Month: May 2021

Why is cryptocurrency popular?

PNRJ financial advice, financial fraud, futurism, heuristics and biases, market failure, public policy , , , , , , , , , , , , ,

May 30 JDN 2459365

At the time of writing, the price of most cryptocurrencies has crashed, likely due to a ban on conventional banks using cryptocurrency in China (though perhaps also due to Elon Musk personally refusing to accept Bitcoin at his businesses). But for all I know by the time this post goes live the price will surge again. Or maybe they’ll crash even further. Who knows? The prices of popular cryptocurrencies have been extremely volatile.

This post isn’t really about the fluctuations of cryptocurrency prices. It’s about something a bit deeper: Why are people willing to put money into cryptocurrencies at all?

The comparison is often made to fiat currency: “Bitcoin isn’t backed by anything, but neither is the US dollar.”

But the US dollar is backed by something: It’s backed by the US government. Yes, it’s not tradeable for gold at a fixed price, but so what? You can use it to pay taxes. The government requires it to be legal tender for all debts. There are certain guaranteed exchange rights built into the US dollar, which underpin the value that the dollar takes on in other exchanges. Moreover, the US Federal Reserve carefully manages the supply of US dollars so as to keep their value roughly constant.

Bitcoin does not have this (nor does Dogecoin, or Etherium, or any of the other hundreds of lesser-known cryptocurrencies). There is no central bank. There is no government making them legal tender for any debts at all, let alone all of them. Nobody collects taxes in Bitcoin.

And so, because its value is untethered, Bitcoin’s price rises and falls, often in huge jumps, more or less randomly. If you look all the way back to when it was introduced, Bitcoin does seem to have an overall upward price trend, but this honestly seems like a statistical inevitability: If you start out being worthless, the only way your price can change is upward. While some people have become quite rich by buying into Bitcoin early on, there’s no particular reason to think that it will rise in value from here on out.

Nor does Bitcoin have any intrinsic value. You can’t eat it, or build things out of it, or use it for scientific research. It won’t even entertain you (unless you have a very weird sense of entertainment). Bitcoin doesn’t even have “intrinsic value” the way gold does (which is honestly an abuse of the term, since gold isn’t actually especially useful): It isn’t innately scarce. It was made scarce by its design: Through the blockchain, a clever application of encryption technology, it was made difficult to generate new Bitcoins (called “mining”) in an exponentially increasing way. But the decision of what encryption algorithm to use was utterly arbitrary. Bitcoin mining could just as well have been made a thousand times easier or a thousand times harder. They seem to have hit a sweet spot where they made it just hard enough that it make Bitcoin seem scarce while still making it feel feasible to get.

We could actually make a cryptocurrency that does something useful, by tying its mining to a genuinely valuable pursuit, like analyzing scientific data or proving mathematical theorems. Perhaps I should suggest a partnership with Folding@Home to make FoldCoin, the crypto coin you mine by folding proteins. There are some technical details there that would be a bit tricky, but I think it would probably be feasible. And then at least all this computing power would accomplish something, and the money people make would be to compensate them for their contribution.

But Bitcoin is not useful. No institution exists to stabilize its value. It constantly rises and falls in price. Why do people buy it?

In a word, FOMO. The fear of missing out. People buy Bitcoin because they see that a handful of other people have become rich by buying and selling Bitcoin. Bitcoin symbolizes financial freedom: The chance to become financially secure without having to participate any longer in our (utterly broken) labor market.

In this, volatility is not a bug but a feature: A stable currency won’t change much in value, so you’d only buy into it because you plan on spending it. But an unstable currency, now, there you might manage to get lucky speculating on its value and get rich quick for nothing. Or, more likely, you’ll end up poorer. You really have no way of knowing.

That makes cryptocurrency fundamentally like gambling. A few people make a lot of money playing poker, too; but most people who play poker lose money. Indeed, those people who get rich are only able to get rich because other people lose money. The game is zero-sum—and likewise so is cryptocurrency.

Note that this is not how the stock market works, or at least not how it’s supposed to work (sometimes maybe). When you buy a stock, you are buying a share of the profits of a corporation—a real, actual corporation that produces and sells goods or services. You’re (ostensibly) supplying capital to fund the operations of that corporation, so that they might make and sell more goods in order to earn more profit, which they will then share with you.

Likewise when you buy a bond: You are lending money to an institution (usually a corporation or a government) that intends to use that money to do something—some real actual thing in the world, like building a factory or a bridge. They are willing to pay interest on that debt in order to get the money now rather than having to wait.

Initial Coin Offerings were supposed to be away to turn cryptocurrency into a genuine investment, but at least in their current virtually unregulated form, they are basically indistinguishable from a Ponzi scheme. Unless the value of the coin is somehow tied to actual ownership of the corporation or shares of its profits (the way stocks are), there’s nothing to ensure that the people who buy into the coin will actually receive anything in return for the capital they invest. There’s really very little stopping a startup from running an ICO, receiving a bunch of cash, and then absconding to the Cayman Islands. If they made it really obvious like that, maybe a lawsuit would succeed; but as long as they can create even the appearance of a good-faith investment—or even actually make their business profitable!—there’s nothing forcing them to pay a cent to the owners of their cryptocurrency.

The really frustrating thing for me about all this is that, sometimes, it works. There actually are now thousands of people who made decisions that by any objective standard were irrational and irresponsible, and then came out of it millionaires. It’s much like the lottery: Playing the lottery is clearly and objectively a bad idea, but every once in awhile it will work and make you massively better off.

It’s like I said in a post about a year ago: Glorifying superstars glorifies risk. When a handful of people can massively succeed by making a decision, that makes a lot of other people think that it was a good decision. But quite often, it wasn’t a good decision at all; they just got spectacularly lucky.

I can’t exactly say you shouldn’t buy any cryptocurrency. It probably has better odds than playing poker or blackjack, and it certainly has better odds than playing the lottery. But what I can say is this: It’s about odds. It’s gambling. It may be relatively smart gambling (poker and blackjack are certainly a better idea than roulette or slot machines), with relatively good odds—but it’s still gambling. It’s a zero-sum high-risk exchange of money that makes a few people rich and lots of other people poorer.

With that in mind, don’t put any money into cryptocurrency that you couldn’t afford to lose at a blackjack table. If you’re looking for something to seriously invest your savings in, the answer remains the same: Stocks. All the stocks.

I doubt this particular crash will be the end for cryptocurrency, but I do think it may be the beginning of the end. I think people are finally beginning to realize that cryptocurrencies are really not the spectacular innovation that they were hyped to be, but more like a high-tech iteration of the ancient art of the Ponzi scheme. Maybe blockchain technology will ultimately prove useful for something—hey, maybe we should actually try making FoldCoin. But the future of money remains much as it has been for quite some time: Fiat currency managed by central banks.

Selectivity is a terrible measure of quality

PNRJ market failure, science and academia , , , , , , , , ,

May 23 JDN 2459358

How do we decide which universities and research journals are the best? There are a vast number of ways we could go about this—and there are in fact many different ranking systems out there, though only a handful are widely used. But one primary criterion which seems to be among the most frequently used is selectivity.

Selectivity is a very simple measure: What proportion of people who try to get in, actually get in? For universities this is admission rates for applicants; for journals it is acceptance rates for submitted papers.

The top-rated journals in economics have acceptance rates of 1-7%. The most prestigious universities have acceptance rates of 4-10%. So a reasonable ballpark is to assume a 95% chance of not getting accepted in either case. Of course, some applicants are more or less qualified, and some papers are more or less publishable; but my guess is that most applicants are qualified and most submitted papers are publishable. So these low acceptance rates mean refusing huge numbers of qualified people.


Selectivity is an objective, numeric score that can be easily generated and compared, and is relatively difficult to fake. This may accouunt for its widespread appeal. And it surely has some correlation with genuine quality: Lots of people are likely to apply to a school because it is good, and lots of people are likely to submit to a journal because it is good.

But look a little bit closer, and it becomes clear that selectivity is really a terrible measure of quality.


One, it is extremely self-fulfilling. Once a school or a journal becomes prestigious, more people will try to get in there, and that will inflate its selectivity rating. Harvard is extremely selective because Harvard is famous and high-rated. Why is Harvard so high-rated? Well, in part because Harvard is extremely selective.

Two, it incentivizes restricting the number of applicants accepted.

Ivy League schools have vast endowments, and could easily afford to expand their capacity, thus employing more faculty and educating more students. But that would require reducing their acceptance rates and hence jeopardizing their precious selectivity ratings. If the goal is to give as many people as possible the highest quality education, then selectivity is a deeply perverse incentive: It specifically incentivizes not educating too many students.

Similarly, most journals include something in their rejection letters about “limited space”, which in the age of all-digital journals is utter nonsense. Journals could choose to publish ten, twenty, fifty times as many papers as they currently do—or half, or a tenth. They could publish everything that gets submitted, or only publish one paper a year. It’s an entirely arbitrary decision with no real constraints. They choose what proportion of papers to publish entirely based primarily on three factors that have absolutely nothing to do with limited space: One, they want to publish enough papers to make it seem like they are putting out regular content; two, they want to make sure they publish anything that will turn out to be a major discovery (though they honestly seem systematically bad at predicting that); and three, they want to publish as few papers as possible within those constraints to maximize their selectivity.

To be clear, I’m not saying that journals should publish everything that gets submitted. Actually I think too many papers already get published—indeed, too many get written. The incentives in academia are to publish as many papers in top journals as possible, rather than to actually do the most rigorous and ground-breaking research. The best research often involves spending long periods of time making very little visible progress, and it does not lend itself to putting out regular publications to impress tenure committees and grant agencies.

The number of scientific papers published each year has grown at about 5% per year since 1900. The number of peer-reviewed journals has grown at an increasing rate, from about 3% per year for most of the 20th century to over 6% now. These are far in excess of population growth, technological advancement, or even GDP growth; this many scientific papers is obviously unsustainable. There are now 300 times as many scientific papers published per year as there were in 1900—while the world population has only increased by about 5-fold during that time. Yes, the number of scientists has also increased—but not that fast. About 8 million people are scientists, publishing an average of 2 million articles per year—one per scientist every four years. But the number of scientist jobs grows at just over 1%—basically tracking population growth or the job market in general. If papers published continue to grow at 5% while the number of scientists increases at 1%, then in 100 years each scientist will have to publish 48 times as many papers as today, or about 1 every month.


So the problem with research journals isn’t so much that journals aren’t accepting enough papers, as that too many people are submitting papers. Of course the real problem is that universities have outsourced their hiring decisions to journal editors. Rather than actually evaluating whether someone is a good teacher or a good researcher (or accepting that they can’t and hiring randomly), universities have trusted in the arbitrary decisions of research journals to decide whom they should hire.

But selectivity as a measure of quality means that journals have no reason not to support this system; they get their prestige precisely from the fact that scientists are so pressured to publish papers. The more papers get submitted, the better the journals look for rejecting them.

Another way of looking at all this is to think about what the process of acceptance or rejection entails. It is inherently a process of asymmetric information.

If we had perfect information, what would the acceptance rate of any school or journal be? 100%, regardless of quality. Only the applicants who knew they would get accepted would apply. So the total number of admitted students and accepted papers would be exactly the same, but all the acceptance rates would rise to 100%.

Perhaps that’s not realistic; but what if the application criteria were stricter? For instance, instead of asking you your GPA and SAT score, Harvard’s form could simply say: “Anyone with a GPA less than 4.0 or an SAT score less than 1500 need not apply.” That’s practically true anyway. But Harvard doesn’t have an incentive to say it out loud, because then applicants who know they can’t meet that standard won’t bother applying, and Harvard’s precious selectivity number will go down. (These are far from sufficient, by the way; I was valedictorian and had a 1590 on my SAT and still didn’t get in.)

There are other criteria they’d probably be even less willing to emphasize, but are no less significant: “If your family income is $20,000 or less, there is a 95% chance we won’t accept you.” “Other things equal, your odds of getting in are much better if you’re Black than if you’re Asian.”

For journals it might be more difficult to express the criteria clearly, but they could certainly do more than they do. Journals could more strictly delineate what kind of papers they publish: This one only for pure theory, that one only for empirical data, this one only for experimental results. They could choose more specific content niches rather than literally dozens of journals all being ostensibly about “economics in general” (the American Economic Review, the Quarterly Journal of Economics, the Journal of Political Economy, the Review of Economic Studies, the European Economic Review, the International Economic Review, Economic Inquiry… these are just the most prestigious). No doubt there would still have to be some sort of submission process and some rejections—but if they really wanted to reduce the number of submissions they could easily do so. The fact is, they want to have a large number of submissions that they can reject.

What this means is that rather than being a measure of quality, selectivity is primarily a measure of opaque criteria. It’s possible to imagine a world where nearly every school and every journal accept less than 1% of applicants; this would occur if the criteria for acceptance were simply utterly unknown and everyone had to try hundreds of places before getting accepted.


Indeed, that’s not too dissimilar to how things currently work in the job market or the fiction publishing market. The average job opening receives a staggering 250 applications. In a given year, a typical literary agent receives 5000 submissions and accepts 10 clients—so about one in every 500.

For fiction writing I find this somewhat forgivable, if regrettable; the quality of a novel is a very difficult thing to assess, and to a large degree inherently subjective. I honestly have no idea what sort of submission guidelines one could put on an agency page to explain to authors what distinguishes a good novel from a bad one (or, not quite the same thing, a successful one from an unsuccessful one).

Indeed, it’s all the worse because a substantial proportion of authors don’t even follow the guidelines that they do include! The most common complaint I hear from agents and editors at writing conferences is authors not following their submission guidelines—such basic problems as submitting content from the wrong genre, not formatting it correctly, having really egregious grammatical errors. Quite frankly I wish they’d shut up about it, because I wanted to hear what would actually improve my chances of getting published, not listen to them rant about the thousands of people who can’t bother to follow directions. (And I’m pretty sure that those people aren’t likely to go to writing conferences and listen to agents give panel discussions.)

But for the job market? It’s really not that hard to tell who is qualified for most jobs. If it isn’t something highly specialized, most people could probably do it, perhaps with a bit of training. If it is something highly specialized, you can restrict your search to people who already have the relevant education or training. In any case, having experience in that industry is obviously a plus. Beyond that, it gets much harder to assess quality—but also much less necessary. Basically anyone with an advanced degree in the relevant subject or a few years of experience at that job will probably do fine, and you’re wasting effort by trying to narrow the field further. If it is very hard to tell which candidate is better, that usually means that the candidates really aren’t that different.

To my knowledge, not a lot of employers or fiction publishers pride themselves on their selectivity. Indeed, many fiction publishers have a policy of simply refusing unsolicited submissions, relying upon literary agents to pre-filter their submissions for them. (Indeed, even many agents refuse unsolicited submissions—which raises the question: What is a debut author supposed to do?) This is good, for if they did—if Penguin Random House (or whatever that ludicrous all-absorbing conglomerate is calling itself these days; ah, what was it like in that bygone era, when anti-trust enforcement was actually a thing?) decided to start priding itself on its selectivity of 0.05% or whatever—then the already massively congested fiction industry would probably grind to a complete halt.

This means that by ranking schools and journals based on their selectivity, we are partly incentivizing quality, but mostly incentivizing opacity. The primary incentive is for them to attract as many applicants as possible, even knowing full well that they will reject most of these applicants. They don’t want to be too clear about what they will accept or reject, because that might discourage unqualified applicants from trying and thus reduce their selectivity rate. In terms of overall welfare, every rejected application is wasted human effort—but in terms of the institution’s selectivity rating, it’s a point in their favor.

Social science is broken. Can we fix it?

PNRJ core principles, critique of neoclassical economics, current events, personal, science and academia , , , , , , , , , , , , ,

May 16 JDN 2459349

Social science is broken. I am of course not the first to say so. The Atlantic recently published an article outlining the sorry state of scientific publishing, and several years ago Slate Star Codex published a lengthy post (with somewhat harsher language than I generally use on this blog) showing how parapsychology, despite being obviously false, can still meet the standards that most social science is expected to meet. I myself discussed the replication crisis in social science on this very blog a few years back.

I was pessimistic then about the incentives of scientific publishing be fixed any time soon, and I am even more pessimistic now.

Back then I noted that journals are often run by for-profit corporations that care more about getting attention than getting the facts right, university administrations are incompetent and top-heavy, and publish-or-perish creates cutthroat competition without providing incentives for genuinely rigorous research. But these are widely known facts, even if so few in the scientific community seem willing to face up to them.

Now I am increasingly concerned that the reason we aren’t fixing this system is that the people with the most power to fix it don’t want to. (Indeed, as I have learned more about political economy I have come to believe this more and more about all the broken institutions in the world. American democracy has its deep flaws because politicians like it that way. China’s government is corrupt because that corruption is profitable for many of China’s leaders. Et cetera.)

I know economics best, so that is where I will focus; but most of what I’m saying here would also apply to other social sciences such as sociology and psychology as well. (Indeed it was psychology that published Daryl Bem.)

Rogoff and Reinhart’s 2010 article “Growth in a Time of Debt”, which was a weak correlation-based argument to begin with, was later revealed (by an intrepid grad student! His name is Thomas Herndon.) to be based upon deep, fundamental errors. Yet the article remains published, without any notice of retraction or correction, in the American Economic Review, probably the most prestigious journal in economics (and undeniably in the vaunted “Top Five”). And the paper itself was widely used by governments around the world to justify massive austerity policies—which backfired with catastrophic consequences.

Why wouldn’t the AER remove the article from their website? Or issue a retraction? Or at least add a note on the page explaining the errors? If their primary concern were scientific truth, they would have done something like this. Their failure to do so is a silence that speaks volumes, a hound that didn’t bark in the night.

It’s rational, if incredibly selfish, for Rogoff and Reinhart themselves to not want a retraction. It was one of their most widely-cited papers. But why wouldn’t AER’s editors want to retract a paper that had been so embarrassingly debunked?

And so I came to realize: These are all people who have succeeded in the current system. Their work is valued, respected, and supported by the system of scientific publishing as it stands. If we were to radically change that system, as we would necessarily have to do in order to re-align incentives toward scientific truth, they would stand to lose, because they would suddenly be competing against other people who are not as good at satisfying the magical 0.05, but are in fact at least as good—perhaps even better—actual scientists than they are.

I know how they would respond to this criticism: I’m someone who hasn’t succeeded in the current system, so I’m biased against it. This is true, to some extent. Indeed, I take it quite seriously, because while tenured professors stand to lose prestige, they can’t really lose their jobs even if there is a sudden flood of far superior research. So in directly economic terms, we would expect the bias against the current system among grad students, adjuncts, and assistant professors to be larger than the bias in favor of the current system among tenured professors and prestigious researchers.

Yet there are other motives aside from money: Norms and social status are among the most powerful motivations human beings have, and these biases are far stronger in favor of the current system—even among grad students and junior faculty. Grad school is many things, some good, some bad; but one of them is a ritual gauntlet that indoctrinates you into the belief that working in academia is the One True Path, without which your life is a failure. If your claim is that grad students are upset at the current system because we overestimate our own qualifications and are feeling sour grapes, you need to explain our prevalence of Impostor Syndrome. By and large, grad students don’t overestimate our abilities—we underestimate them. If we think we’re as good at this as you are, that probably means we’re better. Indeed I have little doubt that Thomas Herndon is a better economist than Kenneth Rogoff will ever be.

I have additional evidence that insider bias is important here: When Paul Romer—Nobel laureate—left academia he published an utterly scathing criticism of the state of academic macroeconomics. That is, once he had escaped the incentives toward insider bias, he turned against the entire field.

Romer pulls absolutely no punches: He literally compares the standard methods of DSGE models to “phlogiston” and “gremlins”. And the paper is worth reading, because it’s obviously entirely correct. He pulls no punches and every single one lands on target. It’s also a pretty fun read, at least if you have the background knowledge to appreciate the dry in-jokes. (Much like “Transgressing the Boundaries: Toward a Transformative Hermeneutics of Quantum Gravity.” I still laugh out loud every time I read the phrase “hegemonic Zermelo-Frankel axioms”, though I realize most people would be utterly nonplussed. For the unitiated, these are the Zermelo-Frankel axioms. Can’t you just see the colonialist imperialism in sentences like “\forall x \forall y (\forall z, z \in x \iff z \in y) \implies x = y”?)

In other words, the Upton Sinclair Principle seems to be applying here: “It is difficult to get a man to understand something when his salary depends upon not understanding it.” The people with the most power to change the system of scientific publishing are journal editors and prestigious researchers, and they are the people for whom the current system is running quite swimmingly.

It’s not that good science can’t succeed in the current system—it often does. In fact, I’m willing to grant that it almost always does, eventually. When the evidence has mounted for long enough and the most adamant of the ancien regime finally retire or die, then, at last, the paradigm will shift. But this process takes literally decades longer than it should. In principle, a wrong theory can be invalidated by a single rigorous experiment. In practice, it generally takes about 30 years of experiments, most of which don’t get published, until the powers that be finally give in.

This delay has serious consequences. It means that many of the researchers working on the forefront of a new paradigm—precisely the people that the scientific community ought to be supporting most—will suffer from being unable to publish their work, get grant funding, or even get hired in the first place. It means that not only will good science take too long to win, but that much good science will never get done at all, because the people who wanted to do it couldn’t find the support they needed to do so. This means that the delay is in fact much longer than it appears: Because it took 30 years for one good idea to take hold, all the other good ideas that would have sprung from it in that time will be lost, at least until someone in the future comes up with them.

I don’t think I’ll ever forget it: At the AEA conference a few years back, I went to a luncheon celebrating Richard Thaler, one of the founders of behavioral economics, whom I regard as one of the top 5 greatest economists of the 20th century (I’m thinking something like, “Keynes > Nash > Thaler > Ramsey > Schelling”). Yes, now he is being rightfully recognized for his seminal work; he won a Nobel, and he has an endowed chair at Chicago, and he got an AEA luncheon in his honor among many other accolades. But it was not always so. Someone speaking at the luncheon offhandedly remarked something like, “Did we think Richard would win a Nobel? Honestly most of us weren’t sure he’d get tenure.” Most of the room laughed; I had to resist the urge to scream. If Richard Thaler wasn’t certain to get tenure, then the entire system is broken. This would be like finding out that Erwin Schrodinger or Niels Bohr wasn’t sure he would get tenure in physics.

A. Gary Schilling, a renowned Wall Street economist (read: One Who Has Turned to the Dark Side), once remarked (the quote is often falsely attributed to Keynes): “markets can remain irrational a lot longer than you and I can remain solvent.” In the same spirit, I would say this: the scientific community can remain wrong a lot longer than you and I can extend our graduate fellowships and tenure clocks.

Is privacy dead?

PNRJ futurism, market failure, public policy , , , , , , , , , , , , , ,

May 9 JDN 2459342

It is the year 2021, and while we don’t yet have flying cars or human-level artificial intelligence, our society is in many ways quite similar to what cyberpunk fiction predicted it would be. We are constantly connected to the Internet, even linking devices in our homes to the Web when that is largely pointless or actively dangerous. Oligopolies of fewer and fewer multinational corporations that are more and more powerful have taken over most of our markets, from mass media to computer operating systems, from finance to retail.

One of the many dire predictions of cyberpunk fiction is that constant Internet connectivity will effectively destroy privacy. There is reason to think that this is in fact happening: We have televisions that listen to our conversations, webcams that can be hacked, sometimes invisibly, and the operating system that runs the majority of personal and business computers is built around constantly tracking its users.

The concentration of oligopoly power and the decline of privacy are not unconnected. It’s the oligopoly power of corporations like Microsoft and Google and Facebook that allows them to present us with absurdly long and virtually unreadable license agreements as an ultimatum: “Sign away your rights, or else you can’t use our product. And remember, we’re the only ones who make this product and it’s increasingly necessary for your basic functioning in society!” This is of course exactly as cyberpunk fiction warned us it would be.

Giving up our private information to a handful of powerful corporations would be bad enough if that information were securely held only by them. But it isn’t. There have been dozens of major data breaches of major corporations, and there will surely be many more. In an average year, several billion data records are exposed through data breaches. Each person produces many data records, so it’s difficult to say exactly how many people have had their data stolen; but it isn’t implausible to say that if you are highly active on the Internet, at least some of your data has been stolen in one breach or another. Corporations have strong incentives to collect and use your data—data brokerage is a hundred-billion-dollar industry—but very weak incentives to protect it from prying eyes. The FTC does impose fines for negligence in the event of a major data breach, but as usual the scale of the fines simply doesn’t match the scale of the corporations responsible. $575 million sounds like a lot of money, but for a corporation with $28 billion in assets it’s a slap on the wrist. It would be equivalent to fining me about $500 (about what I’d get for driving without a passenger in the carpool lane). Yeah, I’d feel that; it would be unpleasant and inconvenient. But it’s certainly not going to change my life. And typically these fines only impact shareholders, and don’t even pass through to the people who made the decisions: The man who was CEO of Equifax when it suffered its catastrophic data breach retired with a $90 million pension.

While most people seem either blissfully unaware or fatalistically resigned to its inevitability, a few people have praised the trend of reduced privacy, usually by claiming that it will result in increased transparency. Yet, ironically, a world with less privacy can actually mean a world with less transparency as well: When you don’t know what information you reveal will be stolen and misused, you will constantly endeavor to protect all your information, even things that you would normally not hesitate to reveal. When even your face and name can be used to track you, you’ll be more hesitant to reveal them. Cyberpunk fiction predicted this too: Most characters in cyberpunk stories are known by their hacker handles, not their real given names.

There is some good news, however. People are finally beginning to notice that they have been pressured into giving away their privacy rights, and demanding to get them back. The United Nations has recently passed resolutions defending digital privacy, governments have taken action against the worst privacy violations with increasing frequency, courts are ruling in favor of stricter protections, think tanks are demanding stricter regulations, and even corporate policies are beginning to change. While the major corporations all want to take your data, there are now many smaller businesses and nonprofit organizations that will sell you tools to help protect it.

This does not mean we can be complacent: The war is far from won. But it does mean that there is some hope left; we don’t simply have to surrender and accept a world where anyone with enough money can know whatever they want about anyone else. We don’t need to accept what the CEO of Sun Microsystems infamously said: “You have zero privacy anyway. Get over it.”

I think the best answer to the decline of privacy is to address the underlying incentives that make it so lucrative. Why is data brokering such a profitable industry? Because ad targeting is such a profitable industry. So profitable, indeed, that huge corporations like Facebook and Google make almost all of their money that way, and the useful services they provide to users are offered for free simply as an enticement to get them to look at more targeted advertising.

Selling advertising is hardly new—we’ve been doing it for literally millennia, as Roman gladiators were often paid to hawk products. It has been the primary source of revenue for most forms of media, from newspapers to radio stations to TV networks, since those media have existed. What has changed is that ad targeting is now a lucrative business: In the 1850s, that newspaper being sold by barking boys on the street likely had ads in it, but they were the same ads for every single reader. Now when you log in to CNN.com or nytimes.com, the ads on that page are specific only to you, based on any information that these media giants have been able to glean from your past Internet activity. If you do try to protect your online privacy with various tools, a quick-and-dirty way to check if it’s working is to see if websites give you ads for things you know you’d never buy.

In fact, I consider it a very welcome recent development that video streaming is finally a way to watch TV shows by actually paying for them instead of having someone else pay for the right to shove ads in my face. I can’t remember the last time I heard a TV ad jingle, and I’m very happy about that fact. Having to spend 15 minutes of each hour of watching TV to watch commercials may not seem so bad—in fact, many people may feel that they’d rather do that than pay the money to avoid it. But think about it this way: If it weren’t worth at least that much to the corporations buying those ads, they wouldn’t do it. And if a corporation expects to get $X from you that you wouldn’t have otherwise paid, that means they’re getting you to spend that much that you otherwise wouldn’t have—meaning that they’re getting you to buy something you didn’t need. Perhaps it’s better after all to spend that $X on getting entertainment that doesn’t try to get you to buy things you don’t need.

Indeed, I think there is an opportunity to restructure the whole Internet this way. What we need is a software company—maybe a nonprofit organization, maybe a for-profit business—that is set up to let us make micropayments for online content in lieu of having our data collected or being force-fed advertising.

How big would these payments need to be? Well, Facebook has about 2.8 billion users and takes in revenue of about $80 billion per year, so the average user would have to pay about $29 a year for the use of Facebook, Instagram, and WhatsApp. That’s about $2.50 per month, or $0.08 per day.

The New York Times is already losing its ad-supported business model; less than $400 million of its $1.8 billion revenue last year was from ads, the rest being primarily from subscriptions. But smaller media outlets have a much harder time gaining subscribers; often people just want to read a single article and aren’t willing to pay for a whole month or year of the periodical. If we could somehow charge for individual articles, how much would we have to charge? Well, a typical webpage has an ad clickthrough rate of 1%, while a typical cost-per-click rate is about $0.60, so ads on the average webpage makes its owners a whopping $0.006. That’s not even a single cent. So if this new micropayment system allowed you to pay one cent to read an article without the annoyance of ads or the pressure to buy something you don’t need, would you pay it? I would. In fact, I’d pay five cents. They could quintuple their revenue!

The main problem is that we currently don’t have an efficient way to make payments that small. Processing a credit card transaction typically costs at least $0.05, so a five-cent transaction would yield literally zero revenue for the website. I’d have to pay ten cents to give the website five, and I admit I might not always want to do that—I’d also definitely be uncomfortable with half the money going to credit card companies.

So what’s needed is software to bundle the payments at each end: In a single credit card transaction, you add say $20 of tokens to an account. Each token might be worth $0.01, or even less if we want. These tokens can then be spent at participating websites to pay for access. The websites can then collect all the tokens they’ve received over say a month, bundle them together, and sell them back to the company that originally sold them to you, for slightly less than what you paid for them. These bundled transactions could actually be quite large in many cases—thousands or millions of dollars—and thus processing fees would be a very small fraction. For smaller sites there could be a minimum amount of tokens they must collect—perhaps also $20 or so—before they can sell them back. Note that if you’ve bought $20 in tokens and you are paying $0.05 per view, you can read 400 articles before you run out of tokens and have to buy more. And they don’t all have to be from the same source, as they would with a traditional subscription; you can read articles from any outlet that participates in the token system.

There are a number of technical issues to be resolved here: How to keep the tokens secure, how to guarantee that once a user purchases access to an article they will continue to have access to it, ideally even if they clear their cache, delete all cookies, or login from another computer. I can’t literally set up this website today, and even if I could, I don’t know how I’d attract a critical mass of both users and participating websites (it’s a major network externality problem). But it seems well within the purview of what the tech industry has done in the past—indeed, it’s quite comparable to the impressive (and unsettling) infrastructure that has been laid down to support ad-targeting and data brokerage.

How would such a system help protect privacy? If micropayments for content became the dominant model of funding online content, most people wouldn’t spend much time looking at online ads, and ad targeting would be much less profitable. Data brokerage, in turn, would become less lucrative, because there would be fewer ways to use that data to make profits. With the incentives to take our data thus reduced, it would be easier to enforce regulations protecting our privacy. Those fines might actually be enough to make it no longer worth the while to take sensitive data, and corporations might stop pressuring people to give it up.

No, privacy isn’t dead. But it’s dying. If we want to save it, we have a lot of work to do.

Economic Possibilities for Ourselves

PNRJ core principles, critique of neoclassical economics, development economics, ethics, futurism, inequality, public policy , , , , , , ,

May 2 JDN 2459335

In 1930, John Maynard Keynes wrote one of the greatest essays ever written on economics, “Economic Possibilities for our Grandchildren.” You can read it here.


In that essay he wrote:

“I would predict that the standard of life in progressive countries one hundred years hence will be between four and eight times as high as it is.”

US population in 1930: 122 million; US real GDP in 1930: $1.1 trillion. Per-capita GDP: $9,000

US population in 2020: 329 million; US real GDP in 2020: $18.4 trillion. Per-capita GDP: $56,000

That’s a factor of 6. Keynes said 4 to 8; that makes his estimate almost perfect. We aren’t just inside his error bar, we’re in the center of it. If anything he was under-confident. Of course we still have 10 years left before a full century has passed: At a growth rate of 1% in per-capita GDP, that will make the ratio closer to 7—still well within his confidence interval.

I’d like to take a moment to marvel at how good this estimate is. Keynes predicted the growth rate of the entire US economy one hundred years in the future to within plus or minus 30%, and got it right.

With this in mind, it’s quite astonishing what Keynes got wrong in his essay.


The point of the essay is that what Keynes calls “the economic problem” will soon be solved. By “the economic problem”, he means the scarcity of resources that makes it impossible for everyone in the world to make a decent living. Keynes predicts that by 2030—so just a few years from now—humanity will have effectively solved this problem, and we will live in a world where everyone can live comfortably with adequate basic necessities like shelter, food, water, clothing, and medicine.

He laments that with the dramatically higher productivity that technological advancement brings, we will be thrust into a life of leisure that we are unprepared to handle. Evolved for a world of scarcity, we built our culture around scarcity, and we may not know what to do with ourselves in a world of abundance.

Keynes sounds his most naive when he imagines that we would spread out our work over more workers each with fewer hours:

“For many ages to come the old Adam will be so strong in us that everybody will need to do some work if he is to be contented. We shall do more things for ourselves than is usual with the rich today, only too glad to have small duties and tasks and routines. But beyond this, we shall endeavour to spread the bread thin on the butter-to make what work there is still to be done to be as widely shared as possible. Three-hour shifts or a fifteen-hour week may put off the problem for a great while. For three hours a day is quite enough to satisfy the old Adam in most of us!”

Plainly that is nothing like what happened. Americans do on average work fewer hours today than we did in the past, but not by anything like this much: average annual hours fell from about 1,900 in 1950 to about 1,700 today. Where Keynes was predicting a drop of 60%, the actual drop was only about 10%.

Here’s another change Keynes predicted that I wish we’d made, but we certainly haven’t:

“When the accumulation of wealth is no longer of high social importance, there will be great changes in the code of morals. We shall be able to rid ourselves of many of the pseudo-moral principles which have hag-ridden us for two hundred years, by which we have exalted some of the most distasteful of human qualities into the position of the highest virtues. We shall be able to afford to dare to assess the money-motive at its true value. The love of money as a possession—as distinguished from the love of money as a means to the enjoyments and realities of life—will be recognised for what it is, a somewhat disgusting morbidity, one of those semicriminal, semi-pathological propensities which one hands over with a shudder to the specialists in mental disease.”

Sadly, people still idolize Jeff Bezos and Elon Musk just as much their forebears idolized Henry Ford or Andrew Carnegie. And really there’s nothing semi- about it: The acquisition of billions of dollars by exploiting others is clearly indicative of narcissism if not psychopathy.

It’s not that we couldn’t have made the world that Keynes imagined. There’s plenty of stuff—his forecast for our per-capita GDP was impeccable. But when we automated away all of the most important work, Keynes thought we would turn to lives of leisure, exploring art, music, literature, film, games, sports. But instead we did something he did not anticipate: We invented new kinds of work.

This would be fine if the new work we invented is genuinely productive; and some of it is, no doubt. Keynes could not have anticipated the emergence of 3D graphics designers, smartphone engineers, or web developers, but these jobs do genuinely productive and beneficial work that makes use of our extraordinary new technologies.

But think for a moment about Facebook and Google, now two of the world’s largest and most powerful corporations. What do they sell? Think carefully! Facebook doesn’t sell social media. Google doesn’t sell search algorithms. Those are services they provide as platforms for what they actually sell: Advertising.

That is, some of the most profitable, powerful corporations in the world today make all of their revenue entirely from trying to persuade people to buy things they don’t actually need. The actual benefits they provide to humanity are sort of incidental; they exist to provide an incentive to look at the ads.

Paul Krugman often talks about Solow’s famous remark that “computers showed up everywhere but the productivity statistics”; aggregate productivity growth has, if anything, been slower in the last 40 years than in the previous 40.

But this aggregate is a very foolish measure. It’s averaging together all sorts of work into one big lump.

If you look specifically at manufacturing output per worker—the sort of thing you’d actually expect to increase due to automation—it has in fact increased, at breakneck speed: The average American worker produced four times as much output per hour in 2000 as in 1950.

The problem is that instead of splitting up the manufacturing work to give people free time, we moved them all into services—which have not meaningfully increased their productivity in the same period. The average growth rate in multifactor productivity in the service industries since the 1970s has been a measly 0.2% per year, meaning that our total output per worker in service industries is only 10% higher than it was in 1970.

While our population is more than double what it was in 1950, our total manufacturing employment is now less than it was in 1950. Our employment in services is four times what it was in 1950. We moved everyone out of the sector that actually got more productive and stuffed them into the sector that didn’t.

This is why the productivity statistics are misleading. Suppose we had 100 workers, and 2 industries.

Initially, in manufacturing, each worker can produce goods worth $20 per hour. In services, each worker can only produce services worth $10 per hour. 50 workers work in each industry, so average productivity is (50*$20+50*$10)/100 = $15 per hour.

Then, after new technological advances, productivity in manufacturing increases to $80 per hour, but people don’t actually want to spend that much on manufactured good. So 30 workers from manufacturing move over to services, which still only produce $10 per hour. Now total productivity is (20*$80+80*$10)/100 = $24 per hour.

Overall productivity now appears to only have risen 60% over that time period (in 50 years this would be 0.9% per year), but in fact it rose 300% in manufacturing (2.2% per year) but 0% in services. What looks like anemic growth in productivity is actually a shift of workers out of the productive sectors into the unproductive sectors.

Keynes imagined that once we had made manufacturing so efficient that everyone could have whatever appliances they like, we’d give them the chance to live their lives without having to work. Instead, we found jobs for them—in large part, jobs that didn’t need doing.

Advertising is the clearest example: It’s almost pure rent-seeking, and if it were suddenly deleted from the universe almost everyone would actually be better off.

But there are plenty of other jobs, what the late David Graeber called “bullshit jobs”, that have the same character: Sales, consulting, brokering, lobbying, public relations, and most of what goes on in management, law and finance. Graeber had a silly theory that we did this on purpose either to make the rich feel important or to keep people working so they wouldn’t question the existing system. The real explanation is much simpler: These jobs are rent-seeking. They do make profits for the corporations that employ them, but they contribute little or nothing to human society as a whole.

I’m not sure how surprised Keynes would be by this outcome. In parts of the essay he acknowledges that the attitude which considers work a virtue and idleness a vice is well-entrenched in our society, and seems to recognize that the transition to a world where most people work very little is one that would be widely resisted. But his vision of what the world would be like in the early 21st century does now seem to be overly optimistic, not in its forecasts of our productivity and output—which, I really cannot stress enough, were absolutely spot on—but in its predictions of how society would adapt to that abundance.

It seems that most people still aren’t quite ready to give up on a world built around jobs. Most people still think of a job as the primary purpose of an adult’s life, that someone who isn’t working for an employer is somehow wasting their life and free-riding on everyone else.

In some sense this is perhaps true; but why is it more true of someone living on unemployment than of someone who works in marketing, or stock brokering, or lobbying, or corporate law? At least people living on unemployment aren’t actively making the world worse. And since unemployment pays less than all but the lowest-paying jobs, the amount of resources that are taken up by people on unemployment is considerably less than the rents which are appropriated by industries like consulting and finance.

Indeed, whenever you encounter a billionaire, there’s one thing you know for certain: They are very good at rent-seeking. Whether by monopoly power, or exploitation, or outright corruption, all the ways it’s possible to make a billion dollars are forms of rent-seeking. And this is for a very simple and obvious reason: No one can possibly work so hard and be so productive as to actually earn a billion dollars. No one’s real opportunity cost is actually that high—and the difference between income and real opportunity cost is by definition economic rent.

If we’re truly concerned about free-riding on other people’s work, we should really be thinking in terms of the generations of scientists and engineers before us who made all of this technology possible, as well as the institutions and infrastructure that have bequeathed us a secure stock of capital. You didn’t build that applies to all of us: Even if all the necessary raw materials were present, none of us could build a smartphone by hand alone on a desert island. Most of us couldn’t even sew a pair of pants or build a house—though that is at least the sort of thing that it’s possible to do by hand.

But in fact I think free-riding on our forebears is a perfectly acceptable activity. I am glad we do it, and I hope our descendants do it to us. I want to build a future where life is better than it is now; I want to leave the world better than we found it. If there were some way to inter-temporally transfer income back to the past, I suppose maybe we ought to do so—but as far as we know, there isn’t. Nothing can change the fact that most people were desperately poor for most of human history.

What we now have the power to decide is what will happen to people in the future: Will we continue to maintain this system where our wealth is decided by our willingness to work for corporations, at jobs that may be utterly unnecessary or even actively detrimental? Or will we build a new system, one where everyone gets the chance to share in the abundance that our ancestors have given us and each person gets the chance to live their life in the way that they find most meaningful?

Keynes imagined a bright future for the generation of his grandchildren. We now live in that generation, and we have precisely the abundance of resources he predicted we would. Can we now find a way to build that bright future?