Fake skepticism

Jun 3 JDN 2458273

“You trust the mainstream media?” “Wake up, sheeple!” “Don’t listen to what so-called scientists say; do your own research!”

These kinds of statements have become quite ubiquitous lately (though perhaps the attitudes were always there, and we only began to hear them because of the Internet and social media), and are often used to defend the most extreme and bizarre conspiracy theories, from moon-landing denial to flat Earth. The amazing thing about these kinds of statements is that they can be used to defend literally anything, as long as you can find some source with less than 100% credibility that disagrees with it. (And what source has 100% credibility?)

And that, I think, should tell you something. An argument that can prove anything is an argument that proves nothing.

Reversed stupidity is not intelligence. The fact that the mainstream media, or the government, or the pharmaceutical industry, or the oil industry, or even gangsters, fanatics, or terrorists believes something does not make it less likely to be true.

In fact, the vast majority of beliefs held by basically everyone—including the most fanatical extremists—are true. I could list such consensus true beliefs for hours: “The sky is blue.” “2+2=4.” “Ice is colder than fire.”

Even if a belief is characteristic of a specifically evil or corrupt organization, that does not necessarily make it false (though it usually is evidence of falsehood in a Bayesian sense). If only terrible people belief X, then maybe you shouldn’t believe X. But if both good and bad people believe X, the fact that bad people believe X really shouldn’t matter to you.

People who use this kind of argument often present themselves as being “skeptics”. They imagine that they have seen through the veil of deception that blinds others.

In fact, quite the opposite is the case: This is fake skepticism. These people are not uniquely skeptical; they are uniquely credulous. If you think the Earth is flat because you don’t trust the mainstream scientific community, that means you do trust someone far less credible than the mainstream scientific community.

Real skepticism is difficult. It requires concerted effort and investigation, and typically takes years. To really seriously challenge the expert consensus in a field, you need to become an expert in that field. Ideally, you should get a graduate degree in that field and actually start publishing your heterodox views. Failing that, you should at least be spending hundreds or thousands of hours doing independent research. If you are unwilling or unable to do that, you are not qualified to assess the validity of the expert consensus.

This does not mean the expert consensus is always right—remarkably often, it isn’t. But it means you aren’t allowed to say it’s wrong, because you don’t know enough to assess that.

This is not elitism. This is not an argument from authority. This is a basic respect for the effort and knowledge that experts spend their lives acquiring.

People don’t like being told that they are not as smart as other people—even though, with any variation at all, that’s got to be true for a certain proportion of people. But I’m not even saying experts are smarter than you. I’m saying they know more about their particular field of expertise.

Do you walk up to construction workers on the street and critique how they lay concrete? When you step on an airplane, do you explain to the captain how to read an altimeter? When you hire a plumber, do you insist on using the snake yourself?

Probably not. And why not? Because you know these people have training; they do this for a living. Yeah, well, scientists do this for a living too—and our training is much longer. To be a plumber, you need a high school diploma and an apprenticeship that usually lasts about four years. To be a scientist, you need a PhD, which means four years of college plus an additional five or six years of graduate school.

To be clear, I’m not saying you should listen to experts speaking outside their expertise. Some of the most idiotic, arrogant things ever said by human beings have been said by physicists opining on biology or economists ranting about politics. Even within a field, some people have such narrow expertise that you can’t really trust them even on things that seem related—like macroeconomists with idiotic views on trade, or ecologists who clearly don’t understand evolution.

This is also why one of the great challenges of being a good interdisciplinary scientist is actually obtaining enough expertise in both fields you’re working in; it isn’t literally twice the work (since there is overlap—or you wouldn’t be doing it—and you do specialize in particular interdisciplinary subfields), but it’s definitely more work, and there are definitely a lot of people on each side of the fence who may never take you seriously no matter what you do.

How do you tell who to trust? This is why I keep coming back to the matter of expert consensus. The world is much too complicated for anyone, much less everyone, to understand it all. We must be willing to trust the work of others. The best way we have found to decide which work is trustworthy is by the norms and institutions of the scientific community itself. Since 97% of climatologists say that climate change is caused by humans, they’re probably right. Since 99% of biologists believe humans evolved by natural selection, that’s probably what happened. Since 87% of economists oppose tariffs, tariffs probably aren’t a good idea.

Can we be certain that the consensus is right? No. There is precious little in this universe that we can be certain about. But as in any game of chance, you need to play the best odds, and my money will always be on the scientific consensus.

What good are macroeconomic models? How could they be better?

Dec 11, JDN 2457734

One thing that I don’t think most people know, but which immediately obvious to any student of economics at the college level or above, is that there is a veritable cornucopia of different macroeconomic models. There are growth models (the Solow model, the Harrod-Domar model, the Ramsey model), monetary policy models (IS-LM, aggregate demand-aggregate supply), trade models (the Mundell-Fleming model, the Heckscher-Ohlin model), large-scale computational models (dynamic stochastic general equilibrium, agent-based computational economics), and I could go on.

This immediately raises the question: What are all these models for? What good are they?

A cynical view might be that they aren’t useful at all, that this is all false mathematical precision which makes economics persuasive without making it accurate or useful. And with such a proliferation of models and contradictory conclusions, I can see why such a view would be tempting.

But many of these models are useful, at least in certain circumstances. They aren’t completely arbitrary. Indeed, one of the litmus tests of the last decade has been how well the models held up against the events of the Great Recession and following Second Depression. The Keynesian and cognitive/behavioral models did rather well, albeit with significant gaps and flaws. The Monetarist, Real Business Cycle, and most other neoclassical models failed miserably, as did Austrian and Marxist notions so fluid and ill-defined that I’m not sure they deserve to even be called “models”. So there is at least some empirical basis for deciding what assumptions we should be willing to use in our models. Yet even if we restrict ourselves to Keynesian and cognitive/behavioral models, there are still a great many to choose from, which often yield inconsistent results.

So let’s compare with a science that is uncontroversially successful: Physics. How do mathematical models in physics compare with mathematical models in economics?

Well, there are still a lot of models, first of all. There’s the Bohr model, the Schrodinger equation, the Dirac equation, Newtonian mechanics, Lagrangian mechanics, Bohmian mechanics, Maxwell’s equations, Faraday’s law, Coulomb’s law, the Einstein field equations, the Minkowsky metric, the Schwarzschild metric, the Rindler metric, Feynman-Wheeler theory, the Navier-Stokes equations, and so on. So a cornucopia of models is not inherently a bad thing.

Yet, there is something about physics models that makes them more reliable than economics models.

Partly it is that the systems physicists study are literally two dozen orders of magnitude or more smaller and simpler than the systems economists study. Their task is inherently easier than ours.

But it’s not just that; their models aren’t just simpler—actually they often aren’t. The Navier-Stokes equations are a lot more complicated than the Solow model. They’re also clearly a lot more accurate.

The feature that models in physics seem to have that models in economics do not is something we might call nesting, or maybe consistency. Models in physics don’t come out of nowhere; you can’t just make up your own new model based on whatever assumptions you like and then start using it—which you very much can do in economics. Models in physics are required to fit consistently with one another, and usually inside one another, in the following sense:

The Dirac equation strictly generalizes the Schrodinger equation, which strictly generalizes the Bohr model. Bohmian mechanics is consistent with quantum mechanics, which strictly generalizes Lagrangian mechanics, which generalizes Newtonian mechanics. The Einstein field equations are consistent with Maxwell’s equations and strictly generalize the Minkowsky, Schwarzschild, and Rindler metrics. Maxwell’s equations strictly generalize Faraday’s law and Coulomb’s law.
In other words, there are a small number of canonical models—the Dirac equation, Maxwell’s equations and the Einstein field equation, essentially—inside which all other models are nested. The simpler models like Coulomb’s law and Newtonian mechanics are not contradictory with these canonical models; they are contained within them, subject to certain constraints (such as macroscopic systems far below the speed of light).

This is something I wish more people understood (I blame Kuhn for confusing everyone about what paradigm shifts really entail); Einstein did not overturn Newton’s laws, he extended them to domains where they previously had failed to apply.

This is why it is sensible to say that certain theories in physics are true; they are the canonical models that underlie all known phenomena. Other models can be useful, but not because we are relativists about truth or anything like that; Newtonian physics is a very good approximation of the Einstein field equations at the scale of many phenomena we care about, and is also much more mathematically tractable. If we ever find ourselves in situations where Newton’s equations no longer apply—near a black hole, traveling near the speed of light—then we know we can fall back on the more complex canonical model; but when the simpler model works, there’s no reason not to use it.

There are still very serious gaps in the knowledge of physics; in particular, there is a fundamental gulf between quantum mechanics and the Einstein field equations that has been unresolved for decades. A solution to this “quantum gravity problem” would be essentially a guaranteed Nobel Prize. So even a canonical model can be flawed, and can be extended or improved upon; the result is then a new canonical model which we now regard as our best approximation to truth.

Yet the contrast with economics is still quite clear. We don’t have one or two or even ten canonical models to refer back to. We can’t say that the Solow model is an approximation of some greater canonical model that works for these purposes—because we don’t have that greater canonical model. We can’t say that agent-based computational economics is approximately right, because we have nothing to approximate it to.

I went into economics thinking that neoclassical economics needed a new paradigm. I have now realized something much more alarming: Neoclassical economics doesn’t really have a paradigm. Or if it does, it’s a very informal paradigm, one that is expressed by the arbitrary judgments of journal editors, not one that can be written down as a series of equations. We assume perfect rationality, except when we don’t. We assume constant returns to scale, except when that doesn’t work. We assume perfect competition, except when that doesn’t get the results we wanted. The agents in our models are infinite identical psychopaths, and they are exactly as rational as needed for the conclusion I want.

This is quite likely why there is so much disagreement within economics. When you can permute the parameters however you like with no regard to a canonical model, you can more or less draw whatever conclusion you want, especially if you aren’t tightly bound to empirical evidence. I know a great many economists who are sure that raising minimum wage results in large disemployment effects, because the models they believe in say that it must, even though the empirical evidence has been quite clear that these effects are small if they are present at all. If we had a canonical model of employment that we could calibrate to the empirical evidence, that couldn’t happen anymore; there would be a coefficient I could point to that would refute their argument. But when every new paper comes with a new model, there’s no way to do that; one set of assumptions is as good as another.

Indeed, as I mentioned in an earlier post, a remarkable number of economists seem to embrace this relativism. “There is no true model.” they say; “We do what is useful.” Recently I encountered a book by the eminent economist Deirdre McCloskey which, though I confess I haven’t read it in its entirety, appears to be trying to argue that economics is just a meaningless language game that doesn’t have or need to have any connection with actual reality. (If any of you have read it and think I’m misunderstanding it, please explain. As it is I haven’t bought it for a reason any economist should respect: I am disinclined to incentivize such writing.)

Creating such a canonical model would no doubt be extremely difficult. Indeed, it is a task that would require the combined efforts of hundreds of researchers and could take generations to achieve. The true equations that underlie the economy could be totally intractable even for our best computers. But quantum mechanics wasn’t built in a day, either. The key challenge here lies in convincing economists that this is something worth doing—that if we really want to be taken seriously as scientists we need to start acting like them. Scientists believe in truth, and they are trying to find it out. While not immune to tribalism or ideology or other human limitations, they resist them as fiercely as possible, always turning back to the evidence above all else. And in their combined strivings, they attempt to build a grand edifice, a universal theory to stand the test of time—a canonical model.

The facts will not speak for themselves, so we must speak for them

August 3, JDN 2457604

I finally began to understand the bizarre and terrifying phenomenon that is the Donald Trump Presidential nomination when I watched this John Oliver episode:


These lines in particular, near the end, finally helped me put it all together:

What is truly revealing is his implication that believing something to be true is the same as it being true. Because if anything, that was the theme of the Republican Convention this week; it was a four-day exercise in emphasizing feelings over facts.

The facts against Donald Trump are absolutely overwhelming. He is not even a competent business man, just a spectacularly manipulative one—and even then, it’s not clear he made any more money than he would have just keeping his inheritance in a diversified stock portfolio. His casinos were too fraudulent for Atlantic City. His university was fraudulent. He has the worst honesty rating Politifact has ever given a candidate. (Bernie Sanders, Barack Obama, and Hillary Clinton are statistically tied for some of the best.)

More importantly, almost every policy he has proposed or even suggested is terrible, and several of them could be truly catastrophic.

Let’s start with economic policy: His trade policy would set back decades of globalization and dramatically increase global poverty, while doing little or nothing to expand employment in the US, especially if it sparks a trade war. His fiscal policy would permanently balloon the deficit by giving one of the largest tax breaks to the rich in history. His infamous wall would probably cost about as much as the federal government currently spends on all basic scientific research combined, and his only proposal for funding it fundamentally misunderstands how remittances and trade deficits work. He doesn’t believe in climate change, and would roll back what little progress we have made at reducing carbon emissions, thereby endangering millions of lives. He could very likely cause a global economic collapse comparable to the Great Depression.

His social policy is equally terrible: He has proposed criminalizing abortion, (in express violation of Roe v. Wade) which even many pro-life people find too extreme. He wants to deport all Muslims and ban Muslims from entering, which not just a direct First Amendment violation but also literally involves jackbooted soldiers breaking into the homes of law-abiding US citizens to kidnap them and take them out of the country. He wants to deport 11 million undocumented immigrants, the largest deportation in US history.

Yet it is in foreign policy above all that Trump is truly horrific. He has explicitly endorsed targeting the families of terrorists, which is a war crime (though not as bad as what Ted Cruz wanted to do, which is carpet-bombing cities). Speaking of war crimes, he thinks our torture policy wasn’t severe enough, and doesn’t even care if it is ineffective. He has made the literally mercantilist assertion that the purpose of military alliances is to create trade surpluses, and if European countries will not provide us with trade surpluses (read: tribute), he will no longer commit to defending them, thereby undermining decades of global stability that is founded upon America’s unwavering commitment to defend our allies. And worst of all, he will not rule out the first-strike deployment of nuclear weapons.

I want you to understand that I am not exaggerating when I say that a Donald Trump Presidency carries a nontrivial risk of triggering global nuclear war. Will this probably happen? No. It has a probability of perhaps 1%. But a 1% chance of a billion deaths is not a risk anyone should be prepared to take.


All of these facts scream at us that Donald Trump would be a catastrophe for America and the world. Why, then, are so many people voting for him? Why do our best election forecasts give him a good chance of winning the election?

Because facts don’t speak for themselves.

This is how the left, especially the center-left, has dropped the ball in recent decades. We joke that reality has a liberal bias, because so many of the facts are so obviously on our side. But meanwhile the right wing has nodded and laughed, even mockingly called us the “reality-based community”, because they know how to manipulate feelings.

Donald Trump has essentially no other skills—but he has that one, and it is enough. He knows how to fan the flames of anger and hatred and point them at his chosen targets. He knows how to rally people behind meaningless slogans like “Make America Great Again” and convince them that he has their best interests at heart.

Indeed, Trump’s persuasiveness is one of his many parallels with Adolf Hitler; I am not yet prepared to accuse Donald Trump of seeking genocide, yet at the same time I am not yet willing to put it past him. I don’t think it would take much of a spark at this point to trigger a conflagration of hatred that launches a genocide against Muslims in the United States, and I don’t trust Trump not to light such a spark.

Meanwhile, liberal policy wonks are looking on in horror, wondering how anyone could be so stupid as to believe him—and even publicly basically calling people stupid for believing him. Or sometimes we say they’re not stupid, they’re just racist. But people don’t believe Donald Trump because they are stupid; they believe Donald Trump because he is persuasive. He knows the inner recesses of the human mind and can harness our heuristics to his will. Do not mistake your unique position that protects you—some combination of education, intellect, and sheer willpower—for some inherent superiority. You are not better than Trump’s followers; you are more resistant to Trump’s powers of persuasion. Yes, statistically, Trump voters are more likely to be racist; but racism is a deep-seated bias in the human mind that to some extent we all share. Trump simply knows how to harness it.

Our enemies are persuasive—and therefore we must be as well. We can no longer act as though facts will automatically convince everyone by the power of pure reason; we must learn to stir emotions and rally crowds just as they do.

Or rather, not just as they do—not quite. When we see lies being so effective, we may be tempted to lie ourselves. When we see people being manipulated against us, we may be tempted to manipulate them in return. But in the long run, we can’t afford to do that. We do need to use reason, because reason is the only way to ensure that the beliefs we instill are true.

Therefore our task must be to make people see reason. Let me be clear: Not demand they see reason. Not hope they see reason. Not lament that they don’t. This will require active investment on our part. We must actually learn to persuade people in such a manner that their minds become more open to reason. This will mean using tools other than reason, but it will also mean treading a very fine line, using irrationality only when rationality is insufficient.

We will be tempted to take the easier, quicker path to the Dark Side, but we must resist. Our goal must be not to make people do what we want them to—but to do what they would want to if they were fully rational and fully informed. We will need rhetoric; we will need oratory; we may even need some manipulation. But as we fight our enemy, we must be vigilant not to become them.

This means not using bad arguments—strawmen and conmen—but pointing out the flaws in our opponents’ arguments even when they seem obvious to us—bananamen. It means not overstating our case about free trade or using implausible statistical results simply because they support our case.

But it also means not understating our case, not hiding in page 17 of an opaque technical report that if we don’t do something about climate change right now millions of people will die. It means not presenting our ideas as “political opinions” when they are demonstrated, indisputable scientific facts. It means taking the media to task for their false balance that must find a way to criticize a Democrat every time they criticize a Republican: Sure, he is a pathological liar and might trigger global economic collapse or even nuclear war, but she didn’t secure her emails properly. If you objectively assess the facts and find that Republicans lie three times as often as Democrats, maybe that’s something you should be reporting on instead of trying to compensate for by changing your criteria.

Speaking of the media, we should be pressuring them to include a regular—preferably daily, preferably primetime—segment on climate change, because yes, it is that important. How about after the weather report every day, you show a climate scientist explaining why we keep having record-breaking summer heat and more frequent natural disasters? If we suffer a global ecological collapse, this other stuff you’re constantly talking about really isn’t going to matter—that is, if it mattered in the first place. When ISIS kills 200 people in an attack, you don’t just report that a bunch of people died without examining the cause or talking about responses. But when a typhoon triggered by climate change kills 7,000, suddenly it’s just a random event, an “act of God” that nobody could have predicted or prevented. Having an appropriate caution about whether climate change caused any particular disaster should not prevent us from drawing the very real links between more carbon emissions and more natural disasters—and sometimes there’s just no other explanation.

It means demanding fact-checks immediately, not as some kind of extra commentary that happens after the debate, but as something the moderator says right then and there. (You have a staff, right? And they have Google access, right?) When a candidate says something that is blatantly, demonstrably false, they should receive a warning. After three warnings, their mic should be cut for that question. After ten, they should be kicked off the stage for the remainder of the debate. Donald Trump wouldn’t have lasted five minutes. But instead, they not only let him speak, they spent the next week repeating what he said in bold, exciting headlines. At least CNN finally realized that their headlines could actually fact-check Trump’s statements rather than just repeat them.
Above all, we will need to understand why people think the way they do, and learn to speak to them persuasively and truthfully but without elitism or condescension. This is one I know I’m not very good at myself; sometimes I get so frustrated with people who think the Earth is 6,000 years old (over 40% of Americans) or don’t believe in climate change (35% don’t think it is happening at all, another 30% don’t think it’s a big deal) that I come off as personally insulting them—and of course from that point forward they turn off. But irrational beliefs are not proof of defective character, and we must make that clear to ourselves as well as to others. We must not say that people are stupid or bad; but we absolutely must say that they are wrong. We must also remember that despite our best efforts, some amount of reactance will be inevitable; people simply don’t like having their beliefs challenged.

Yet even all this is probably not enough. Many people don’t watch mainstream media, or don’t believe it when they do (not without reason). Many people won’t even engage with friends or family members who challenge their political views, and will defriend or even disown them. We need some means of reaching these people too, and the hardest part may be simply getting them to listen to us in the first place. Perhaps we need more grassroots action—more protest marches, or even activists going door to door like Jehovah’s Witnesses. Perhaps we need to establish new media outlets that will be as widely accessible but held to a higher standard.

But we must find a way–and we have little time to waste.