risk

Of men and bears

PNRJ core principles, current events, ethics, personal, politics, tribal paradigm , , , , , , , , , , , , ,

May 5 JDN 2460436

[CW: rape, violence, crime, homicide]

I think it started on TikTok, but I’m too old for TikTok, so I first saw it on Facebook and Twitter.

Men and women were asked:
“Would you rather be alone in the woods with a man, or a bear?”

Answers seem to have been pretty mixed. Some women still thought a man was a safer choice, but a significant number chose the bear.

Then when the question was changed to a woman, almost everyone chose the woman over the bear.

What can we learn from this?

I think the biggest thing it tells us is that a lot of women are afraid of men. If you are seriously considering the wild animal over the other human being, you’re clearly afraid.

A lot of the discourse on this seems to be assuming that they are right to be afraid, but I’m not so sure.

It’s not that the fear is unfounded: Most women will suffer some sort of harassment, and a sizeable fraction will suffer some sort of physical or sexual assault, at the hands of some men at some point in their lives.

But there is a cost to fear, and I don’t think we’re taking it properly into account here. I’m worried that encouraging women to fear men will only serve to damage relationships between men and women, the vast majority of which are healthy and positive. I’m worried that this fear is really the sort of overreaction to trauma that ends up causing its own kind of harm.

If you think that’s wrong, consider this:

A sizeable fraction of men will be physically assaulted by other men.

Should men fear each other?

Should all men fear all other men?

What does it do to a society when its whole population fears half of its population? Does that sound healthy? Does whatever small increment in security that might provide seem worth it?

Keep in mind that women being afraid of men doesn’t seem to be protecting them from harm right now. So even if there is genuine harm to be feared, the harm of that fear is actually a lot more obvious than the benefit of it. Our entire society becomes fearful and distrustful, and we aren’t actually any safer.

I’m worried that this is like our fear of terrorism, which made us sacrifice our civil liberties without ever clearly making us safer. What are women giving up due to their fear of men? Is it actually protecting them?

If you have any ideas for how we might actually make women safer, let’s hear them. But please, stop saying idiotic things like “Don’t be a rapist.” 95% of men already aren’t, and the 5% who are, are not going to listen to anything you—or I—say to them. (Bystander intervention programs can work. But just telling men to not be rapists does not.)

I’m all for teaching about consent, but it really isn’t that hard to do—and most rapists seem to understand it just fine, they just don’t care. They’ll happily answer on a survey that they “had sex with someone without their consent”. By all means, undermine rape myths; just don’t expect it to dramatically reduce the rate of rape.

I absolutely want to make people safer. But telling people to be afraid of people like me doesn’t actually seem to accomplish that.

And yes, it hurts when people are afraid of you.

This is not a small harm. This is not a minor trifle. Once we are old enough to be seen as “men” rather than “boys” (which seems to happen faster if you’re Black than if you’re White), men know that other people—men and women, but especially women—will fear us. We go through our whole lives having to be careful what we say, how we move, when we touch someone else, because we are shaped like rapists.

When my mother encounters a child, she immediately walks up to the child and starts talking to them, pointing, laughing, giggling. I can’t do that. If I tried to do the exact same thing, I would be seen as a predator. In fact, without children of my own, it’s safer for me to just not interact with children at all, unless they are close friends or family. This is a whole class of joyful, fulfilling experience that I just don’t get to have because people who look like me commit acts of violence.

Normally we’re all about breaking down prejudice, not treating people differently based on how they look—except when it comes to gender, apparently. It’s okay to fear men but not women.

Who is responsible for this?

Well, obviously the ones most responsible are actual rapists.

But they aren’t very likely to listen to me. If I know any rapists, I don’t know that they are rapists. If I did know, I would want them imprisoned. (Which is likely why they wouldn’t tell me if they were.)

Moreover, my odds of actually knowing a rapist are probably lower than you think, because I don’t like to spend time with men who are selfish, cruel, aggressive, misogynist, or hyper-masculine. The fact that 5% of men in general are rapists doesn’t mean that 5% of any non-random sample of men are rapists. I can only think of a few men I have ever known personally who I would even seriously suspect, and I’ve cut ties with all of them.

The fact that psychopaths are not slavering beasts, obviously different from the rest of us, does not mean that there is no way to tell who is a psychopath. It just means that you need to know what you’re actually looking for. When I once saw a glimmer of joy in someone’s eyes as he described the suffering of animals in an experiment, I knew in that moment he was a psychopath. (There are legitimate reasons to harm animals in scientific experiments—but a good person does not enjoy it.) He did not check most of the boxes of the “Slavering Beast theory”: He had many friends; he wasn’t consistently violent; he was a very good liar; he was quite accomplished in life; he was handsome and charismatic. But go through an actual psychopathy checklist, and you realize that every one of these features makes psychopathy more likely, not less.

I’m not even saying it’s easy to detect psychopaths. It’s not. Even experts need to look very closely and carefully, because psychopaths are often very good at hiding. But there are differences. And it really is true that the selfish, cruel, aggressive, misogynist, hyper-masculine men are more likely to be rapists than the generous, kind, gentle, feminist, androgynous men. It’s not a guarantee—there are lots of misogynists who aren’t rapists, and there are men who present as feminists in public but are rapists in private. But it is a tendency nevertheless. You don’t need to treat every man as equally dangerous, and I don’t think it’s healthy to do so.

Indeed, if I had the choice to be alone in the woods with either a gay male feminist or a woman I knew was cruel to animals, I’d definitely choose the man. These differences matter.

And maybe, just maybe, if we could tamp down this fear a little bit, men and women could have healthier interactions with one another and build stronger relationships. Even if the fear is justified, it could still be doing more harm than good.

So are you safer with a man, or a bear?

Let’s go back to the original thought experiment, and consider the actual odds of being attacked. Yes, the number of people actually attacked by bears is far smaller than the number of people actually attacked by men. (It’s also smaller than the number of people attacked by women, by the way.)

This is obviously because we are constantly surrounded by people, and rarely interact with bears.

In other words, that fact alone basically tells us nothing. It could still be true even if bears are far more dangerous than men, because people interact with bears far less often.

The real question is “How likely is an attack, given that you’re alone in the woods with one?”

Unfortunately, I was unable to find any useful statistics on this. There area lot of vague statements like “Bears don’t usually attack humans” or “Bears only attack when startled or protecting their young”; okay. But how often is “usually”? How often are bears startled? What proportion of bears you might encounter are protecting their young?

So this is really a stab in the dark; but do you think it’s perhaps fair to say that maybe 10% of bear-human close encounters result in an attack?

That doesn’t seem like an unreasonably high number, at least. 90% not attacking sounds like “usually”. Being startled or protecting their young don’t seem like events much rarer than 10%. This estimate could certainly be wrong (and I’m sure it’s not precise), but it seems like the right order of magnitude.

So I’m going to take that as my estimate:

If you are alone in the woods with a bear, you have about a 10% chance of being attacked.

Now, what is the probability that a randomly-selected man would attack you, if you were alone in the woods with him?

This one can be much better estimated. It is roughly equal to the proportion of men who are psychopaths.


Now, figures on this vary too, partly because psychopathy comes in degrees. But at the low end we have about 1.2% of men and 0.3% of women who are really full-blown psychopaths, and at the high end we have about 10% of men and 2% of women who exhibit significant psychopathic traits.

I’d like to note two things about these figures:

  1. It still seems like the man is probably safer than the bear.
  2. Men are only about four or five times as likely to be psychopaths as women.

Admittedly, my bear estimate is very imprecise; so if, say, only 5% of bear encounters result in attacks and 10% of men would attack if you were alone in the woods, men could be more dangerous. But I think it’s unlikely. I’m pretty sure bears are more dangerous.

But the really interesting thing is that people who seemed ambivalent about man versus bear, or even were quite happy to choose the bear, seem quite consistent in choosing women over bears. And I’m not sure the gender difference is really large enough to justify that.

If 1.2% to 10% of men are enough for us to fear all men, why aren’t 0.3% to 2% of women enough for us to fear all women? Is there a threshold at 1% or 5% that flips us from “safe” to “dangerous”?

But aren’t men responsible for most violence, especially sexual violence?

Yes, but probably not by as much as you think.

The vast majority of rapesare committed by men, and most of those are against women. But the figures may not be as lopsided as you imagine; in a given year, about 0.3% of women are raped by a man, and about 0.1% of men are raped by a woman. Over their lifetimes, about 25% of women will be sexually assaulted, and about 5% of men will be. Rapes of men by women have gone even more under-reported than rapes in general, in part because it was only recently that being forced to penetrate someone was counted as a sexual assault—even though it very obviously is.

So men are about 5 times as likely to commit rape as women. That’s a big difference, but I bet it’s a lot smaller than what many of you believed. There are statistics going around that claim that as many as 99% of rapes are committed by men; those statistics are ignoring the “forced to penetrate” assaults, and thus basically defining rape of men by women out of existence.

Indeed, 5 to 1 is quite close to the ratio in psychopathy.

I think that’s no coincidence: In fact, I think it’s largely the case that the psychopaths and the rapists are the same people.

What about homicide?

While men are indeed much more likely to be perpetrators of homicide, they are also much more likely to be victims.

Of about 23,000 homicide offenders in 2022, 15,100 were known to be men, 2,100 were known to be women, and 5,800 were unknown (because we never caught them). Assuming that women are no more or less likely to be caught than men, we can ignore the unknown, and presume that the same gender ratio holds across all homicides: 12% are committed by women.

Of about 22,000 homicides in the US last year, 17,700 victims were men. 3,900 victims were women. So men are 4.5 times as likely to be murdered than women in the US. Similar ratios hold in most First World countries (though total numbers are lower).

Overall, this means that men are about 7 times as likely to commit murder, but about 4.5 times as likely to suffer it.

So if we measure by rate of full-blown psychopathy, men are about 4 times as dangerous as women. If we measure by rate of moderate psychopathy, men are about 5 times as dangerous. If we measure by rate of rape, men are about 5 times as dangerous. And if we measure by rate of homicide, men are about 7 times as dangerous—but mainly to each other.

Put all this together, and I think it’s fair to summarize these results as:

Men are about five times as dangerous as women.

That’s not a small difference. But it’s also not an astronomical one. If you are right to be afraid of all men because they could rape or murder you, why are you not also right to be afraid of all women, who are one-fifth as likely to do the same?

Should we all fear everyone?

Surely you can see that isn’t a healthy way for a society to operate. Yes, there are real dangers in this world; but being constantly afraid of everyone will make you isolated, lonely, paranoid and probably depressed—and it may not even protect you.

It seems like a lot of men responding to the “man or bear” meme were honestly shocked that women are so afraid. If so, they have learned something important. Maybe that’s the value in the meme.

But the fear can be real, even justified, and still be hurting more than it’s helping. I don’t see any evidence that it’s actually making anyone any safer.

We need a better answer than fear.

Bundling the stakes to recalibrate ourselves

PNRJ cognitive science, heuristics and biases, personal , , , , , , , , , ,

Mar 31 JDN 2460402

In a previous post I reflected on how our minds evolved for an environment of immediate return: An immediate threat with high chance of success and life-or-death stakes. But the world we live in is one of delayed return: delayed consequences with low chance of success and minimal stakes.

We evolved for a world where you need to either jump that ravine right now or you’ll die; but we live in a world where you’ll submit a hundred job applications before finally getting a good offer.

Thus, our anxiety system is miscalibrated for our modern world, and this miscalibration causes us to have deep, chronic anxiety which is pathological, instead of brief, intense anxiety that would protect us from harm.

I had an idea for how we might try to jury-rig this system and recalibrate ourselves:

Bundle the stakes.

Consider job applications.

The obvious way to think about it is to consider each application, and decide whether it’s worth the effort.

Any particular job application in today’s market probably costs you 30 minutes, but you won’t hear back for 2 weeks, and you have maybe a 2% chance of success. But if you fail, all you lost was that 30 minutes. This is the exact opposite of what our brains evolved to handle.

So now suppose if you think of it in terms of sending 100 job applications.

That will cost you 30 times 100 minutes = 50 hours. You still won’t hear back for weeks, but you’ve spent weeks, so that won’t feel as strange. And your chances of success after 100 applications are something like 1-(0.98)^100 = 87%.

Even losing 50 hours over a few weeks is not the disaster that falling down a ravine is. But it still feels a lot more reasonable to be anxious about that than to be anxious about losing 30 minutes.

More importantly, we have radically changed the chances of success.

Each individual application will almost certainly fail, but all 100 together will probably succeed.

If we were optimally rational, these two methods would lead to the same outcomes, by a rather deep mathematical law, the linearity of expectation:
E[nX] = n E[X]

Thus, the expected utility of doing something n times is precisely n times the expected utility of doing it once (all other things equal); and so, it doesn’t matter which way you look at it.

But of course we aren’t perfectly rational. We don’t actually respond to the expected utility. It’s still not entirely clear how we do assess probability in our minds (prospect theory seems to be onto something, but it’s computationally harder than rational probability, which means it makes absolutely no sense to evolve it).

If instead we are trying to match up our decisions with a much simpler heuristic that evolved for things like jumping over ravines, our representation of probability may be very simple indeed, something like “definitely”, “probably”, “maybe”, “probably not”, “definitely not”. (This is essentially my categorical prospect theory, which, like the stochastic overload model, is a half-baked theory that I haven’t published and at this point probably never will.)

2% chance of success is solidly “probably not” (or maybe something even stronger, like “almost definitely not”). Then, outcomes that are in that category are presumably weighted pretty low, because they generally don’t happen. Unless they are really good or really bad, it’s probably safest to ignore them—and in this case, they are neither.

But 87% chance of success is a clear “probably”; and outcomes in that category deserve our attention, even if their stakes aren’t especially high. And in fact, by bundling them, we have even made the stakes a bit higher—likely making the outcome a bit more salient.

The goal is to change “this will never work” to “this is going to work”.

For an individual application, there’s really no way to do that (without self-delusion); maybe you can make the odds a little better than 2%, but you surely can’t make them so high they deserve to go all the way up to “probably”. (At best you might manage a “maybe”, if you’ve got the right contacts or something.)

But for the whole set of 100 applications, this is in fact the correct assessment. It will probably work. And if 100 doesn’t, 150 might; if 150 doesn’t, 200 might. At no point do you need to delude yourself into over-estimating the odds, because the actual odds are in your favor.

This isn’t perfect, though.

There’s a glaring problem with this technique that I still can’t resolve: It feels overwhelming.

Doing one job application is really not that big a deal. It accomplishes very little, but also costs very little.

Doing 100 job applications is an enormous undertaking that will take up most of your time for multiple weeks.

So if you are feeling demotivated, asking you to bundle the stakes is asking you to take on a huge, overwhelming task that surely feels utterly beyond you.

Also, when it comes to this particular example, I even managed to do 100 job applications and still get a pretty bad outcome: My only offer was Edinburgh, and I ended up being miserable there. I have reason to believe that these were exceptional circumstances (due to COVID), but it has still been hard to shake the feeling of helplessness I learned from that ordeal.

Maybe there’s some additional reframing that can help here. If so, I haven’t found it yet.

But maybe stakes bundling can help you, or someone out there, even if it can’t help me.

Against Self-Delusion

PNRJ cognitive science, core principles, personal , , , , , , , , , , , , , ,

Mar 10 JDN 2460381

Is there a healthy amount of self-delusion? Would we be better off convincing ourselves that the world is better than it really is, in order to be happy?


A lot of people seem to think so.

I most recently encountered this attitude in Kathryn Schulz’s book Being Wrong (I liked the TED talk much better, in part because it didn’t have this), but there are plenty of other examples.

You’ll even find advocates for this attitude in the scientific literature, particularly when talking about the Lake Wobegon Effect, optimism bias, and depressive realism.

Fortunately, the psychology community seems to be turning away from this, perhaps because of mounting empirical evidence that “depressive realism” isn’t a robust effect. When I searched today, it was easier to find pop psych articles against self-delusion than in favor of it. (I strongly suspect that would not have been true about 10 years ago.)

I have come up with a very simple, powerful argument against self-delusion:

If you’re allowed to delude yourself, why not just believe everything is perfect?

If you can paint your targets after shooting, why not always paint a bullseye?

The notion seems to be that deluding yourself will help you achieve your goals. But if you’re going to delude yourself, why bother achieving goals? You could just pretend to achieve goals. You could just convince yourself that you have achieved goals. Wouldn’t that be so much easier?

The idea seems to be, for instance, to get an aspiring writer to actually finish the novel and submit it to the publisher. But why shouldn’t she simply imagine she has already done so? Why not simply believe she’s already a bestselling author?

If there’s something wrong with deluding yourself into thinking you’re a bestselling author, why isn’t that exact same thing wrong with deluding yourself into thinking you’re a better writer than you are?

Once you have opened this Pandora’s Box of lies, it’s not clear how you can ever close it again. Why shouldn’t you just stop working, stop eating, stop doing anything at all, but convince yourself that your life is wonderful and die in a state of bliss?

Granted, this is not generally what people who favor (so-called) “healthy self-delusion” advocate. But it’s difficult to see any principled reason why they should reject it. Once you give up on tying your beliefs to reality, it’s difficult to see why you shouldn’t just say that anything goes.

Why are some deviations from reality okay, but not others? Is it because they are small? Small changes in belief can still have big consequences: Believe a car is ten meters behind where it really is, and it may just run you over.

The general approach of “healthy self-delusion” seems to be that it’s all right to believe that you are smarter, prettier, healthier, wiser, and more competent than you actually are, because that will make you more confident and therefore more successful.

Well, first of all, it’s worth pointing out that some people obviously go way too far in that direction and become narcissists. But okay, let’s say we find a way to avoid that. (It’s unclear exactly how, since, again, by construction, we aren’t tying ourselves to reality.)

In practice, the people who most often get this sort of advice are people who currently lack self-confidence, who doubt their own abilities—people who suffer from Impostor Syndrome. And for people like that (and I count myself among them), a certain amount of greater self-confidence would surely be a good thing.

The idea seems to be that deluding yourself to increase your confidence will get you to face challenges and take risks you otherwise wouldn’t have, and that this will yield good outcomes.

But there’s a glaring hole in this argument:

If you have to delude yourself in order to take a risk, you shouldn’t take that risk.

Risk-taking is not an unalloyed good. Russian Roulette is certainly risky, but it’s not a good career path.

There are in fact a lot of risks you simply shouldn’t take, because they aren’t worth it.

The right risks to take are the ones for which the expected benefit outweighs the expected cost: The one with the highest expected utility. (That sounds simple, and in principle it is; but in practice, it can be extraordinarily difficult to determine.)

In other words, the right risks to take are the ones that are rational. The ones that a correct view of the world will instruct you to take.

That aspiring novelist, then, should write the book and submit it to publishers—if she’s actually any good at writing. If she’s actually terrible, then never submitting the book is the correct decision; she should spend more time honing her craft before she tries to finish it—or maybe even give up on it and do something else with her life.

What she needs, therefore, is not a confident assessment of her abilities, but an accurate one. She needs to believe that she is competent if and only if she actually is competent.

But I can also see how self-delusion can seem like good advice—and even work for some people.

If you start from an excessively negative view of yourself or the world, then giving yourself a more positive view will likely cause you to accomplish more things. If you’re constantly telling yourself that you are worthless and hopeless, then convincing yourself that you’re better than you thought is absolutely what you need to do. (Because it’s true.)

I can even see how convincing yourself that you are the best is useful—even though, by construction, most people aren’t. When you live in a hyper-competitive society like ours, where we are constantly told that winning is everything, losers are worthless, and second place is as bad as losing, it may help you get by to tell yourself that you really are the best, that you really can win. (Even weirder: “Winning isn’t everything; it’s the only thing.” Uh, that’s just… obviously false? Like, what is this even intended to mean that “Winning is everything” didn’t already say better?)

But that’s clearly not the right answer. You’re solving one problem by adding another. You shouldn’t believe you are the best; you should recognize that you don’t have to be. Second place is not as bad as losing—and neither is fifth, or tenth, or fiftieth place. The 100th-most successful author in the world still makes millions writing. The 1,000th-best musician does regular concert tours. The 10,000th-best accountant has a steady job. Even the 100,000th-best trucker can make a decent living. (Well, at least until the robots replace him.)

Honestly, it’d be great if our whole society would please get this memo. It’s no problem that “only a minority of schools play sport to a high level”—indeed, that’s literally inevitable. It’s also not clear that “60% of students read below grade level” is a problem, when “grade level” seems to be largely defined by averages. (Literacy is great and all, but what’s your objective standard for “what a sixth grader should be able to read”?)

We can’t all be the best. We can’t all even be above-average.

That’s okay. Below-average does not mean inadequate.

That’s the message we need to be sending:

You don’t have to be the best in order to succeed.

You don’t have to be perfect in order to be good enough.

You don’t even have to be above-average.

This doesn’t require believing anything that isn’t true. It doesn’t require overestimating your abilities or your chances. In fact, it asks you to believe something that is more true than “You have to be the best” or “Winning is everything”.

If what you want to do is actually worth doing, an accurate assessment will tell you that. And if an accurate assessment tells you not to do it, then you shouldn’t do it. So you have no reason at all to strive for anything other than accurate beliefs.

With this in mind, the fact that the empirical evidence for “depressive realism” is shockingly weak is not only unsurprising; it’s almost irrelevant. You can’t have evidence against being rational. If deluded people succeed more, that means something is very, very wrong; and the solution is clearly not to make more people deluded.

Of course, it’s worth pointing out that the evidence is shockingly weak: Depressed people show different biases, not less bias. And in fact they seem to be more overconfident in the following sense: They are more certain that what they predict will happen is what will actually happen.

So while most people think they will succeed when they will probably fail, depressed people are certain they will fail when in fact they could succeed. Both beliefs are inaccurate, but the depressed one is in an important sense more inaccurate: It tells you to give up, which is the wrong thing to do.

“Healthy self-delusion” ultimately amounts to trying to get you to do the right thing for the wrong reasons. But why? Do the right thing for the right reasons! If it’s really the right thing, it should have the right reasons!

When maximizing utility doesn’t

PNRJ critique of neoclassical economics, ethics, futurism , , , , , , , , , , ,

Jun 4 JDN 2460100

Expected utility theory behaves quite strangely when you consider questions involving mortality.

Nick Beckstead and Teruji Thomas recently published a paper on this: All well-defined utility functions are either reckless in that they make you take crazy risks, or timid in that they tell you not to take even very small risks. It’s starting to make me wonder if utility theory is even the right way to make decisions after all.

Consider a game of Russian roulette where the prize is $1 million. The revolver has 6 chambers, 3 with a bullet. So that’s a 1/2 chance of $1 million, and a 1/2 chance of dying. Should you play?

I think it’s probably a bad idea to play. But the prize does matter; if it were $100 million, or $1 billion, maybe you should play after all. And if it were $10,000, you clearly shouldn’t.

And lest you think that there is no chance of dying you should be willing to accept for any amount of money, consider this: Do you drive a car? Do you cross the street? Do you do anything that could ever have any risk of shortening your lifespan in exchange for some other gain? I don’t see how you could live a remotely normal life without doing so. It might be a very small risk, but it’s still there.

This raises the question: Suppose we have some utility function over wealth; ln(x) is a quite plausible one. What utility should we assign to dying?


The fact that the prize matters means that we can’t assign death a utility of negative infinity. It must be some finite value.

But suppose we choose some value, -V, (so V is positive), for the utility of dying. Then we can find some amount of money that will make you willing to play: ln(x) = V, x = e^(V).

Now, suppose that you have the chance to play this game over and over again. Your marginal utility of wealth will change each time you win, so we may need to increase the prize to keep you playing; but we could do that. The prizes could keep scaling up as needed to make you willing to play. So then, you will keep playing, over and over—and then, sooner or later, you’ll die. So, at each step you maximized utility—but at the end, you didn’t get any utility.

Well, at that point your heirs will be rich, right? So maybe you’re actually okay with that. Maybe there is some amount of money ($1 billion?) that you’d be willing to die in order to ensure your heirs have.

But what if you don’t have any heirs? Or, what if we consider making such a decision as a civilization? What if death means not only the destruction of you, but also the destruction of everything you care about?

As a civilization, are there choices before us that would result in some chance of a glorious, wonderful future, but also some chance of total annihilation? I think it’s pretty clear that there are. Nuclear technology, biotechnology, artificial intelligence. For about the last century, humanity has been at a unique epoch: We are being forced to make this kind of existential decision, to face this kind of existential risk.

It’s not that we were immune to being wiped out before; an asteroid could have taken us out at any time (as happened to the dinosaurs), and a volcanic eruption nearly did. But this is the first time in humanity’s existence that we have had the power to destroy ourselves. This is the first time we have a decision to make about it.

One possible answer would be to say we should never be willing to take any kind of existential risk. Unlike the case of an individual, when we speaking about an entire civilization, it no longer seems obvious that we shouldn’t set the utility of death at negative infinity. But if we really did this, it would require shutting down whole industries—definitely halting all research in AI and biotechnology, probably disarming all nuclear weapons and destroying all their blueprints, and quite possibly even shutting down the coal and oil industries. It would be an utterly radical change, and it would require bearing great costs.

On the other hand, if we should decide that it is sometimes worth the risk, we will need to know when it is worth the risk. We currently don’t know that.

Even worse, we will need some mechanism for ensuring that we don’t take the risk when it isn’t worth it. And we have nothing like such a mechanism. In fact, most of our process of research in AI and biotechnology is widely dispersed, with no central governing authority and regulations that are inconsistent between countries. I think it’s quite apparent that right now, there are research projects going on somewhere in the world that aren’t worth the existential risk they pose for humanity—but the people doing them are convinced that they are worth it because they so greatly advance their national interest—or simply because they could be so very profitable.

In other words, humanity finally has the power to make a decision about our survival, and we’re not doing it. We aren’t making a decision at all. We’re letting that responsibility fall upon more or less randomly-chosen individuals in government and corporate labs around the world. We may be careening toward an abyss, and we don’t even know who has the steering wheel.

A guide to surviving the apocalypse

PNRJ current events, ethics, futurism , , , , , , , , , ,

Aug 21 JDN 2459820

Some have characterized the COVID pandemic as an apocalypse, though it clearly isn’t. But a real apocalypse is certainly possible, and its low probability is offset by its extreme importance. The destruction of human civilization would be quite literally the worst thing that ever happened, and if it led to outright human extinction or civilization was never rebuilt, it could prevent a future that would have trillions if not quadrillions of happy, prosperous people.

So let’s talk about things people like you and me could do to survive such a catastrophe, and hopefully work to rebuild civilization. I’ll try to inject a somewhat light-hearted tone into this otherwise extraordinarily dark topic; we’ll see how well it works. What specifically we would want—or be able—to do will depend on the specific scenario that causes the apocalypse, so I’ll address those specifics shortly. But first, let’s talk about general stuff that should be useful in most, if not all, apocalypse scenarios.

It turns out that these general pieces of advice are also pretty good advice for much smaller-scale disasters such as fires, tornados, or earthquakes—all of which are far more likely to occur. Your top priority is to provide for the following basic needs:

1. Water: You will need water to drink. You should have some kind of stockpile of clean water; bottled water is fine but overpriced, and you’d do just as well to bottle tap water (as long as you do it before the crisis occurs and the water system goes down). Better still would be to have water filtration and purification equipment so that you can simply gather whatever water is available and make it drinkable.

2. Food: You will need nutritious, non-perishable food. Canned vegetables and beans are ideal, but you can also get a lot of benefit from dry staples such as crackers. Processed foods and candy are not as nutritious, but they do tend to keep well, so they can do in a pinch. Avoid anything that spoils quickly or requires sophisticated cooking. In the event of a disaster, you will be able to make fire and possibly run a microwave on a solar panel or portable generator—but you can’t rely on the electrical or gas mains to stay operational, and even boiling will require precious water.

3. Shelter: Depending on the disaster, your home may or may not remain standing—and even if it is standing, it may not be fit for habitation. Consider backup options for shelter: Do you have a basement? Do you own any tents? Do you know people you could move in with, if their homes survive and yours doesn’t?

4. Defense: It actually makes sense to own a gun or two in the event of a crisis. (In general it’s actually a big risk, though, so keep that in mind: the person your gun is most likely to kill is you.) Just don’t go overboard and do what we all did in Oregon Trail, stocking plenty of bullets but not enough canned food. Ammo will be hard to replace, though; your best option may actually be a gauss rifle (yes, those are real, and yes, I want one), because all they need for ammo is ferromagnetic metal of the appropriate shape and size. Then, all you need is a solar panel to charge its battery and some machine tools to convert scrap metal into ammo.

5. Community: Humans are highly social creatures, and we survive much better in groups. Get to know your neighbors. Stay in touch with friends and family. Not only will this improve your life in general, it will also give you people to reach out to if you need help during the crisis and the government is indisposed (or toppled). Having a portable radio that runs on batteries, solar power, or hand-crank operation will also be highly valuable for staying in touch with people during a crisis. (Likewise flashlights!)

Now, on to the specific scenarios. I will consider the following potential causes of apocalypse: Alien Invasion, Artificial Intelligence Uprising, Climate Disaster, Conventional War, Gamma-Ray Burst, Meteor Impact, Plague, Nuclear War, and last (and, honestly, least), Zombies.

I will rate each apocalypse by its risk level, based on its probability of occurring within the next 100 years (roughly the time I think it will take us to meaningfully colonize space and thereby change the game):

Very High: 1% or more

High: 0.1% – 1%

Moderate: 0.01% – 0.1%

Low: 0.001% – 0.01%

Very Low: 0.0001% – 0.001%

Tiny: 0.00001% – 0.0001%

Miniscule: 0.00001% or less

I will also rate your relative safety in different possible locations you might find yourself during the crisis:

Very Safe: You will probably survive.

Safe: You will likely survive if you are careful.

Dicey: You may survive, you may not. Hard to say.

Dangerous: You will likely die unless you are very careful.

Very Dangerous: You will probably die.

Hopeless: You will definitely die.

I’ll rate the following locations for each, with some explanation: City, Suburb, Rural Area, Military Base, Underground Bunker, Ship at Sea. Certain patterns will emerge—but some results may surprise you. This may tell you where to go to have the best chance of survival in the event of a disaster (though I admit bunkers are often in short supply).

All right, here goes!

Alien Invasion

Risk: Low

There are probably sapient aliens somewhere in this vast universe, maybe even some with advanced technology. But they are very unlikely to be willing to expend the enormous resources to travel across the stars just to conquer us. Then again, hey, it could happen; maybe they’re imperialists, or they have watched our TV commercials and heard the siren song of oregano.

City: Dangerous

Population centers are likely to be primary targets for their invasion. They probably won’t want to exterminate us outright (why would they?), but they may want to take control of our cities, and are likely to kill a lot of people when they do.

Suburb: Dicey

Outside the city centers will be a bit safer, but hardly truly safe.

Rural Area: Dicey

Where humans are spread out, we’ll present less of a target. Then again, if you own an oregano farm….

Military Base: Very Dangerous

You might think that having all those planes and guns around would help, but these will surely be prime targets in an invasion. Since the aliens are likely to be far more technologically advanced, it’s unlikely our military forces could put up much resistance. Our bases would likely be wiped out almost immediately.

Underground Bunker: Safe

This is a good place to be. Orbital and aerial weapons won’t be very effective against underground targets, and even ground troops would have trouble finding and attacking an isolated bunker. Since they probably won’t want to exterminate us, hiding in your bunker until they establish a New World Order could work out for you.

Ship at Sea: Dicey

As long as it’s a civilian vessel, you should be okay. A naval vessel is just as dangerous as a base, if not more so; they would likely strike our entire fleets from orbit almost instantly. But the aliens are unlikely to have much reason to bother attacking a cruise ship or a yacht. Then again, if they do, you’re toast.

Artificial Intelligence Uprising

Risk: Very High

While it sounds very sci-fi, this is one of the most probable apocalypse scenarios, and we should be working to defend against it. There are dozens of ways that artificial intelligence could get out of control and cause tremendous damage, particularly if the AI got control of combat drones or naval vessels. This could mean a superintelligent AI beyond human comprehension, but it need not; it could in fact be a very stupid AI that was programmed to make profits for Hasbro and decided that melting people into plastic was the best way to do that.

City: Very Dangerous

Cities don’t just have lots of people; they also have lots of machines. If the AI can hack our networks, they may be able to hack into not just phones and laptops, but even cars, homes, and power plants. Depending on the AI’s goals (which are very hard to predict), cities could become disaster zones almost immediately, as thousands of cars shut down and crash and all the power plants get set to overload.

Suburb: Dangerous

Definitely safer than the city, but still, you’ve got plenty of technology around you for the AI to exploit.

Rural Area: Dicey

The further you are from other people and their technology, the safer you’ll be. Having bad wifi out in the boonies may actually save your life. Then again, even tractors have software updates now….

Military Base: Very Dangerous

The military is extremely high-tech and all network-linked. Unless they can successfully secure their systems against the AI very well, very fast, suddenly all the guided missiles and combat drones and sentry guns will be deployed in service of the robot revolution.

Underground Bunker: Safe

As long as your bunker is off the grid, you should be okay. The robots won’t have any weapons we don’t already have, and bunkers are built because they protect pretty well against most weapons.

Ship at Sea: Hopeless

You are surrounded by technology and you have nowhere to run. A military vessel is worse than a civilian ship, but either way, you’re pretty much doomed. The AI is going to take over the radio, the GPS system, maybe even the controls of the ship themselves. It could intentionally overload the engines, or drive you into rocks, or simply shut down everything and leave you to starve at sea. A sailing yacht with a hand-held compass and sextant should be relatively safe, if you manage to get your hands on one of those somehow.

Climate Disaster

Risk: Moderate

Let’s be clear here. Some kind of climate disaster is inevitable; indeed, it’s already in progress. But what I’m talking about is something really severe, something that puts all of human civilization in jeopardy. That, fortunately, is fairly unlikely—and even more so after the big bill that just passed!

City: Dicey

Buildings provide shelter from the elements, and cities will be the first places we defend. Dikes will be built around Manhattan like the ones around Amsterdam. You won’t need to worry about fires, snowstorms, or flooding very much. Still, a really severe crisis could cause all utility systems to break down, meaning you won’t have heating and cooling.

Suburb: Dicey

The suburbs will be about as safe as the cities, maybe a little worse because there isn’t as much shelter if you lose your home to a disaster event.

Rural Area: Dangerous

Remote areas are going to have it the worst. Especially if you’re near a coast that can flood or a forest that can burn, you’re exposed to the elements and there won’t be much infrastructure to protect you. Your best bet is to move in toward the city, where other people will try to help you against the coming storms.

Military Base: Very Safe

Military infrastructure will be prioritized in defense plans, and soldiers are already given lots of survival tools and training. If you can get yourself to a military base and they actually let you in, you really won’t have much to worry about.

Underground Bunker: Very Safe

Underground doesn’t have a lot of weather, it turns out. As long as your bunker is well sealed against flooding, earthquakes are really your only serious concern, and climate change isn’t going to affect those very much.

Ship at Sea: Safe

Increased frequency of hurricanes and other storms will make the sea more dangerous, but as long as you steer clear of storms as they come, you should be okay.

Conventional War

Risk: Moderate

Once again, I should clarify. Obviously there are going to be wars—there are wars going on this very minute. But a truly disastrous war, a World War 3 still fought with conventional weapons, is fairly unlikely. We can’t rule it out, but we don’t have to worry too much—or rather, it’s nukes we should worry about, as I’ll get to in a little bit. It’s unlikely that truly apocalyptic damage could be caused by conventional weapons alone.

City: Dicey

Cities will often be where battles are fought, as they are strategically important. Expect bombing raids and perhaps infantry or tank battalions. Still, it’s actually pretty feasible to survive in a city that is under attack by conventional weapons; while lots of people certainly die, in most wars, most people actually don’t.

Suburb: Safe

Suburbs rarely make interesting military targets, so you’ll mainly have to worry about troops passing through on their way to cities.

Rural Area: Safe

For similar reasons to the suburbs, you should be relatively safe out in the boonies. You may encounter some scattered skirmishes, but you’re unlikely to face sustained attack.

Military Base: Dicey

Whether military bases are safe really depends on whether your side is winning or not. If they are, then you’re probably okay; that’s where all the soldiers and military equipment are, there to defend you. If they aren’t, then you’re in trouble; military bases make nice, juicy targets for attack.

Ship at Sea: Safe

There’s a reason it is big news every time a civilian cruise liner gets sunk in a war (does the Lusitania ring a bell?); it really doesn’t happen that much. Transport ships are at risk of submarine raids, and of course naval vessels will face constant threats; but cruise liners aren’t strategically important, so military forces have very little reason to target them.

Gamma-Ray Burst

Risk: Tiny

While gamma-ray bursts certainly happen all the time, so far they have all been extremely remote from Earth. It is currently estimated that they only happen a few times in any given galaxy every few million years. And each one is concentrated in a narrow beam, so even when they happen they only affect a few nearby stars. This is very good news, because if it happened… well, that’s pretty much it. We’d be doomed.

If a gamma-ray burst happened within a few light-years of us, and happened to be pointed at us, it would scour the Earth, boil the water, burn the atmosphere. Our entire planet would become a dead, molten rock—if, that is, it wasn’t so close that it blew the planet up completely. And the same is going to be true of Mars, Mercury, and every other planet in our solar system.

Underground Bunker: Very Dangerous

Your one meager hope of survival would be to be in an underground bunker at the moment the burst hit. Since most bursts give very little warning, you are unlikely to achieve this unless you, like, live in a bunker—which sounds pretty terrible. Moreover, your bunker needs to be a 100% closed system, and deep underground; the surface will be molten and the air will be burned away. There’s honestly a pretty narrow band of the Earth’s crust that’s deep enough to protect you but not already hot enough to doom you.

Anywhere Else: Hopeless

If you aren’t deep underground at the moment the burst hits us, that’s it; you’re dead. If you are on the side of the Earth facing the burst, you will die mercifully quickly, burned to a crisp instantly. If you are not, your death will be a bit slower, as the raging firestorm that engulfs the Earth, boils the oceans, and burns away the atmosphere will take some time to hit you. But your demise is equally inevitable.

Well, that was cheery. Remember, it’s really unlikely to happen! Moving on!

Meteor Impact

Risk: Tiny

Yes, “it has happened before, and it will happen again; the only question is when.” However, meteors with sufficient size to cause a global catastrophe only seem to hit the Earth about once every couple hundred million years. Moreover, right now the first time in human history where we might actually have a serious chance of detecting and deflecting an oncoming meteor—so even if one were on the way, we’d still have some hope of saving ourselves.

Underground Bunker: Dangerous

A meteor impact would be a lot like a gamma-ray burst, only much less so. (Almost anything is “much less so” than a gamma-ray burst, with the lone exception of a supernova, which is always “much more so”.) It would still boil a lot of ocean and start a massive firestorm, but it wouldn’t boil all the ocean, and the firestorm wouldn’t burn away all the oxygen in the atmosphere. Underground is clearly the safest place to be, preferably on the other side of the planet from the impact.

Anywhere Else: Very Dangerous

If you are above ground, it wouldn’t otherwise matter too much where you are, at least not in any way that’s easy to predict. Further from the impact is obviously better than closer, but the impact could be almost anywhere. After the initial destruction there would be a prolonged impact winter, which could cause famines and wars. Rural areas might be a bit safer than cities, but then again if you are in a remote area, you are less likely to get help if you need it.

Plague

Risk: Low

Obviously, the probability of a pandemic is 100%. You best start believing in pandemics; we’re in one. But pandemics aren’t apocalyptic plagues. To really jeopardize human civilization, there would have to be a superbug that spreads and mutates rapidly, has a high fatality rate, and remains highly resistant to treatment and vaccination. Fortunately, there aren’t a lot of bacteria or viruses like that; the last one we had was the Black Death, and humanity made it through that one. In fact, there is good reason to believe that with modern medical technology, even a pathogen like the Black Death wouldn’t be nearly as bad this time around.

City: Dangerous

Assuming the pathogen spreads from human to human, concentrations of humans are going to be the most dangerous places to be. Staying indoors and following whatever lockdown/mask/safety protocols that authorities recommend will surely help you; but if the plague gets bad enough, infrastructure could start falling apart and even those things will stop working.

Suburb: Safe

In a suburb, you are much more isolated from other people. You can stay in your home and be fairly safe from the plague, as long as you are careful.

Rural Area: Dangerous

The remoteness of a rural area means that you’d think you wouldn’t have to worry as much about human-to-human transmission. But as we’ve learned from COVID, rural areas are full of stubborn right-wing people who refuse to follow government safety protocols. There may not be many people around, but they probably will be taking stupid risks and spreading the disease all over the place. Moreover, if the disease can be carried by animals—as quite a few can—livestock will become an added danger.

Military Base: Safe

If there’s one place in the world where people follow government safety protocols, it’s a military base. Bases will have top-of-the-line equipment, skilled and disciplined personnel, and up-to-the-minute data on the spread of the pathogen.

Underground Bunker: Very Safe

The main thing you need to do is be away from other people for awhile, and a bunker is a great place to do that. As long as your bunker is well-stocked with food and water, you can ride out the plague and come back out once it dies down.

Ship at Sea: Dicey

This is an all-or-nothing proposition. If no one on the ship has the disease, you’re probably safe as long as you remain at sea, because very few pathogens can spread that far through the air. On the other hand, if someone on your ship does carry the disease, you’re basically doomed.

Nuclear War

Risk: Very High

Honestly, this is the one that terrifies me. I have no way of knowing that Vladmir Putin or Xi Jinping won’t wake up one morning any day now and give the order to launch a thousand nuclear missiles. (I honestly wasn’t even sure Trump wouldn’t, so it’s a damn good thing he’s out of office.) They have no reason to, but they’re psychopathic enough that I can’t be sure they won’t.

City: Dangerous

Obviously, most of those missiles are aimed at cities. And if you happen to be in the center of such a city, this is very bad for your health. However, nukes are not the automatic death machines that they are often portrayed to be; sure, right at the blast center you’re vaporized. But Hiroshima and Nagasaki both had lots of survivors, many of whom lived on for years or even decades afterward, even despite the radiation poisoning.

Suburb: Dangerous

Being away from a city center might provide some protection, but then again it might not; it really depends on how the nukes are targeted. It’s actually quite unlikely that Russia or China (or whoever) would deploy large megaton-yield missiles, as they are very expensive; so you could only have a few, making it easier to shoot them all down. The far more likely scenario is lots of kiloton-yield missiles, deployed in what is called a MIRV: multiple independent re-entry vehicle. One missile launches into space, then splits into many missiles, each of which can have a different target. It’s sort of like a cluster bomb, only the “little” clusters are each Hiroshima bombs. Those clusters might actually be spread over metropolitan areas relatively evenly, so being in a suburb might not save you. Or it might. Hard to say.

Rural Area: Dicey

If you are sufficiently remote from cities, the nukes probably won’t be aimed at you. And since most of the danger really happens right when the nuke hits, this is good news for you. You won’t have to worry about the blast or the radiation; your main concerns will be fallout and the resulting collapse of infrastructure. Nuclear winter could also be a risk, but recent studies suggest that’s relatively unlikely even in a full-scale nuclear exchange.

Military Base: Hopeless

The nukes are going to be targeted directly at military bases. Probably multiple nukes per base, in case some get shot down. Basically, if you are on a base at the time the missiles hit, you’re doomed. If you know the missiles are coming, your best bet would be to get as far from that base as you can, into as remote an area as you can. You’ll have a matter of minutes, so good luck.

Underground Bunker: Safe

There’s a reason we built a bunch of underground bunkers during the Cold War; they’re one of the few places you can go to really be safe from a nuclear attack. As long as your bunker is well-stocked and well-shielded, you can hide there and survive not only the initial attack, but the worst of the fallout as well.

Ship at Sea: Safe

Ships are small enough that they probably wouldn’t be targeted by nukes. Maybe if you’re on or near a major naval capital ship, like an aircraft carrier, you’d be in danger; someone might try to nuke that. (Even then, aircraft carriers are tough: Anything short of a direct hit might actually be survivable. In tests, carriers have remained afloat and largely functional even after a 100-kiloton nuclear bomb was detonated a mile away. They’re even radiation-shielded, because they have nuclear reactors.) But a civilian vessel or even a smaller naval vessel is unlikely to be targeted. Just stay miles away from any cities or any other ships, and you should be okay.

Zombies

Risk: Miniscule

Zombies per se—the literal undead—aren’t even real, so that’s just impossible. But something like zombies could maybe happen, in some very remote scenario in which some bizarre mutant strain of rabies or something spreads far and wide and causes people to go crazy and attack other people. Even then, if the infection is really only spread through bites, it’s not clear how it could ever reach a truly apocalyptic level; more likely, it would cause a lot of damage locally and then be rapidly contained, and we’d remember it like Pearl Harbor or 9/11: That terrible, terrible day when 5,000 people became zombies in Portland, and then they all died and it was over. An airborne or mosquito-borne virus would be much more dangerous, but then we’re really talking about a plague, not zombies. The ‘turns people into zombies’ part of the virus would be a lot less important than the ‘spreads through the air and kills you’ part.

Seriously, why is this such a common trope? Why do people think that this could cause an apocalypse?

City: Safe

Yes, safe, dammit. Once you have learned that zombies are on the loose, stay locked in your home, wearing heavy clothing (to block bites; a dog suit is ideal, but a leather jacket or puffy coat would do) with a shotgun (or a gauss rifle, see above) at the ready, and you’ll probably be fine. Yes, this is the area of highest risk, due to the concentration of people who could potentially be infected with the zombie virus. But unless you are stupid—which people in these movies always seem to be—you really aren’t in all that much danger. Zombies can at most be as fast and strong as humans (often, they seem to be less!), so all you need to do is shoot them before they can bite you. And unlike fake movie zombies, anything genuinely possible will go down from any mortal wound, not just a perfect headshot—I assure you, humans, however crazed by infection they might be, can’t run at you if their hearts (or their legs) are gone. It might take a bit more damage to drop them than an ordinary person, if they aren’t slowed down by pain; but it wouldn’t require perfect marksmanship or any kind of special weaponry. Buckshot to the chest will work just fine.

Suburb: Safe

Similar to the city, only more so, because people there are more isolated.

Rural Area: Very Safe

And rural areas are even more isolated still—plus you have more guns than people, so you’ll have more guns than zombies.

Military Base: Very Safe

Even more guns, plus military training and a chain of command! The zombies don’t stand a chance. A military base would be a great place to be, and indeed that’s where the containment would begin, as troops march from the bases to the cities to clear out the zombies. Shaun of the Dead (of all things!) actually got this right: One local area gets pretty bad, but then the Army comes in and takes all the zombies out.

Underground Bunker: Very Safe

A bunker remains safe in the event of zombies, just as it is in most other scenarios.

Ship at Sea: Very Safe

As long as the infection hasn’t spread to the ship you are currently on and the zombies can’t swim, you are at literally zero risk.

Risk compensation is not a serious problem

PNRJ development economics, ethics, mathematical models, public policy , , ,

Nov 28 JDN 2459547

Risk compensation. It’s one of those simple but counter-intuitive ideas that economists love, and it has been a major consideration in regulatory policy since the 1970s.

The idea is this: The risk we face in our actions is partly under our control. It requires effort to reduce risk, and effort is costly. So when an external source, such as a government regulation, reduces our risk, we will compensate by reducing the effort we expend, and thus our risk will decrease less, or maybe not at all. Indeed, perhaps we’ll even overcompensate and make our risk worse!

It’s often used as an argument against various kinds of safety efforts: Airbags will make people drive worse! Masks will make people go out and get infected!

The basic theory here is sound: Effort to reduce risk is costly, and people try to reduce costly things.

Indeed, it’s theoretically possible that risk compensation could yield the exact same risk, or even more risk than before—or at least, I wasn’t able to prove that for any possible risk profile and cost function it couldn’t happen.

But I wasn’t able to find any actual risk profiles or cost functions that would yield this result, even for a quite general form. Here, let me show you.

Let’s say there’s some possible harm H. There is also some probability that it will occur, which you can mitigate with some choice x. For simplicity let’s say that it’s one-to-one, so that your risk of H occurring is precisely 1-x. Since probabilities must be between 0 and 1, thus so must x.

Reducing that risk costs effort. I won’t say much about that cost, except to call it c(x) and assume the following:

(1) It is increasing: More effort reduces risk more and costs more than less effort.

(2) It is convex: Reducing risk from a high level to a low level (e.g. 0.9 to 0.8) costs less than reducing it from a low level to an even lower level (e.g. 0.2 to 0.1).

These both seem like eminently plausible—indeed, nigh-unassailable—assumptions. And they result in the following total expected cost (the opposite of your expected utility):

(1-x)H + c(x)

Now let’s suppose there’s some policy which will reduce your risk by a factor r, which must be between 0 and 1. Your cost then becomes:

r(1-x)H + c(x)

Minimizing this yields the following result:

rH = c'(x)

where c'(x) is the derivative of c(x). Since c(x) is increasing and convex, c'(x) is positive and increasing.

Thus, if I make r smaller—an external source of less risk—then I will reduce the optimal choice of x. This is risk compensation.

But have I reduced or increased the amount of risk?

The total risk is r(1-x); since r decreased and so did x, it’s not clear whether this went up or down. Indeed, it’s theoretically possible to have cost functions that would make it go up—but I’ve never seen one.

For instance, suppose we assume that c(x) = axb, where a and b are constants. This seems like a pretty general form, doesn’t it? To maintain the assumption that c(x) is increasing and convex, I need a > 0 and b > 1. (If 0 < b < 1, you get a function that’s increasing but concave. If b=1, you get a linear function and some weird corner solutions where you either expend no effort at all or all possible effort.)

Then I’m trying to minimize:

r(1-x)H + axb

This results in a closed-form solution for x:

x = (rH/ab)^(1/(b-1))

Since b>1, 1/(b-1) > 0.


Thus, the optimal choice of x is increasing in rH and decreasing in ab. That is, reducing the harm H or the overall risk r will make me put in less effort, while reducing the cost of effort (via either a or b) will make me put in more effort. These all make sense.

Can I ever increase the overall risk by reducing r? Let’s see.


My total risk r(1-x) is therefore:

r(1-x) = r[1-(rH/ab)^(1/(b-1))]

Can making r smaller ever make this larger?

Well, let’s compare it against the case when r=1. We want to see if there’s a case where it’s actually larger.

r[1-(rH/ab)^(1/(b-1))] > [1-(H/ab)^(1/(b-1))]

r – r^(1/(b-1)) (H/ab)^(1/(b-1)) > 1 – (H/ab)^(1/(b-1))

For this to be true, we would need r > 1, which would mean we didn’t reduce risk at all. Thus, reducing risk externally reduces total risk even after compensation.

Now, to be fair, this isn’t a fully general model. I had to assume some specific functional forms. But I didn’t assume much, did I?

Indeed, there is a fully general argument that externally reduced risk will never harm you. It’s quite simple.

There are three states to consider: In state A, you have your original level of risk and your original level of effort to reduce it. In state B, you have an externally reduced level of risk and your original level of effort. In state C, you have an externally reduced level of risk, and you compensate by reducing your effort.

Which states make you better off?

Well, clearly state B is better than state A: You get reduced risk at no cost to you.

Furthermore, state C must be better than state B: You voluntarily chose to risk-compensate precisely because it made you better off.

Therefore, as long as your preferences are rational, state C is better than state A.

Externally reduced risk will never make you worse off.

QED. That’s it. That’s the whole proof.

But I’m a behavioral economist, am I not? What if people aren’t being rational? Perhaps there’s some behavioral bias that causes people to overcompensate for reduced risks. That’s ultimately an empirical question.

So, what does the empirical data say? Risk compensation is almost never a serious problem in the real world. Measures designed to increase safety, lo and behold, actually increase safety. Removing safety regulations, astonishingly enough, makes people less safe and worse off.

If we ever do find a case where risk compensation is very large, then I guess we can remove that safety measure, or find some way to get people to stop overcompensating. But in the real world this has basically never happened.

It’s still a fair question whether any given safety measure is worth the cost: Implementing regulations can be expensive, after all. And while many people would like to think that “no amount of money is worth a human life”, nobody does—or should, or even can—act like that in the real world. You wouldn’t drive to work or get out of bed in the morning if you honestly believed that.

If it would cost $4 billion to save one expected life, it’s definitely not worth it. Indeed, you should still be able to see that even if you don’t think lives can be compared with other things—because $4 billion could save an awful lot of lives if you spent it more efficiently. (Probablyover a million, in fact, as current estimates of the marginal cost to save one life are about $2,300.) Inefficient safety interventions don’t just cost money—they prevent us from doing other, more efficient safety interventions.

And as for airbags and wearing masks to prevent COVID? Yes, definitely 100% worth it, as both interventions have already saved tens if not hundreds of thousands of lives.

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.

Glorifying superstars glorifies excessive risk

PNRJ core principles, financial advice, inequality , , , , , , , ,

Apr 26 JDN 2458964

Suppose you were offered the choice of the following two gambles; which one would you take?

Gamble A: 99.9% chance of $0; 0.1% chance of $100 million

Gamble B: 10% chance of $50,000; 80% chance of $100,000; 10% chance of $1 million

I think it’s pretty clear that you should choose gamble B.

If you were risk-neutral, the expected payoffs would be $100,000 for gamble A and $185,000 for gamble B. So clearly gamble B is the better deal.

But you’re probably risk-averse. If you have logarithmic utility with a baseline and current wealth of $10,000, the difference is even larger:

0.001*ln(10001) = 0.009

0.1*ln(6) + 0.8*ln(11) + 0.1*ln(101) = 2.56

Yet suppose this is a gamble that a lot of people get to take. And furthermore suppose that what you read about in the news every day is always the people who are the very richest. Then you will read, over and over again, about people who took gamble A and got lucky enough to get the $100 million. You’d probably start to wonder if maybe you should be taking gamble A instead.

This is more or less the world we live in. A handful of billionaires own staggering amounts of wealth, and we are constantly hearing about them. Even aside from the fact that most of them inherited a large portion of it and all of them had plenty of advantages that most of us will never have, it’s still not clear that they were actually smart about taking the paths they did—it could simply be that they got spectacularly lucky.

Or perhaps there’s an even clearer example: Professional athletes. The vast majority of athletes make basically no money at sports. Even most paid athletes are in minor leagues and make only a modest living.

There’s certainly nothing wrong with being an amateur who plays sports for fun. But if you were to invest a large proportion of your time training in sports in the hopes of becoming a professional athlete, you would most likely find yourself gravely disappointed, as your chances of actually getting into the major leagues and becoming a multi-millionaire are exceedingly small. Yet you can probably name at least a few major league athletes who are multi-millionaires—perhaps dozens, if you’re a serious fan—and I doubt you can name anywhere near as many minor league players or players who never made it into paid leagues in the first place.

When we spend all of our time focused on the superstars, what we are effectively assessing is the maximum possible income available on a given career track. And it’s true; the maximum for professional athletes and especially entrepreneurs is extremely high. But the maximum isn’t what you should care about; you should really be concerned about the average or even the median.

And it turns out that the same professions that offer staggeringly high incomes at the very top also tend to be professions with extremely high risk attached. The average income for an athlete is very small; the median is almost certainly zero. Entrepreneurs do better; their average and median income aren’t too much worse than most jobs. But this moderate average comes with a great deal of risk; yes, you could become a billionaire—but far more likely, you could become bankrupt.

This is a deeply perverse result: The careers that our culture most glorifies, the ones that we inspire people to dream about, are precisely those that are the most likely to result in financial ruin.

Realizing this changes your perspective on a lot of things. For instance, there is a common lament that teachers aren’t paid the way professional athletes are. I for one am extremely grateful that this is the case. If teachers were paid like athletes, yes, 0.1% would be millionaires, but only 4.9% would make a decent living, and the remaining 95% would be utterly broke. Indeed, this is precisely what might happen if MOOCs really take off, and a handful of superstar teachers are able to produce all the content while the vast majority of teaching mostly amounts to showing someone else’s slideshows. Teachers are much better off in a world where they almost all make a decent living even though none of them ever get spectacularly rich. (Are many teachers still underpaid? Sure. How do I know this? Because there are teacher shortages. A chronic shortage of something is a surefire sign that its price is too low.) And clearly the idea that we could make all teachers millionaires is just ludicrous: Do you want to pay $1 million a year for your child’s education?

Is there a way that we could change this perverse pattern? Could we somehow make it feel more inspiring to choose a career that isn’t so risky? Well, I doubt we’ll ever get children to dream of being accountants or middle managers. But there are a wide range of careers that are fulfilling and meaningful while still making a decent living—like, well, teaching. Even working in creative arts can be like this: While very few authors are millionaires, the median income for an author is quite respectable. (On the other hand there’s some survivor bias here: We don’t count you as an author if you can’t get published at all.) Software engineers are generally quite satisfied with their jobs, and they manage to get quite high incomes with low risk. I think the real answer here is to spend less time glorifying obscene hoards of wealth and more time celebrating lives that are rich and meaningful.

I don’t know if Jeff Bezos is truly happy. But I do know that you and I are more likely to be happy if instead of trying to emulate him, we focus on making our own lives meaningful.

Why are humans so bad with probability?

PNRJ cognitive science, critique of neoclassical economics, statistics , , , , , , , , , , , ,

Apr 29 JDN 2458238

In previous posts on deviations from expected utility and cumulative prospect theory, I’ve detailed some of the myriad ways in which human beings deviate from optimal rational behavior when it comes to probability.

This post is going to be a bit different: Yes, we behave irrationally when it comes to probability. Why?

Why aren’t we optimal expected utility maximizers?
This question is not as simple as it sounds. Some of the ways that human beings deviate from neoclassical behavior are simply because neoclassical theory requires levels of knowledge and intelligence far beyond what human beings are capable of; basically anything requiring “perfect information” qualifies, as does any game theory prediction that involves solving extensive-form games with infinite strategy spaces by backward induction. (Don’t feel bad if you have no idea what that means; that’s kind of my point. Solving infinite extensive-form games by backward induction is an unsolved problem in game theory; just this past week I saw a new paper presented that offered a partial potential solution—and yet we expect people to do it optimally every time?)

I’m also not going to include questions of fundamental uncertainty, like “Will Apple stock rise or fall tomorrow?” or “Will the US go to war with North Korea in the next ten years?” where it isn’t even clear how we would assign a probability. (Though I will get back to them, for reasons that will become clear.)

No, let’s just look at the absolute simplest cases, where the probabilities are all well-defined and completely transparent: Lotteries and casino games. Why are we so bad at that?

Lotteries are not a computationally complex problem. You figure out how much the prize is worth to you, multiply it by the probability of winning—which is clearly spelled out for you—and compare that to how much the ticket price is worth to you. The most challenging part lies in specifying your marginal utility of wealth—the “how much it’s worth to you” part—but that’s something you basically had to do anyway, to make any kind of trade-offs on how to spend your time and money. Maybe you didn’t need to compute it quite so precisely over that particular range of parameters, but you need at least some idea how much $1 versus $10,000 is worth to you in order to get by in a market economy.

Casino games are a bit more complicated, but not much, and most of the work has been done for you; you can look on the Internet and find tables of probability calculations for poker, blackjack, roulette, craps and more. Memorizing all those probabilities might take some doing, but human memory is astonishingly capacious, and part of being an expert card player, especially in blackjack, seems to involve memorizing a lot of those probabilities.

Furthermore, by any plausible expected utility calculation, lotteries and casino games are a bad deal. Unless you’re an expert poker player or blackjack card-counter, your expected income from playing at a casino is always negative—and the casino set it up that way on purpose.

Why, then, can lotteries and casinos stay in business? Why are we so bad at such a simple problem?

Clearly we are using some sort of heuristic judgment in order to save computing power, and the people who make lotteries and casinos have designed formal models that can exploit those heuristics to pump money from us. (Shame on them, really; I don’t fully understand why this sort of thing is legal.)

In another previous post I proposed what I call “categorical prospect theory”, which I think is a decently accurate description of the heuristics people use when assessing probability (though I’ve not yet had the chance to test it experimentally).

But why use this particular heuristic? Indeed, why use a heuristic at all for such a simple problem?

I think it’s helpful to keep in mind that these simple problems are weird; they are absolutely not the sort of thing a tribe of hunter-gatherers is likely to encounter on the savannah. It doesn’t make sense for our brains to be optimized to solve poker or roulette.

The sort of problems that our ancestors encountered—indeed, the sort of problems that we encounter, most of the time—were not problems of calculable probability risk; they were problems of fundamental uncertainty. And they were frequently matters of life or death (which is why we’d expect them to be highly evolutionarily optimized): “Was that sound a lion, or just the wind?” “Is this mushroom safe to eat?” “Is that meat spoiled?”

In fact, many of the uncertainties most important to our ancestors are still important today: “Will these new strangers be friendly, or dangerous?” “Is that person attracted to me, or am I just projecting my own feelings?” “Can I trust you to keep your promise?” These sorts of social uncertainties are even deeper; it’s not clear that any finite being could ever totally resolve its uncertainty surrounding the behavior of other beings with the same level of intelligence, as the cognitive arms race continues indefinitely. The better I understand you, the better you understand me—and if you’re trying to deceive me, as I get better at detecting deception, you’ll get better at deceiving.

Personally, I think that it was precisely this sort of feedback loop that resulting in human beings getting such ridiculously huge brains in the first place. Chimpanzees are pretty good at dealing with the natural environment, maybe even better than we are; but even young children can outsmart them in social tasks any day. And once you start evolving for social cognition, it’s very hard to stop; basically you need to be constrained by something very fundamental, like, say, maximum caloric intake or the shape of the birth canal. Where chimpanzees look like their brains were what we call an “interior solution”, where evolution optimized toward a particular balance between cost and benefit, human brains look more like a “corner solution”, where the evolutionary pressure was entirely in one direction until we hit up against a hard constraint. That’s exactly what one would expect to happen if we were caught in a cognitive arms race.

What sort of heuristic makes sense for dealing with fundamental uncertainty—as opposed to precisely calculable probability? Well, you don’t want to compute a utility function and multiply by it, because that adds all sorts of extra computation and you have no idea what probability to assign. But you’ve got to do something like that in some sense, because that really is the optimal way to respond.

So here’s a heuristic you might try: Separate events into some broad categories based on how frequently they seem to occur, and what sort of response would be necessary.

Some things, like the sun rising each morning, seem to always happen. So you should act as if those things are going to happen pretty much always, because they do happen… pretty much always.

Other things, like rain, seem to happen frequently but not always. So you should look for signs that those things might happen, and prepare for them when the signs point in that direction.

Still other things, like being attacked by lions, happen very rarely, but are a really big deal when they do. You can’t go around expecting those to happen all the time, that would be crazy; but you need to be vigilant, and if you see any sign that they might be happening, even if you’re pretty sure they’re not, you may need to respond as if they were actually happening, just in case. The cost of a false positive is much lower than the cost of a false negative.

And still other things, like people sprouting wings and flying, never seem to happen. So you should act as if those things are never going to happen, and you don’t have to worry about them.

This heuristic is quite simple to apply once set up: It can simply slot in memories of when things did and didn’t happen in order to decide which category they go in—i.e. availability heuristic. If you can remember a lot of examples of “almost never”, maybe you should move it to “unlikely” instead. If you get a really big number of examples, you might even want to move it all the way to “likely”.

Another large advantage of this heuristic is that by combining utility and probability into one metric—we might call it “importance”, though Bayesian econometricians might complain about that—we can save on memory space and computing power. I don’t need to separately compute a utility and a probability; I just need to figure out how much effort I should put into dealing with this situation. A high probability of a small cost and a low probability of a large cost may be equally worth my time.

How might these heuristics go wrong? Well, if your environment changes sufficiently, the probabilities could shift and what seemed certain no longer is. For most of human history, “people walking on the Moon” would seem about as plausible as sprouting wings and flying away, and yet it has happened. Being attacked by lions is now exceedingly rare except in very specific places, but we still harbor a certain awe and fear before lions. And of course availability heuristic can be greatly distorted by mass media, which makes people feel like terrorist attacks and nuclear meltdowns are common and deaths by car accidents and influenza are rare—when exactly the opposite is true.

How many categories should you set, and what frequencies should they be associated with? This part I’m still struggling with, and it’s an important piece of the puzzle I will need before I can take this theory to experiment. There is probably a trade-off between more categories giving you more precision in tailoring your optimal behavior, but costing more cognitive resources to maintain. Is the optimal number 3? 4? 7? 10? I really don’t know. Even I could specify the number of categories, I’d still need to figure out precisely what categories to assign.

The right (and wrong) way to buy stocks

PNRJ financial advice, heuristics and biases , , , , , , , , , , , , , , , , , , ,

July 9, JDN 2457944

Most people don’t buy stocks at all. Stock equity is the quintessential form of financial wealth, and 42% of financial net wealth in the United States is held by the top 1%, while the bottom 80% owns essentially none.

Half of American households do not have any private retirement savings at all, and are depending either on employee pensions or Social Security for their retirement plans.

This is not necessarily irrational. In order to save for retirement, one must first have sufficient income to live on. Indeed, I got very annoyed at a “financial planning seminar” for grad students I attended recently, trying to scare us about the fact that almost none of us had any meaningful retirement savings. No, we shouldn’t have meaningful retirement savings, because our income is currently much lower than what we can expect to get once we graduate and enter our professions. It doesn’t make sense for someone scraping by on a $20,000 per year graduate student stipend to be saving up for retirement, when they can quite reasonably expect to be making $70,000-$100,000 per year once they finally get that PhD and become a professional economist (or sociologist, or psychologist or physicist or statistician or political scientist or material, mechanical, chemical, or aerospace engineer, or college professor in general, etc.). Even social workers, historians, and archaeologists make a lot more money than grad students. If you are already in the workforce and only expect to be getting small raises in the future, maybe you should start saving for retirement in your 20s. If you’re a grad student, don’t bother. It’ll be a lot easier to save once your income triples after graduation. (Personally, I keep about $700 in stocks mostly to get a feel for what it is like owning and trading stocks that I will apply later, not out of any serious expectation to support a retirement fund. Even at Warren Buffet-level returns I wouldn’t make more than $200 a year this way.)

Total US retirement savings are over $25 trillion, which… does actually sound low to me. In a country with a GDP now over $19 trillion, that means we’ve only saved a year and change of total income. If we had a rapidly growing population this might be fine, but we don’t; our population is fairly stable. People seem to be relying on economic growth to provide for their retirement, and since we are almost certainly at steady-state capital stock and fairly near full employment, that means waiting for technological advancement.

So basically people are hoping that we get to the Wall-E future where the robots will provide for us. And hey, maybe we will; but assuming that we haven’t abandoned capitalism by then (as they certainly haven’t in Wall-E), maybe you should try to make sure you own some assets to pay for robots with?

But okay, let’s set all that aside, and say you do actually want to save for retirement. How should you go about doing it?

Stocks are clearly the way to go. A certain proportion of government bonds also makes sense as a hedge against risk, and maybe you should even throw in the occasional commodity future. I wouldn’t recommend oil or coal at this point—either we do something about climate change and those prices plummet, or we don’t and we’ve got bigger problems—but it’s hard to go wrong with corn or steel, and for this one purpose it also can make sense to buy gold as well. Gold is not a magical panacea or the foundation of all wealth, but its price does tend to correlate negatively with stock returns, so it’s not a bad risk hedge.

Don’t buy exotic derivatives unless you really know what you’re doing—they can make a lot of money, but they can lose it just as fast—and never buy non-portfolio assets as a financial investment. If your goal is to buy something to make money, make it something you can trade at the click of a button. Buy a house because you want to live in that house. Buy wine because you like drinking wine. Don’t buy a house in the hopes of making a financial return—you’ll have leveraged your entire portfolio 10 to 1 while leaving it completely undiversified. And the problem with investing in wine, ironically, is its lack of liquidity.

The core of your investment portfolio should definitely be stocks. The biggest reason for this is the equity premium; equities—that is, stocks—get returns so much higher than other assets that it’s actually baffling to most economists. Bond returns are currently terrible, while stock returns are currently fantastic. The former is currently near 0% in inflation-adjusted terms, while the latter is closer to 16%. If this continues for the next 10 years, that means that $1000 put in bonds would be worth… $1000, while $1000 put in stocks would be worth $4400. So, do you want to keep the same amount of money, or quadruple your money? It’s up to you.

Higher risk is generally associated with higher return, because rational investors will only accept additional risk when they get some additional benefit from it; and stocks are indeed riskier than most other assets, but not that much riskier. For this to be rational, people would need to be extremely risk-averse, to the point where they should never drive a car or eat a cheeseburger. (Of course, human beings are terrible at assessing risk, so what I really think is going on is that people wildly underestimate the risk of driving a car and wildly overestimate the risk of buying stocks.)

Next, you may be asking: How does one buy stocks? This doesn’t seem to be something people teach in school.

You will need a brokerage of some sort. There are many such brokerages, but they are basically all equivalent except for the fees they charge. Some of them will try to offer you various bells and whistles to justify whatever additional cut they get of your trades, but they are almost never worth it. You should choose one that has a low a trade fee as possible, because even a few dollars here and there can add up surprisingly quickly.

Fortunately, there is now at least one well-established reliable stock brokerage available to almost anyone that has a standard trade fee of zero. They are called Robinhood, and I highly recommend them. If they have any downside, it is ironically that they make trading too easy, so you can be tempted to do it too often. Learn to resist that urge, and they will serve you well and cost you nothing.

Now, which stocks should you buy? There are a lot of them out there. The answer I’m going to give may sound strange: All of them. You should buy all the stocks.

All of them? How can you buy all of them? Wouldn’t that be ludicrously expensive?

No, it’s quite affordable in fact. In my little $700 portfolio, I own every single stock in the S&P 500 and the NASDAQ. If I get a little extra money to save, I may expand to own every stock in Europe and China as well.

How? A clever little arrangement called an exchange-traded fund, or ETF for short. An ETF is actually a form of mutual fund, where the fund purchases shares in a huge array of stocks, and adjusts what they own to precisely track the behavior of an entire stock market (such as the S&P 500). Then what you can buy is shares in that mutual fund, which are usually priced somewhere between $100 and $300 each. As the price of stocks in the market rises, the price of shares in the mutual fund rises to match, and you can reap the same capital gains they do.

A major advantage of this arrangement, especially for a typical person who isn’t well-versed in stock markets, is that it requires almost no attention at your end. You can buy into a few ETFs and then leave your money to sit there, knowing that it will grow as long as the overall stock market grows.

But there is an even more important advantage, which is that it maximizes your diversification. I said earlier that you shouldn’t buy a house as an investment, because it’s not at all diversified. What I mean by this is that the price of that house depends only on one thing—that house itself. If the price of that house changes, the full change is reflected immediately in the value of your asset. In fact, if you have 10% down on a mortgage, the full change is reflected ten times over in your net wealth, because you are leveraged 10 to 1.

An ETF is basically the opposite of that. Instead of its price depending on only one thing, it depends on a vast array of things, averaging over the prices of literally hundreds or thousands of different corporations. When some fall, others will rise. On average, as long as the economy continues to grow, they will rise.

The result is that you can get the same average return you would from owning stocks, while dramatically reducing the risk you bear.

To see how this works, consider the past year’s performance of Apple (AAPL), which has done very well, versus Fitbit (FIT), which has done very poorly, compared with the NASDAQ as a whole, of which they are both part.

AAPL has grown over 50% (40 log points) in the last year; so if you’d bought $1000 of their stock a year ago it would be worth $1500. FIT has fallen over 60% (84 log points) in the same time, so if you’d bought $1000 of their stock instead, it would be worth only $400. That’s the risk you’re taking by buying individual stocks.

Whereas, if you had simply bought a NASDAQ ETF a year ago, your return would be 35%, so that $1000 would be worth $1350.

Of course, that does mean you don’t get as high a return as you would if you had managed to choose the highest-performing stock on that index. But you’re unlikely to be able to do that, as even professional financial forecasters are worse than random chance. So, would you rather take a 50-50 shot between gaining $500 and losing $600, or would you prefer a guaranteed $350?

If higher return is not your only goal, and you want to be socially responsible in your investments, there are ETFs for that too. Instead of buying the whole stock market, these funds buy only a section of the market that is associated with some social benefit, such as lower carbon emissions or better representation of women in management. On average, you can expect a slightly lower return this way; but you are also helping to make a better world. And still your average return is generally going to be better than it would be if you tried to pick individual stocks yourself. In fact, certain classes of socially-responsible funds—particularly green tech and women’s representation—actually perform better than conventional ETFs, probably because most investors undervalue renewable energy and, well, also undervalue women. Women CEOs perform better at lower prices; why would you not want to buy their companies?

In fact ETFs are not literally guaranteed—the market as a whole does move up and down, so it is possible to lose money even by buying ETFs. But because the risk is so much lower, your odds of losing money are considerably reduced. And on average, an ETF will, by construction, perform exactly as well as the average performance of a randomly-chosen stock from that market.

Indeed, I am quite convinced that most people don’t take enough risk on their investment portfolios, because they confuse two very different types of risk.

The kind you should be worried about is idiosyncratic risk, which is risk tied to a particular investment—the risk of having chosen the Fitbit instead of Apple. But a lot of the time people seem to be avoiding market risk, which is the risk tied to changes in the market as a whole. Avoiding market risk does reduce your chances of losing money, but it does so at the cost of reducing your chances of making money even more.

Idiosyncratic risk is basically all downside. Yeah, you could get lucky; but you could just as well get unlucky. Far better if you could somehow average over that risk and get the average return. But with diversification, that is exactly what you can do. Then you are left only with market risk, which is the kind of risk that is directly tied to higher average returns.

Young people should especially be willing to take more risk in their portfolios. As you get closer to retirement, it becomes important to have more certainty about how much money will really be available to you once you retire. But if retirement is still 30 years away, the thing you should care most about is maximizing your average return. That means taking on a lot of market risk, which is then less risky overall if you diversify away the idiosyncratic risk.

I hope now that I have convinced you to avoid buying individual stocks. For most people most of the time, this is the advice you need to hear. Don’t try to forecast the market, don’t try to outperform the indexes; just buy and hold some ETFs and leave your money alone to grow.

But if you really must buy individual stocks, either because you think you are savvy enough to beat the forecasters or because you enjoy the gamble, here’s some additional advice I have for you.

My first piece of advice is that you should still buy ETFs. Even if you’re willing to risk some of your wealth on greater gambles, don’t risk all of it that way.

My second piece of advice is to buy primarily large, well-established companies (like Apple or Microsoft or Ford or General Electric). Their stocks certainly do rise and fall, but they are unlikely to completely crash and burn the way that young companies like Fitbit can.

My third piece of advice is to watch the price-earnings ratio (P/E for short). Roughly speaking, this is the number of years it would take for the profits of this corporation to pay off the value of its stock. If they pay most of their profits in dividends, it is approximately how many years you’d need to hold the stock in order to get as much in dividends as you paid for the shares.

Do you want P/E to be large or small? You want it to be small. This is called value investing, but it really should just be called “investing”. The alternatives to value investing are actually not investment but speculation and arbitrage. If you are actually investing, you are buying into companies that are currently undervalued; you want them to be cheap.

Of course, it is not always easy to tell whether a company is undervalued. A common rule-of-thumb is that you should aim for a P/E around 20 (20 years to pay off means about 5% return in dividends); if the P/E is below 10, it’s a fantastic deal, and if it is above 30, it might not be worth the price. But reality is of course more complicated than this. You don’t actually care about current earnings, you care about future earnings, and it could be that a company which is earning very little now will earn more later, or vice-versa. The more you can learn about a company, the better judgment you can make about their future profitability; this is another reason why it makes sense to buy large, well-known companies rather than tiny startups.

My final piece of advice is not to trade too frequently. Especially with something like Robinhood where trades are instant and free, it can be tempting to try to ride every little ripple in the market. Up 0.5%? Sell! Down 0.3%? Buy! And yes, in principle, if you could perfectly forecast every such fluctuation, this would be optimal—and make you an almost obscene amount of money. But you can’t. We know you can’t. You need to remember that you can’t. You should only trade if one of two things happens: Either your situation changes, or the company’s situation changes. If you need the money, sell, to get the money. If you have extra savings, buy, to give those savings a good return. If something bad happened to the company and their profits are going to fall, sell. If something good happened to the company and their profits are going to rise, buy. Otherwise, hold. In the long run, those who hold stocks longer are better off.