s this year won’t feel like a celebration of a successful year so much as relief that we finally made it through.

Many of us have lost loved ones. Fortunately none of my immediate friends and family have died of COVID, but I can now count half a dozen acquaintances, friends-of-friends or distant relatives who are no longer with us. And I’ve been relatively lucky overall; both I and my partner work in jobs that are easy to do remotely, so our lives haven’t had to change all that much.

Yet 2020 is nearly over, and already there are signs that things really will get better in 2021. There are many good reasons for hope.

There are now multiple vaccines for COVID that have been successfully fast-tracked, and they are proving to be remarkably effective. Current forecasts suggest that we’ll have most of the US population vaccinated by the end of next summer.

Maybe the success of this vaccine will finally convince some of the folks who have been doubting the safety and effectiveness of vaccines in general. (Or maybe not; it’s too soon to tell.)

Perhaps the greatest reason to be hopeful about the future is the fact that 2020 is a sharp deviation from the long-term trend toward a better world. That 150 million people thrown back into extreme poverty needs to be compared against the over 1 billion people who have been lifted out of extreme poverty in just the last 30 years.

Those 1.7 million deaths need to be compared against the fact that global life expectancy has increased from 45 to 73 since 1950. The world population is 7.8 billion people. The global death rate has fallen from over 20 deaths per 1000 people per year to only 7.6 deaths per 1000 people per year. Multiplied over 7.8 billion people, that’s nearly 100 million lives saved every single year by advances in medicine and overall economic development. Indeed, if we were to sustain our current death rate indefinitely, our life expectancy would rise to over 130. There are various reasons to think that probably won’t happen, mostly related to age demographics, but in fact there are medical breakthroughs we might make that would make it possible. Even according to current forecasts, world life expectancy is expected to exceed 80 years by the end of the 21st century.

There have also been some significant environmental milestones this year: Global carbon emissions fell an astonishing 7% in 2020, though much of that was from reduced economic activity in response to the pandemic. (If we could sustain that, we’d cut global emissions in half each decade!) But many other milestones were the product of hard work, not silver linings of a global disaster: Whales returned to the Hudson river, Sweden officially terminated their last coal power plant, and the Great Barrier Reef is showing signs of recovery.

Yes, it’s been a bad year for most of us—most of the world, in fact. But there are many reasons to think that next year will be much better.

# Hyper-competition

Dec13 JDN 2459197

This phenomenon has been particularly salient for me the last few months, but I think it’s a common experience for most people in my generation: Getting a job takes an awful lot of work.

Over the past six months, I’ve applied to over 70 different positions and so far gone through 4 interviews (2 by video, 2 by phone). I’ve done about 10 hours of test work. That so far has gotten me no offers, though I have yet to hear from 50 employers. Ahead of me I probably have about another 10 interviews, then perhaps 4 of what would have been flyouts and in-person presentations but instead will be “comprehensive interviews” and presentations conducted online, likely several more hours of test work, and then finally, maybe, if I’m lucky, I’ll get a good offer or two. If I’m unlucky, I won’t, and I’ll have to stick around for another year and do all this over again next year.

Aside from the limitations imposed by the pandemic, this is basically standard practice for PhD graduates. And this is only the most extreme end of a continuum of intensive job search efforts, for which even applying to be a cashier at Target requires a formal application, references, and a personality test.

This wasn’t how things used to be. Just a couple of generations ago, low-wage employers would more or less hire you on the spot, with perhaps a resume or a cursory interview. More prestigious employers would almost always require a CV with references and an interview, but it more or less stopped there. I discussed in an earlier post how much of the difference actually seems to come from our chronic labor surplus.

Is all of this extra effort worthwhile? Are we actually fitting people to better jobs this way? Even if the matches are better, are they enough better to justify all this effort?

It is a commonly-held notion among economists that competition in markets is good, that it increases efficiency and improves outcomes. I think that this is often, perhaps usually, the case. But the labor market has become so intensely competitive, particularly for high-paying positions, that the costs of this competitive effort likely outweigh the benefits.

How could this happen? Shouldn’t the free market correct for such an imbalance? Not necessarily. Here is a simple formal model of how this sort of intensive competition can result in significant waste.

Note that this post is about a formal mathematical model, so it’s going to use a lot of algebra. If you are uninterested in such things, you can read the next two paragraphs and then skip to the conclusions at the end.

The overall argument is straightforward: If candidates are similar in skill level, a complicated application process can make sense from a firm’s perspective, but be harmful from society’s perspective, due to the great cost to the applicants. This can happen because the difficult application process imposes an externality on the workers who don’t get the job.

All right, here is where the algebra begins.

I’ve included each equation as both formatted text and LaTeX.

Consider a competition between two applicants, X and Z.

They are each asked to complete a series of tasks in an application process. The amount of effort X puts into the application is x, and the amount of effort Z puts into the application is z. Let’s say each additional bit of effort has a fixed cost, normalized to 1.

Let’s say that their skills are similar, but not identical; this seems quite realistic. X has skill level hx, and Z has skill level hz.

Getting hired has a payoff for each worker of V. This includes all the expected benefits of the salary, benefits, and working conditions. I’ll assume that these are essentially the same for both workers, which also seems realistic.

The benefit to the employer is proportional to the worker’s skill, so letting h be the skill level of the actually hired worker, the benefit of hiring that worker is hY. The reason they are requiring this application process is precisely because they want to get the worker with the highest h. Let’s say that this application process has a cost to implement, c.

Who will get hired? Well, presumably whoever does better on the application. The skill level will amplify the quality of their output, let’s say proportionally to the effort they put in; so X’s expected quality will be hxx and Z’s expected output will be hzz.

Let’s also say there’s a certain amount of error in the process; maybe the more-qualified candidate will sleep badly the day of the interview, or make a glaring and embarrassing typo on their CV. And quite likely the quality of application output isn’t perfectly correlated with the quality of actual output once hired. To capture all this, let’s say that having more skill and putting in more effort only increases your probability of getting the job, rather than actually guaranteeing it.

In particular, let’s say that the probability of X getting hired is P[X] = hxx/(hxx + hzz).

$P[X] = \frac{h_x}{h_x x + h_z z}$

This results in a contest function, a type of model that I’ve discussed in some earlier posts in a rather different context.

The expected payoff for worker X is:

E[Ux] = hxx/(hxx + hzz) V – x

$E[U_x] = \frac{h_x x}{h_x x + h_z z} V – x$

Maximizing this with respect to the choice of effort x (which is all that X can control at this point) yields:

hxhzz V = (hxx + hzz)2

$h_x h_z x V = (h_x x + h_z z)^2$

A similar maximization for worker Z yields:

hxhzx V = (hxx + hzz)2

$h_x h_z z V = (h_x x + h_z z)^2$

It follows that x=z, i.e. X and Z will exert equal efforts in Nash equilibrium. Their probability of success will then be contingent entirely on their skill levels:

P[X] = hx/(hx + hz).

$P[X] = \frac{h_x}{h_x + h_y}$

Substituting that back in, we can solve for the actual amount of effort:

hxhzx V = (hx + hz)2x2

$h_x h_z x V = (h_x + h_z)^2 x^2$

x = hxhzV/(hx + hz)2

$x = \frac{h_x h_z}{h_x + h_z} V$

Now let’s see what that gives for the expected payoffs of the firm and the workers. This is worker X’s expected payoff:

E[Ux] = hx/(hx + hz) V – hxhzV/(hx + hz)2 = (hx/(hx + hz))2 V

$E[U_x] = \frac{h_x}{h_x + h_z} V – \frac{h_x h_z}{(h_x + h_z)^2} V = \left( \frac{h_x}{h_x + h_z}\right)^2 V$

Worker Z’s expected payoff is the same, with hx and hz exchanged:

E[Uz] = (hz/(hx + hz))2 V

$E[U_z] = \left( \frac{h_z}{h_x + h_z}\right)^2 V$

What about the firm? Their expected payoff is the the probability of hiring X, times the value of hiring X, plus the probability of hiring Z, times the value of hiring Z, all minus the cost c:

E[Uf] = hx/(hx + hz) hx Y + hz/(hx + hz) hz Y – c= (hx2 + hz2)/(hx + hz) Y – c

$E[U_f] = \frac{h_x}{h_x + h_z} h_x Y + \frac{h_z}{h_x + h_z} h_z Y – c = \frac{h_x^2 + h_z^2}{h_x + h_z} Y – c$

To see whether the application process was worthwhile, let’s compare against the alternative of simply flipping a coin and hiring X or Z at random. The probability of getting hired is then 1/2 for each candidate.

Expected payoffs for X and Z are now equal:

E[Ux] = E[Uz] = V/2

$E[U_x] = E[U_z] = \frac{V}{2}$

The expected payoff for the firm can be computed the same as before, but now without the cost c:

E[Uf] = 1/2 hx Y + 1/2 hz Y = (hx + hz)/2 Y

$E[U_f] = \frac{1}{2} h_x Y + \frac{1}{2} h_z Y = \frac{h_x + h_z}{2} Y$

This has a very simple interpretation: The expected value to the firm is just the average quality of the two workers, times the overall value of the job.

Which of these two outcomes is better? Well, that depends on the parameters, of course. But in particular, it depends on the difference between hx and hz.

Consider two extremes: In one case, the two workers are indistinguishable, and hx = hz = h. In that case, the payoffs for the hiring process reduce to the following:

E[Ux] = E[Uz] = V/4

$E[U_x] = E[U_z] = \frac{V}{4}$

E[Uf] = h Y – c

$E[U_f] = h Y – c$

Compare this against the payoffs for hiring randomly:

E[Ux] = E[Uz] = V/2

$E[U_x] = E[U_z] = \frac{V}{2}$

E[Uf] = h Y

$E[U_f] = h Y$

Both the workers and the firm are strictly better off if the firm just hires at random. This makes sense, since the workers have identical skill levels.

Now consider the other extreme, where one worker is far better than the other; in fact, one is nearly worthless, so hz ~ 0. (I can’t do exactly zero because I’d be dividing by zero, but let’s say one is 100 times better or something.)

In that case, the payoffs for the hiring process reduce to the following:

E[Ux] = V

E[Uz] = 0

$E[U_x] = V$

$E[U_z] = 0$

X will definitely get the job, so X is much better off.

E[Uf] = hx Y – c

$E[U_f] = h_x Y – c$

E[Ux] = E[Uz] = V/2

$E[U_x] = E[U_z] = \frac{V}{2}$

E[Uf] = hY/2

$E[U_f] = \frac{h}{2} Y$

As long as c < hY/2, both the firm and the higher-skill worker are better off in this scenario. (The lower-skill worker is worse off, but that’s not surprising.) The total expected benefit for everyone is also higher in this scenario.

Thus, the difference in skill level between the applicants is vital. If candidates are very different in skill level, in a way that the application process can accurately measure, then a long and costly application process can be beneficial, not only for the firm but also for society as a whole.

In these extreme examples, it was either not worth it for the firm, or worth it for everyone. But there is an intermediate case worth looking at, where the long and costly process can be worth it for the firm, but not for society as a whole. I will call this case hyper-competition—a system that is so competitive it makes society overall worse off.

This inefficient result occurs precisely when:
c < (hx2 + hz2)/(hx + hz) Y – (hx + hz)/2 Y < c + (hx/(hx + hz))2 V + (hz/(hx + hz))2 V

$c < \frac{h_x^2 + h_z^2}{h_x + h_z} Y – \frac{h_x + h_z}{2} Y < c + \left( \frac{h_x}{h_x + h_z}\right)^2 V + \left( \frac{h_z}{h_x + h_z}\right)^2 V$

This simplifies to:

c < (hx – hz)2/(2hx + 2hz) Y < c + (hx2 + hz2)/(hx + hz)2 V

$c < \frac{(h_x – h_z)^2}{2 (h_x + h_z)} Y < c + \frac{(h_x^2 + h_z^2)}{(h_x+h_z)^2} V$

If c is small, then we are interested in the case where:

(hx – hz)2 Y/2 < (hx2 + hz2)/(hx + hz) V

$\frac{(h_x – h_z)^2}{2} Y < \frac{h_x^2 + h_z^2}{h_x + h_z} V$

This is true precisely when the difference hx – hz is small compared to the overall size of hx or hz—that is, precisely when candidates are highly skilled but similar. This is pretty clearly the typical case in the real world. If the candidates were obviously different, you wouldn’t need a competitive process.

For instance, suppose that hx = 10 and hz = 8, while V = 180, Y = 20 and c = 1.

Then, if we hire randomly, these are the expected payoffs:

E[Uf] = (hx + hz)/2 Y = 180

E[Ux] = E[Uz] = V/2 = 90

If we use the complicated hiring process, these are the expected payoffs:

E[Ux] = (hx/(hx + hz))2 V = 55.5

E[Uz] = (hz/(hx + hz))2 V = 35.5

E[Uf] = (hx2 + hz2)/(hx + hz) Y – c = 181

The firm gets a net benefit of 1, quite small; while the workers face a far larger total expected loss of 90. And these candidates aren’t that similar: One is 25% better than the other. Yet because the effort expended in applying was so large, even this improvement in quality wasn’t worth it from society’s perspective.

This conclude’s the algebra for today, if you’ve been skipping it.

In this model I’ve only considered the case of exactly two applicants, but this can be generalized to more applicants, and the effect only gets stronger: Seemingly-large differences in each worker’s skill level can be outweighed by the massive cost of making so many people work so hard to apply and get nothing to show for it.

Thus, hyper-competition can exist despite apparently large differences in skill. Indeed, it is precisely the typical real-world scenario with many applicants who are similar that we expect to see the greatest inefficiencies. In the absence of intervention, we should expect markets to get this wrong.

Of course, we don’t actually want employers to hire randomly, right? We want people who are actually qualified for their jobs. Yes, of course; but you can probably assess that with nothing more than a resume and maybe a short interview. Most employers are not actually trying to find qualified candidates; they are trying to sift through a long list of qualified candidates to find the one that they think is best qualified. And my suspicion is that most of them honestly don’t have good methods of determining that.

This means that it could be an improvement for society to simply ban long hiring processes like these—indeed, perhaps ban job interviews altogether, as I can hardly think of a more efficient mechanism for allowing employers to discriminate based on race, gender, age, or disability than a job interview. Just collect a resume from each applicant, remove the ones that are unqualified, and then roll a die to decide which one you hire.

This would probably make the fit of workers to their jobs somewhat worse than the current system. But most jobs are learned primarily through experience anyway, so once someone has been in a job for a few years it may not matter much who was hired originally. And whatever cost we might pay in less efficient job matches could be made up several times over by the much faster, cheaper, easier, and less stressful process of applying for jobs.

Indeed, think for a moment of how much worse it feels being turned down for a job after a lengthy and costly application process that is designed to assess your merit (but may or may not actually do so particularly well), as opposed to simply finding out that you lost a high-stakes die roll. Employers could even send out letters saying one of two things: “You were rejected as unqualifed for this position.” versus “You were qualified, but you did not have the highest die roll.” Applying for jobs already feels like a crapshoot; maybe it should literally be one.

People would still have to apply for a lot of jobs—actually, they’d probably end up applying for more, because the lower cost of applying would attract more applicants. But since the cost is so much lower, it would still almost certainly be easier to do a job search than it is in the current system. In fact, it could largely be automated: simply post your resume on a central server and the system matches you with employers’ requirements and then randomly generates offers. Employers and prospective employees could fill out a series of forms just once indicating what they were looking for, and then the system could do the rest.

What I find most interesting about this policy idea is that it is in an important sense anti-meritocratic. We are in fact reducing the rewards for high levels of skill—at least a little bit—in order to improve society overall and especially for those with less skill. This is exactly the kind of policy proposal that I had hoped to see from a book like The Meritocracy Trap, but never found there. Perhaps it’s too radical? But the book was all about how we need fundamental, radical change—and then its actual suggestions were simple, obvious, and almost uncontroversial.

Note that this simplified process would not eliminate the incentives to get major, verifiable qualifications like college degrees or years of work experience. In fact, it would focus the incentives so that only those things matter, instead of whatever idiosyncratic or even capricious preferences HR agents might have. There would be no more talk of “culture fit” or “feeling right for the job”, just: “What is their highest degree? How many years have they worked in this industry?” I suppose this is credentialism, but in a world of asymmetric information, I think credentialism may be our only viable alternative to nepotism.

Of course, it’s too late for me. But perhaps future generations may benefit from this wisdom.

Nov 29 JDN 2459183

For the last several weeks I’ve been participating in a program called “positive intelligence” (which they abbreviate “PQ” even though that doesn’t make sense); it’s basically a self-help program that is designed to improve mood and increase productivity. I am generally skeptical of such things, and I could tell from the start that it was being massively oversold, but I had the opportunity to participate for free, and I looked into the techniques involved and most of them seem to be borrowed from cognitive-behavioral therapy and mindfulness meditation.

Overall, I would say that the program has had small but genuine benefits for me. I think the most helpful part was actually getting the chance to participate in group sessions (via Zoom of course) with others also going through the program. That kind of mutual social support can make a big difference. The group I joined was all comprised of fellow economists (some other grad students, some faculty), so we had a lot of shared experiences.

Some of the techniques feel very foolish, and others just don’t seem to work for me; but I did find at least some of the meditation techniques (which they annoyingly insist on calling by the silly name “PQ reps”) have helped me relax.

But there’s one part of the PQ program in particular that I just can’t buy into, and this is the idea that adversity is a gift and an opportunity.

They call it the “Sage perspective”: You observe the world without judging what is good or bad, and any time you think something is bad, you find a way to transform it into a gift and an opportunity. The claim is that everything—or nearly everything—that happens to you can make you better off. There’s a lot of overlap here with the attitude “Everything happens for a reason”.

I don’t doubt that sincerely believing this would make you happier. Nevertheless, it is obviously false.

If indeed adversity were a gift, we would seek it out. If getting fired or going bankrupt or getting sick were a gift and an opportunity, we’d work to make these things happen.

Yes, it’s true that sometimes an event which seems bad at the time can turn out to have good consequences in the long run. This is simply because we are unable to foresee all future ramifications. Sometimes things turn out differently than you think they will. But most of the time, when something seems bad, it is actually bad.

There might be some small amount of discomfort or risk that would be preferable to a life of complete safety and complacency; but we are perfectly capable of seeking out whatever discomfort or risk we choose. Most of us live with far more discomfort and risk than we would prefer, and simply have no choice in the matter.

If adversity were a gift, people would thank you for giving it to them. “Thanks for dumping me!” “Thanks for firing me!” “Thanks for punching me!” These aren’t the sort of thing we hear very often (at least not sincerely).

I think this is fairly obvious, honestly, so I won’t belabor it any further. But it raises a question: Is there a way to salvage the mental health benefits of this attitude while abandoning its obvious falsehood?

“Everything happens for a reason” doesn’t work; we live in a universe of deep randomness, ruled by the blind idiot gods of natural law.

“Every cloud has a silver lining” is better; but clearly not every bad thing has an upside, or if it does the upside can be so small as to be utterly negligible. (What was the upside of Rwandan genocide?) Restricted to ordinary events like getting fired this one works pretty well; but it obviously fails for the most extreme traumas, and doesn’t seem particularly helpful for the death of a loved one either.

“What doesn’t kill me makes me stronger” is better still, but clearly not true in every case; some bad events that don’t actually kill us can traumatize us and make the rest of our lives harder. Perhaps “What doesn’t permanently damage me makes me stronger”?

I think the version of this attitude that I have found closest to the truth is “Everything is raw material”. Sometimes bad things just happen: Bad luck, or bad actions, can harm just about anyone at just about any time. But it is within our power to decide how we will respond to what happens to us, and wallowing in despair is almost never the best response.

Thus, while it is foolish to see adversity as a gift, it is not so foolish to see it as an opportunity. Don’t try to pretend that bad things aren’t bad. There’s no sense in denying that we would prefer some outcomes over others, and we feel hurt or disappointed when things don’t turn out how we wanted. Yet even what is bad can still contain within it chances to learn or make things better.

# What’s wrong with “should”?

Nov 8 JDN 2459162

I have been a patient in cognitive behavioral therapy (CBT) for many years now. The central premise that thoughts can influence emotions is well-founded, and the results of CBT are empirically well supported.

One of the central concepts in CBT is cognitive distortions: There are certain systematic patterns in how we tend to think, which often results in beliefs and emotions that are disproportionate with reality.

Most of the cognitive distortions CBT deals with make sense to me—and I am well aware that my mind applies them frequently: All-or-nothing, jumping to conclusions, overgeneralization, magnification and minimization, mental filtering, discounting the positive, personalization, emotional reasoning, and labeling are all clearly distorted modes of thinking that nevertheless are extremely common.

But there’s one “distortion” on CBT lists that always bothers me: “should statements”.

Listen to this definition of what is allegedly a cognitive distortion:

Another particularly damaging distortion is the tendency to make “should” statements. Should statements are statements that you make to yourself about what you “should” do, what you “ought” to do, or what you “must” do. They can also be applied to others, imposing a set of expectations that will likely not be met.

When we hang on too tightly to our “should” statements about ourselves, the result is often guilt that we cannot live up to them. When we cling to our “should” statements about others, we are generally disappointed by their failure to meet our expectations, leading to anger and resentment.

So any time we use “should”, “ought”, or “must”, we are guilty of distorted thinking? In other words, all of ethics is a cognitive distortion? The entire concept of obligation is a symptom of a mental disorder?

Different sources on CBT will define “should statements” differently, and sometimes they offer a more nuanced definition that doesn’t have such extreme implications:

Individuals thinking in ‘shoulds’, ‘oughts; or ‘musts’ have an ironclad view of how they and others ‘should’ and ‘ought’ to be. These rigid views or rules can generate feels of anger, frustration, resentment, disappointment and guilt if not followed.

Example: You don’t like playing tennis but take lessons as you feel you ‘should’, and that you ‘shouldn’t’ make so many mistakes on the court, and that your coach ‘ought to’ be stricter on you. You also feel that you ‘must’ please him by trying harder.

This is particularly problematic, I think, because of the All-or-Nothing distortion which does genuinely seem to be common among people with depression: Unless you are very clear from the start about where to draw the line, our minds will leap to saying that all statements involving the word “should” are wrong.

I think what therapists are trying to capture with this concept is something like having unrealistic expectations, or focusing too much on what could or should have happened instead of dealing with the actual situation you are in. But many seem to be unable to articulate that clearly, and instead end up asserting that entire concept of moral obligation is a cognitive distortion.

There may be a deeper error here as well: The way we study mental illness doesn’t involve enough comparison with the control group. Psychologists are accustomed to asking the question, “How do people with depression think?”; but they are not accustomed to asking the question, “How do people with depression think compared to people who don’t?” If you want to establish that A causes B, it’s not enough to show that those with B have A; you must also show that those who don’t have B also don’t have A.

This is an extreme example for illustration, but suppose someone became convinced that depression is caused by having a liver. They studied a bunch of people with depression, and found that they all had livers; hypothesis confirmed! Clearly, we need to remove the livers, and that will cure the depression.

The best example I can find of a study that actually asked that question compared nursing students and found that cognitive distortions explain about 20% of the variance in depression. This is a significant amount—but still leaves a lot unexplained. And most of the research on depression doesn’t even seem to think to compare against people without depression.

My impression is that some cognitive distortions are genuinely more common among people with depression—but not all of them. There is an ongoing controversy over what’s called the depressive realism effect, which is the finding that in at least some circumstances the beliefs of people with mild depression seem to be more accurate than the beliefs of people with no depression at all. The result is controversial both because it seems to threaten the paradigm that depression is caused by distortions, and because it seems to be very dependent on context; sometimes depression makes people more accurate in their beliefs, other times it makes them less accurate.

Overall, I am inclined to think that most people have a variety of cognitive distortions, but we only tend to notice when those distortions begin causing distress—such when are they involved in depression. Human thinking in general seems to be a muddled mess of heuristics, and the wonder is that we function as well as we do.

Does this mean that we should stop trying to remove cognitive distortions? Not at all. Distorted thinking can be harmful even if it doesn’t cause you distress: The obvious example is a fanatical religious or political belief that leads you to harm others. And indeed, recognizing and challenging cognitive distortions is a highly effective treatment for depression.

Actually I created a simple cognitive distortion worksheet based on the TEAM-CBT approach developed by David Burns that has helped me a great deal in a remarkably short time. You can download the worksheet yourself and try it out. Start with a blank page and write down as many negative thoughts as you can, and then pick 3-5 that seem particularly extreme or unlikely. Then make a copy of the cognitive distortion worksheet for each of those thoughts and follow through it step by step. Particularly do not ignore the step “This thought shows the following good things about me and my core values:”; that often feels the strangest, but it’s a critical part of what makes the TEAM-CBT approach better than conventional CBT.

So yes, we should try to challenge our cognitive distortions. But the mere fact that a thought is distressing doesn’t imply that it is wrong, and giving up on the entire concept of “should” and “ought” is throwing out a lot of babies with that bathwater.

We should be careful about labeling any thoughts that depressed people have as cognitive distortions—and “should statements” is a clear example where many psychologists have overreached in what they characterize as a distortion.

# What meritocracy trap?

Nov 1 JDN 2459155

So I just finished reading The Meritocracy Trap by David Markovits.

The basic thesis of the book is that America’s rising inequality is not due to a defect in our meritocratic ideals, but is in fact their ultimate fruition. Markovits implores us to reject the very concept of meritocracy, and replace it with… well, something, and he’s never very clear about exactly what.

The most frustrating thing about reading this book is trying to figure out where Markovits draws the line for “elite”. He rapidly jumps between talking about the upper quartile, the upper decile, the top 1%, and even the top 0.1% or top 0.01% while weaving his narrative. The upper quartile of the US contains 75 million people; the top 0.01% contains only 300,000. The former is the size of Germany, the latter the size of Iceland (which has fewer people than Long Beach). Inequality which concentrates wealth in the top quartile of Americans is a much less serious problem than inequality which concentrates wealth in the top 0.01%. It could still be a problem—those lower three quartiles are people too—but it is definitely not nearly as bad.

I think it’s particularly frustrating to me personally, because I am an economist, which means both that such quantitative distinctions are important to me, and also that whether or not I myself am in this “elite” depends upon which line you are drawing. Do I have a post-graduate education? Yes. Was I born into the upper quartile? Not quite, but nearly. Was I raised by married parents in a stable home? Certainly. Am I in the upper decile and working as a high-paid professional? Hopefully I will be soon. Will I enter the top 1%? Maybe, maybe not. Will I join the top 0.1%? Probably not. Will I ever be in the top 0.01% and a captain of industry? Almost certainly not.

So, am I one of the middle class who are suffering alienation and stagnation, or one of the elite who are devouring themselves with cutthroat competition? Based on BLS statistics for economists and job offers I’ve been applying to, my long-term household income is likely to be about 20-50% higher than my parents’; this seems like neither the painful stagnation he attributes to the middle class nor the unsustainable skyrocketing of elite incomes. (Even 50% in 30 years is only 1.4% per year, about our average rate of real GDP growth.) Marxists would no doubt call me petit bourgeoisie; but isn’t that sort of the goal? We want as many people as possible to live comfortable upper-middle class lives in white-collar careers?

Markovits characterizes—dare I say caricatures—the habits of the middle-class versus the elite, and once again I and most people I know cross-cut them: I spend more time with friends than family (elite), but I cook familiar foods, not fancy dinners (middle); I exercise fairly regularly and don’t watch much television (elite) but play a lot of video games and sleep a lot as well (middle). My web searches involve technology and travel (elite), but also chronic illness (middle). I am a donor to Amnesty International (elite) but also play tabletop role-playing games (middle). I have a functional, inexpensive car (middle) but a top-of-the-line computer (elite)—then again that computer is a few years old now (middle). Most of the people I hang out with are well-educated (elite) but struggling financially (middle), civically engaged (elite) but pessimistic (middle). I rent my apartment and have a lot of student debt (middle) but own stocks (elite). (The latter seemed like a risky decision before the pandemic, but as stock prices have risen and student loan interest was put on moratorium, it now seems positively prescient.) So which class am I, again?

I went to public school (middle) but have a graduate degree (elite). I grew up in Ann Arbor (middle) but moved to Irvine (elite). Then again my bachelor’s was at a top-10 institution (elite) but my PhD will be at only a top-50 (middle). The beautiful irony there is that the top-10 institution is the University of Michigan and the top-50 institution is the University of California, Irvine. So I can’t even tell which class each of those events is supposed to represent! Did my experience of Ann Arbor suddenly shift from middle class to elite when I graduated from public school and started attending the University of Michigan—even though about a third of my high school cohort did exactly that? Was coming to UCI an elite act because it’s a PhD in Orange County, or a middle-class act because it’s only a top-50 university?

If the gap between these two classes is such a wide chasm, how am I straddling it? I honestly feel quite confident in characterizing myself as precisely the upwardly-mobile upper-middle class that Markovits claims no longer exists. Perhaps we’re rarer than we used to be; perhaps our status is more precarious; but we plainly aren’t gone.

Markovits keeps talking about “radical differences” “not merely in degree but in kind” between “subordinate” middle-class workers and “superordinate” elite workers, but if the differences are really that stark, why is it so hard to tell which group I’m in? From what I can see, the truth seems less like a sharp divide between middle-class and upper-class, and more like an increasingly steep slope from middle-class to upper-middle class to upper-class to rich to truly super-rich. If I had to put numbers on this, I’d say annual household incomes of about $50,000,$100,000, $200,000,$400,000, $1 million, and$10 million respectively. (And yet perhaps I should add more categories: Even someone who makes $10 million a year has only pocket change next to Elon Musk or Jeff Bezos.) The slope has gotten steeper over time, but it hasn’t (yet?) turned into a sharp cliff the way Markovits describes. America’s Lorenz curve is clearly too steep, but it doesn’t have a discontinuity as far as I can tell. Some of the inequalities Markovits discusses are genuine, but don’t seem to be particularly related to meritocracy. The fact that students from richer families go to better schools indeed seems unjust, but the problem is clearly not that the rich schools are too good (except maybe at the very top, where truly elite schools seem a bit excessive—five-figure preschool tuition?), but that the poor schools are not good enough. So it absolutely makes sense to increase funding for poor schools and implement various reforms, but this is hardly a radical notion—nor is it in any way anti-meritocratic. Providing more equal opportunities for the poor to raise their own station is what meritocracy is all about. Other inequalities he objects to seem, if not inevitable, far too costly to remove: Educated people are better parents, who raise their children in ways that make them healthier, happier, and smarter? No one is going to apologize for being a good parent, much less stop doing so because you’re concerned about what it does to inequality. If you have some ideas for how we might make other people into better parents, by all means let’s hear them. But I believe I speak for the entire upper-middle class when I say: when I have kids of my own, I’m going to read to them, I’m not going to spank them, and there’s not a damn thing you can do to change my mind on either front. Quite frankly, this seems like a heavy-handed satire of egalitarianism, right out of Harrison Bergeron: Let’s make society equal by forcing rich people to neglect and abuse their kids as much as poor people do! My apologies to Vonnegut: I thought you were ridiculously exaggerating, but apparently some people actually think like this. This is closely tied with the deepest flaw in the argument: The meritocratic elite are actually more qualified. It’s easy to argue that someone like Donald Trump shouldn’t rule the world; he’s a deceitful, narcissistic, psychopathic, incompetent buffoon. (The only baffling part is that 40% of American voters apparently disagree.) But it’s a lot harder to see why someone like Bill Gates shouldn’t be in charge of things: He’s actually an extremely intelligent, dedicated, conscientious, hard-working, ethical, and competent individual. Does he deserve$100 billion? No, for reasons I’ve talked about before. But even he knows that! He’s giving most of it away to highly cost-effective charities! Bill Gates alone has saved several million lives by his philanthropy.

Markovits tries to argue that the merits of the meritocratic elite are arbitrary and contextual, like the alleged virtues of the aristocratic class: “The meritocratic virtues, that is, are artifacts of economic inequality in just the fashion in which the pitching virtues are artifacts of baseball.” (p. 264) “The meritocratic achievement commonly celebrated today, no less than the aristocratic virtue acclaimed in the ancien regime, is a sham.” (p. 268)

But it’s pretty hard for me to see how things like literacy, knowledge of history and science, and mathematical skill are purely arbitrary. Even the highly specialized skills of a quantum physicist, software engineer, or geneticist are clearly not arbitrary. Not everyone needs to know how to solve the Schrodinger equation or how to run a polymerase chain reaction, but our civilization greatly benefits from the fact that someone does. Software engineers aren’t super-productive because of high inequality; they are super-productive because they speak the secret language of the thinking machines. I suppose some of the skills involved in finance, consulting, and law are arbitrary and contextual; but he makes it sound like the only purpose graduate school serves is in teaching us table manners.

Precisely by attacking meritocracy, Markovits renders his own position absurd. So you want less competent people in charge? You want people assigned to jobs they’re not good at? You think businesses should go out of their way to hire employees who will do their jobs worse? Had he instead set out to show how American society fails at achieving its meritocratic ideals—indeed, failing to provide equality of opportunity for the poor is probably the clearest example of this—he might have succeeded. But instead he tries to attack the ideals themselves, and fails miserably.

Markovits avoids the error that David Graeber made: Graeber sees that there are many useless jobs but doesn’t seem to have a clue why these jobs exist (and turns to quite foolish Marxian conspiracy theories to explain it). Markovits understands that these jobs are profitable for the firms that employ them, but unproductive for society as a whole. He is right; this is precisely what virtually the entire fields of finance, sales, advertising, and corporate law consist of. Most people in our elite work very hard with great skill and competence, and produce great profits for the corporations that employ them, all while producing very little of genuine societal value. But I don’t see how this is a flaw in meritocracy per se.

Nor does Markovits stop at accusing employment of being rent-seeking; he takes aim at education as well: “when the rich make exceptional investments in schooling, this does reduce the value of ordinary, middle-class training and degrees. […] Meritocratic education inexorably engenders a wasteful and destructive arms educational arms race, which ultimately benefits no one, not even the victors.” (p.153) I don’t doubt that education is in part such a rent-seeking arms race, and it’s worthwhile to try to minimize that. But education is not entirely rent-seeking! At the very least, is there not genuine value in teaching children to read and write and do arithmetic? Perhaps by the time we get to calculus or quantum physics or psychopathology we have reached diminishing returns for most students (though clearly at least some people get genuine value out of such things!), but education is not entirely comprised of signaling or rent-seeking (and nor do “sheepskin effects” prove otherwise).

My PhD may be less valuable to me than it would be to someone in my place 40 years ago, simply because there are more people with PhDs now and thus I face steeper competition. Then again, perhaps not, as the wage premium for college and postgraduate education has been increasing, not decreasing, over that time period. (How much of that wage premium is genuine social benefit and how much is rent-seeking is difficult to say.) In any case it’s definitely still valuable. I have acquired many genuine skills, and will in fact be able to be genuinely more productive as well as compete better in the labor market than I would have without it. Some parts of it have felt like a game where I’m just trying to stay ahead of everyone else, but it hasn’t all been that. A world where nobody had PhDs would be a world with far fewer good scientists and far slower technological advancement.

Abandoning meritocracy entirely would mean that we no longer train people to be more productive or match people to the jobs they are most qualified to do. Do you want a world where surgery is not done by the best surgeons, where airplanes are not flown by the best pilots? This necessarily means less efficient production and an overall lower level of prosperity for society as a whole. The most efficient way may not be the best way, but it’s still worth noting that it’s the most efficient way.

Really, is meritocracy the problem, or is it something else?

Markovits is clearly right that something is going wrong with American society: Our inequality is much too high, and our job market is much too cutthroat. I can’t even relate to his description of what the job market was like in the 1960s (“Old Economy Steve” has it right): “Even applicants for white-collar jobs received startlingly little scrutiny. For most midcentury workers, getting a job did not involve any application at all, in the competitive sense of the term.” (p.203)

In fact, if anything he seems to understate the difference across time, perhaps because it lets him overstate the difference across class (p. 203):

Today, by contrast, the workplace is methodically arranged around gradations of skill. Firms screen job candidates intensively at hiring, and they then sort elite and non-elite workers into separate physical spaces.

Only the very lowest-wage employers, seeking unskilled workers, hire casually. Middle-class employers screen using formal cognitive tests and lengthy interviews. And elite employers screen with urgent intensity, recruiting from only a select pool and spending millions of dollars to probe applicants over several rounds of interviews, lasting entire days.

Today, not even the lowest-wage employers hire casually! Have you ever applied to work at Target? There is a personality test you have to complete, which I presume is designed to test your reliability as an obedient corporate drone. Never in my life have I gotten a job that didn’t involve either a lengthy application process or some form of personal connection—and I hate to admit it, but usually the latter. It is literally now harder to get a job as a cashier at Target than it was to get a job as an engineer at Ford 60 years ago.

But I still can’t shake the feeling that meritocracy is not exactly what’s wrong here. The problem with the sky-high compensation packages at top financial firms isn’t that they are paid to people who are really good at their jobs; it’s that those jobs don’t actually accomplish anything beneficial for society. Where elite talent and even elite compensation is combined with genuine productivity, such as in science and engineering, it seems unproblematic (and I note that Markovits barely even touches on these industries, perhaps because he sees they would undermine his argument). The reason our economic growth seems to have slowed as our inequality has massively surged isn’t that we are doing too good a job of rewarding people for being productive.

Indeed, it seems like the problem may be much simpler: Labor supply exceeds labor demand.

Take a look at this graph from the Federal Reserve Bank of San Francisco:

[Beveridge_curve_data.png]

This graph shows the relationship over time between unemployment and job vacancies. As you can see, they are generally inversely related: More vacancies means less unemployment. I have drawn in a green line which indicates the cutoff between having more vacancies than unemployment—upper left—and having more unemployment than vacancies—lower right. We have almost always been in the state of having more unemployment than we have vacancies; notably, the mid-1960s were one of the few periods in which we had significantly more vacancies than unemployment.

For decades we’ve been instituting policies to try to give people “incentives to work”; but there is no shortage of labor in this country. We seem to have plenty of incentives to work—what we need are incentives to hire people and pay them well.

Indeed, perhaps we need incentives not to work—like a basic income or an expanded social welfare system. Thanks to automation, productivity is now astonishingly high, and yet we work ourselves to death instead of enjoying leisure.

And of course there are various other policy changes that have made our inequality worse—chiefly the dramatic drops in income tax rates at the top brackets that occurred under Reagan.

In fact, many of the specific suggestions Markovits makes—which, much to my chagrin, he waits nearly 300 pages to even mention—are quite reasonable, or even banal: He wants to end tax deductions for alumni donations to universities and require universities to enroll more people from lower income brackets; I could support that. He wants to regulate finance more stringently, eliminate most kinds of complex derivatives, harmonize capital gains tax rates to ordinary income rates, and remove the arbitrary cap on payroll taxes; I’ve been arguing for all of those things for years. What about any of these policies is anti-meritocratic? I don’t see it.

More controversially, he wants to try to re-organize production to provide more opportunities for mid-skill labor. In some industries I’m not sure that’s possible: The 10X programmer is a real phenomenon, and even mediocre programmers and engineers can make software and machines that are a hundred times as productive as doing the work by hand would be. But some of his suggestions make sense, such as policies favoring nurse practitioners over specialist doctors and legal secretaries instead of bar-certified lawyers. (And please, please reform the medical residency system! People die from the overwork caused by our medical residency system.)

But I really don’t see how not educating people or assigning people to jobs they aren’t good at would help matters—which means that meritocracy, as I understand the concept, is not to blame after all.

# How to be a good writer

Oct 25 JDN 2459148

“A writer is someone for whom writing is more difficult than it is for other people.”
~ Thomas Mann

“You simply sit down at the typewriter, open your veins, and bleed.”

~ Red Smith

Why is it so difficult to write well? Why is it that those of us who write the most often find it the most agonizing?

My guess is that many other art forms are similar, but writing is what I know best.

I have come to realize that there are four major factors which determine the quality of someone’s writing, and the pain and challenge of writing comes from the fact that they are not very compatible with one another.

The first is talent. To a certain degree, one can be born a better or worse writer, or become so through forces not of one’s own making. This one costs nothing to get if you already have it, but if you don’t have it, you can’t really acquire it. If you do lack talent, that doesn’t mean you can’t write; but it does limit how successful you are likely to be at writing. (Then again, some very poorly-written books have made some very large sums of money!) It’s also very difficult to know whether you really have talent; people tell me I do, so I suppose I believe them.

The second is practice. You must write and keep on writing. You must write many things in many contexts, and continue to write despite various pressures and obstacles trying to stop you from writing. Reading is also part of this process, as we learn new ways to use words by seeing how others have used them. In fact, you should read more words than you write.

The third is devotion. If you are to truly write well, you must pour your heart and soul into what you write. I can tell fairly quickly whether someone is serious about writing or not by seeing how they react to the metaphor I like to use: “I carve off shards of my soul and assemble them into robots that I release into the world; and when the robots fail, I wonder whether I have assembled them incorrectly, or if there is something fundamentally wrong with my soul itself.” Most people react with confusion. Serious writers nod along in agreement.

The fourth is criticism. You must seek out criticism from a variety of sources, you must accept that criticism, and you must apply it in improving your work in the future. You must avoid becoming defensive, but you must also recognize that disagreement will always exist. You will never satisfy everyone with what you write. The challenge is to satisfy as much of your target audience as possible.

And therein lies the paradox: For when you have devoted your heart and soul into a work, receiving criticism on it can make you want to shut down, wanting to avoid that pain. And thus, you stop practicing, and you stop improving.


text:
## CryptoDB

### Palash Sarkar

#### Publications

Year
Venue
Title
2020
JOFC
This work considers the problem of fast and secure scalar multiplication using curves of genus one defined over a field of prime order. Previous work by Gaudry and Lubicz (Finite Fields Appl 15(2):246–260, 2009 ) had suggested the use of the associated Kummer line to speed up scalar multiplication. In the present work, we explore this idea in detail. The first task is to obtain an elliptic curve in Legendre form which satisfies necessary security conditions such that the associated Kummer line has small parameters and a base point with small coordinates. It turns out that the ladder step on the Kummer line supports parallelism and can be implemented very efficiently in constant time using the single-instruction multiple-data (SIMD) operations available in modern processors. For the 128-bit security level, this work presents three Kummer lines denoted as $K_1:=\mathsf{KL2519(81,20)}$ K 1 : = KL 2519 ( 81 , 20 ) , $K_2:=\mathsf{KL25519(82,77)}$ K 2 : = KL 25519 ( 82 , 77 ) and $K_3:=\mathsf{KL2663(260,139)}$ K 3 : = KL 2663 ( 260 , 139 ) over the three primes $2^{251}-9$ 2 251 - 9 , $2^{255}-19$ 2 255 - 19 and $2^{266}-3$ 2 266 - 3 , respectively. Implementations of scalar multiplications for all three Kummer lines using Intel intrinsics have been done, and the code is publicly available. Timing results on the Skylake and the Haswell processors of Intel indicate that both fixed base and variable base scalar multiplications for $K_1$ K 1 and $K_2$ K 2 are faster than those achieved by Sandy2x , which is a highly optimised SIMD implementation in assembly of the well-known Curve25519 . On Skylake, both fixed base and variable base scalar multiplications for $K_3$ K 3 are faster than Sandy2x , whereas on Haswell, fixed base scalar multiplication for $K_3$ K 3 is faster than Sandy2x while variable base scalar multiplication for both $K_3$ K 3 and Sandy2x takes roughly the same time. In practical terms, the particular Kummer lines that are introduced in this work are serious candidates for deployment and standardisation. We further illustrate the usefulness of the proposed Kummer lines by instantiating the quotient Digital Signature Algorithm on all the three Kummer lines.
2017
TOSC
Universal hash functions based on univariate polynomials are well known, e.g. Poly1305 and GHASH. Using Horner’s rule to evaluate such hash functionsrequire l − 1 field multiplications for hashing a message consisting of l blocks where each block is one field element. A faster method is based on the class of Bernstein-Rabin-Winograd (BRW) polynomials which require ⌊l/2⌋ multiplications and ⌊lgl⌋ squarings for l≥3 blocks. Though this is significantly smaller than Horner’s rule based hashing, implementation of BRW polynomials for variable length messages present significant difficulties. In this work, we propose a two-level hash function where BRW polynomial based hashing is done at the lower level and Horner’s rule based hashing is done at the higher level. The BRW polynomial based hashing is applied to a fixed number of blocks and hence the difficulties in handling variable length messages is avoided. Even though the hash function has two levels, we show that it is sufficient to use a single field element as the hash key. The basic idea is instantiated to propose two new hash functions, one which hashes a single binary string and the other can hash a vector of binary strings. We describe two actual implementations, one over F2128 and the other over F2256 both using the pclmulqdq instruction available in modern Intel processors. On both the Haswell and Skylake processors, the implementation over F2128 is faster than both an implementation of GHASH by Gueron; and a highly optimised implementation, also by Gueron, of another polynomial based hash function called POLYVAL. We further show that the Fast Fourier Transform based field multiplication over F2256 proposed by Bernstein and Chou can be used to evaluate the new hash function at a cost of about at most 46 bit operations per bit of digest, but, unlike the Bernstein-Chou analysis, there is no hidden cost of generating the hash key. More generally, the new idea of building a two-level hash function having a single field element as the hash key can be applied to other finite fields to build new hash functions.
2017
ASIACRYPT
2016
EUROCRYPT
2016
ASIACRYPT
2012
PKC
2006
ASIACRYPT
2006
FSE
2006
PKC
2005
ASIACRYPT
2004
ASIACRYPT
2004
ASIACRYPT
2004
FSE
2004
PKC
2003
ASIACRYPT
2003
FSE
2002
ASIACRYPT
2002
CRYPTO
2001
CHES
2000
CRYPTO
2000
EUROCRYPT
1999
CRYPTO

#### Program Committees

Asiacrypt 2015
Crypto 2015
Asiacrypt 2014 (Program chair)
Asiacrypt 2013 (Program chair)
Eurocrypt 2012
Crypto 2012
Asiacrypt 2011
Crypto 2010
FSE 2010
Asiacrypt 2008
Asiacrypt 2007
FSE 2007
Crypto 2007
FSE 2005
Eurocrypt 2005

format: plain


text:
# Overlap

Logic Level 2

How many times do the minute and hour hands of a clock perfectly overlap in 24 hours, from 7 a.m. to 7 a.m. the next day?

Clarification: It is a standard analog clock where both hands move continuously.

×