Searching For Eden

By Robin Hanson · December 5, 2020 1:40 pm · Comments (0)

In my last post, I reviewed the standard theory that life on Earth got very lucky to complete a series of hard try-try steps to get to our human level before its window for life closes. I said that this theory has had only mixed success in predicting Earth history timings, and does noticeably badly in predicting that Earth should score well on the key figure of merit of (V*M*W)N, for number of hard try-try steps N, volume V, metabolism M, and time window W not used for easy steps. This seems a pretty big deal, as this is a pretty basic theory on a pretty important process. If we are very wrong about it, that’s important to know. (Just as its important to get to the bottom of credible UFO sightings.)

This evidence conflict might be tolerably weak if one only estimated N=1, one very hard step. But, I said, life designs look so complex and well-integrated that I estimate at least ten hard steps, much more than the few perhaps seen in Earth’s fossil record. This graph conveys a similar intuition, suggesting that those added hard steps happened either as many try-once steps very early in Earth history, or as many try-try steps before Earth.

In my last post, I suggested that this conflict could at least be cut by positing many hard try-once steps, instead of the usual hard try-try steps, early in Earth’s history. But now I’ll admit I don’t think that is enough. I find it hard to believe that more than half of (the integrated magnitude of) hard steps are of the try-once sort, and yet even N=5 gives a quite strong evidence conflict. So I’m forced to take seriously panspermia, the hypothesis that life had another oasis before Earth, and was transferred from that oasis to Earth very early in Earth’s history. Call that prior oasis “Eden”.

Yes, interstellar panspermia seems hard and risky, in effect adding another try-once great filter step which life must compete. Here’s a recent estimate:

But if this scenario allows an Eden with a figure of merit as large as Earth’s, and if there are R times as may oases that could support the more robust early sort of life, relative to the more fragile multicellular sort that comes later, then the relative chance of this Eden scenario, compared to just-Earth, is a factor of R*2N times the chance that Eden could successfully transfer life to another (any other) suitable oasis. If Eden’s volume were instead twice as big as Earth’s, that would be R*3N, etc. So even a small chance to transfer to another oasis could be more than compensated by such a factor.

If there really was an Eden, then finding it is likely to become one of the great historical quests of our descendants. So what can we say about Eden now, to advise this quest? Here are some clues:

  1. Until we replace our usual theory, we still probably want to use the usual figure of merit to predict Eden. Except that the time deadline for delivering life to Earth says that the time window W can only be extended by having an oasis that starts earlier. So Eden likely meets the usual constraints (like temperature), has a large volume V and metabolism M, and started early.
  2. The more try-try hard steps that happened on Eden, as opposed to on Earth, the weaker is the evidence conflict re Earth. So maybe most such steps happened on Eden.
  3. Eden mainly needs to give rise to single-cell extremophiles that could travel well enough. So it needn’t support fragile multicellular life, and may work better if it has high (but not overly high) variability to encourage the evolution of robustness. So there is a substantial R factor.
  4. Eventually, Eden would have been home to the sort of life that gave rise to our sort of life. With carbon, water, and DNA. So that rejects exotic hypothesized life such as made of silicon, or in plasmas or neutron stars.
  5. This robust single-celled life seems much less vulnerable to the gamma ray bursts, supernova, and asteroids that tend to kill off fragile life like us close to the galactic center. Or to the large solar flares common near red dwarf stars. So while Earth was not allowed there, Eden is allowed in such places.
  6. Panspermia gets easier in places where stars are closer together, as toward the galactic center. So all else equal, expect Eden in such places.
  7. However, if dormant cells only survive between stars for a million years, then if its dust or rock travel host moved at a typical relative velocity of 30km/s, it could only travel 100 light years in that time, which doesn’t get you far in the galaxy. Thus either Eden was quite near to Earth when Earth acquired life, or dormant life can last much longer, or hosts could fly much faster.
  8. The usual analysis of interstellar panspermia gets pretty low rates. But the chance of panspermia should be increased by the density of stuff flying around near the travel origin and destination locations. Such stuff can kick up life from Eden, and help grab stuff traveling past Earth. Earth had lots of stuff flying about in its new solar system formed, and that was embedded in larger complex turbulent dynamic molecular clouds which had more stuff flying about. So if Eden was close to Earth then, Eden was plausibly in a similar cloud area then, which helped induce the travel origin. Seems worth analyzing how molecular clouds change panspermia rates.
  9. Life could have continued on Eden long after it sent life to Earth, but the selection effect of seeing our existence doesn’t enhance the chance of that. The higher is our estimate of the number of oases to which Eden life would have spread, the easier it will be to find such life out there. But unless that chance is enormous, we expect Eden and any of its other descendants to be quite hard to find. Stars that are siblings of our Sun, born in the same nursery, seem good candidates to look at.
  10. The hypothesis of two prior oases in sequence, instead of one, would also be penalized by a low chance of transfer between them, but might allow a larger total time window W, and a boost in R via more possible oases. Furthermore, this scenario might allow a split wherein try-try steps happen in the oasis with a large figure of merit, but try-once steps happen in multiple parallel small oases, giving them a larger chance of success.
  11. Life in the atmosphere of a brown drawf seems an interesting possibility, but it seems harder for passing stuff to kick out or grab life from such a reservoir. Those things are easier for life on a planet near a red dwarf, but those may suffer too much variability.
  12. Life may have been possible in a few places 10-17 million years after the Big Bang, from heavy elements formed by supernovae in rare star-forming fluctuation regions that constitute ~10-17 of all matter.
  13. (I’ll add more here as I or others suggest them.)
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Try-Try or Try-Once Great Filter?

By Robin Hanson · December 3, 2020 9:00 pm · Comments (1)

Here’s a simple and pretty standard theory of the origin and history of life and intelligence. Life can exist in a supporting oasis (e.g., Earth’s surface) that has a volume V and metabolism M per unit volume, and which lasts for a time window W between forming and then later ending. This oasis makes discrete “advances” between levels over time, and at any one time the entire oasis is at the same level. For example, an oasis may start at the level of simple dead chemical activity, may later rise to a level that counts as “life”, then rise to a level that includes “intelligence”, and finally to a level where civilization makes a big loud noises that are visible as clearly artificial from far away in the universe.

There can be different kinds of levels, each with a different process for stepping to the next level. For example, at a “delay” level, the oasis takes a fixed time delay D to move to the next level. At a “try once” level, the oasis has a particular probability of immediately stepping to the next level, and if it fails at that it stays forever “stuck”, which is equivalent to a level with an infinite delay. And at a “try try” level, the oasis stays at a level while it searches for an “innovation” to allow it to step to the next level. This search produces a constant rate per unit time of jumping. As an oasis exists for only a limited window W, it may never reach high levels, and in fact may never get beyond its first try-try level.

If we consider a high level above many hard try-try levels, and with small enough values of V,M,W, then any one oasis may have a very small chance of “succeeding” at reaching that high level before its window ends. In this case, there is a “great filter” that stands between the initial state of the oasis and a final success state. Such a success would then only tend to happen somewhere if there are enough similar oases going through this process, to overcome these small odds at each oasis. And if we know that very few of many similar such oases actually succeed, then we know that each must face a great filter. For example, knowing that we humans now can see no big loud artificial activity for a very long distance from us tells us that planets out there face a great filter between their starting level and that big loud level.

Each try-try type level has an expected time E to step to the next level, a time that goes inversely as V*M. After all, the more volume there is of stuff that tries, and faster its local activity, the more chances it has to find an innovation. A key division between such random levels is between ones in which this expected time E is much less than, or much greater than, the oasis window W. When E << W, these jumps are fast and “easy”, and so levels change relatively steadily over time, at a rate proportional to V*M. And when E >> W, then these jumps are so “hard” that most oases never succeed at them.

Let us focus for now on oases that face a great filter, have no try-once steps, and yet succeed against the odds. There are some useful patterns to note here. First, let’s set aside S, the sum of the delays D for delay steps, and of the expected times E for easy try-try steps, for all such steps between the initial level and the success level. Such an oasis then really only has a time duration of about W-S to do all its required hard try-try steps.

The first pattern to note is that the chance that an oasis does all these hard steps within its window W is proportional to (V*M*(W-S))N, where N is the number of these hard steps needed to reach its success level. So if we are trying to predict which of many differing oases is mostly likely to succeed, this is the formula to use.

The second pattern to note is that if an oasis succeeds in doing all its required hard steps within its W-S duration, then the time durations required to do each of the hard steps are all drawn from the same (roughly exponential) distribution, regardless of the value of E for those steps! Also, the time remaining in the oasis after the success level has been reached is also drawn from this same distribution. This makes concrete predictions about the pattern of times in the historical record of a successful oasis.

Now let’s try to compare this theory to the history of life on Earth. The first known fossils of cells seems to be from 0.1-0.5 Ga (billion years) after life would be possible on Earth, which happened about 4.2 Gya (billion years ago), which was about 9.6 Ga after the universe formed. The window remaining for (eukaryotic) life to remain on Earth seems 0.8-1.5 Ga. The relatively steady growth in max brain sizes since multi-cellular life arose 0.5 Gya suggests that during this period there were many easy, but no hard, try-try steps. Multi-celluar life seems to require sufficient oxygen in the atmosphere, but the process of collecting enough oxygen seems to have started about 2.4 Gya, implying a long 1.9 Ga delay step. Prokaryotes started exchanging genes about 2.0 Gya, eukaryotes appeared about 1.7 Gya, and modern sex appeared about 1.2 Gya. These events may or may not have been the result of successful try-try steps.

Can we test this history against the predictions that try-try hard step durations, and the window time remaining, should all be drawn from the same roughly exponential distribution? Prokaryote sex, eukaryotes, and modern sex all appeared within 0.8 Ga, which seems rather close together, and leaving a long uneventful period of almost ~2 Ga before them. The clearest hard step duration candidates are before the first life, which took 0.0-0.5 Ga, and the window remaining of 0.8-1.5 Ga, which could be pretty different durations. Overall I’d say that while this data isn’t a clear refutation of the same hard step distribution hypothesis, it also isn’t that much of a confirmation.

What about the prediction that the chance of oasis success is proportional to (V*M*(W-S))N? The prediction about Earth is that it will tend to score high on this metric, as Earth is the only example of success that we know.

Let’s consider some predictions in turn, starting with metabolism M. Life of the sort that we know seems to allow only a limited range of temperatures, and near a star that requires a limited range of distances from the star, which then implies a limited range of metabolisms M. As a result of this limited range of possible M, our prediction that oases with larger M will have higher chances of success doesn’t have much room to show itself. But for what its worth, Earth seems to be nearer to the inner than outer edge of the Sun’s allowable zone, giving it a higher value of M. So that’s a weak confirmation of the theory, though it would be stronger if the allowed zone range were larger than most authors now estimate.

What about volume V? The radii of non-gas-giant planets seems to be lognormally distributed, with Earth at the low end of the distribution (at a value of 1 on this axis):

So there are many planets out there (at r=4) with 16 times Earth’s surface area, and with 64 times the volume, ratios that must be raised to the power of N to give their advantage over Earth. And these larger planets are made much more of water than is Earth. This seems to be a substantial, if perhaps not overwhelming, disconfirmation of the prediction that Earth would score high on VN. The higher is the number of hard steps N, the stronger is this disconfirmation.

Regarding the time window W, I see three relevant parameters: when a planet’s star formed, how long that star lasts, and how often there are supernova nearby that destroy all life on the planet. Regarding star lifetimes, main sequence star luminosity goes as mass to the fourth power, which implies that star lifetimes go inversely as mass to the third power. And as the smallest viable stars have 0.08 of our sun’s mass, that implies that there are stars with over 1000 times the Sun’s lifetime, an advantage that must again be raised to the power N. And there are actually a lot more such stars, 10-100 times more than of the Sun’s size:

However, the higher metabolism of larger mass stars gives them a spatially wider habitable zone for planets nearby, and planets near small stars are said to face other problems; how much does that compensate? And double stars should also offer wider habitable zones; so why is our Sun single?

Now what if life that appears near small long-lived stars would appear too late, as life that appeared earlier would spread and take over? In this case, we are talking about a race to see which oases can achieve intelligence or big loud civilizations before others. In which case, the prediction is that winning oases are the ones that appeared first in time, as well has having good metrics of V,M,W.

Regarding that, here are estimates of where the habitable stars appear in time and galactic radii, taking into account both star formation rates and local supernovae rates (with the Sun’s position shown via a yellow star):

As you can see, our Sun is far from the earliest, and its quite a bit closer to galactic center than is ideal for its time. And if the game isn’t a race to be first, our Sun seems much earlier than is ideal (these estimates are arbitrarily stopped at 10Ga).

Taken together, all this seems to me to give a substantial disconfirmation of the theory that chance of oasis success is proportional to (V*M*(W-S))N, a disconfirmation that gets stronger the larger is N. So depending on N, maybe not an overwhelming disconfirmation, but at least substantial and worrisome. Yes, we might yet discover more constraints on habitability to explain all these, but until we find them, we must worry about the implications of our analysis of the situation as we best understand it.

So what alternative theories do we have to consider? In this post, I’d like to suggest replacing try-try steps with try-once steps in the great filter. These might, for example, be due to evolution’s choices of key standards, such as the genetic code, choices that tend to lock in and get entrenched, preventing competing standards from being tried. The overall chance of success with try-once steps goes as the number of oases, and is independent of oasis lifetime, volume, or metabolism, favoring many small oases relative to a few big ones. With more try-once steps, we need fewer try-try steps in the great filter, and thus N gets slower, weakening our prediction conflicts. In addition, many try-once steps could unproblematically happen close to each other in time.

This seems attractive to me because I estimate there to be in fact a great many rather hard steps. Say at least ten. This is because the design of even “simple” single cell organisms seems to me amazingly complex and well-integrated. (Just look at it.) “Recent” life innovations like eukaryotes, different kinds of sex, and multicellular organisms do involved substantial complexity, but the total complexity of life seems to me far larger than these. And while incremental evolution is capable of generating a lot of complexity and integration, I expect that what we see in even the simplest cells must have involved a lot of hard steps, of either the try-once or the try-try type. And if they are all try-try steps, that makes for a huge N, which makes the prediction conflicts above very difficult to overcome.

Well that’s enough for this post, but I expect to have more to say on the subject soon.

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Keep Govt Officials Out of Life Details

By Robin Hanson · November 30, 2020 4:50 pm · Comments (0)

The government can meddle in your life both via both your production and consumption. That is, it can tell you how much of what to produce, and how to do that, and it can tell you how much of what to consume, and how to do that. These meddlings can be general and uniform across the population, and decided by a legislature. Or they can make more distinctions between people, and be decided by low level government employees.

For example, the government can subsidize fresh fruits and vegetables in general, for everyone, or Ms. Jones’ social worker might tell her that if she wants to keep her kids she better serve more fresh spinach to her children at dinner this week. The government can require everyone to pay the same fraction of their income in taxes, or a draft board can choose to conscript Mr. Jones into becoming a solider, and then his sargent can order him to take that hill now.

While we might disagree on where we would draw the line, I think we can all agree that, all else equal, it is better if the government decides at a high level to meddle uniformly in everyone’s lives, than if low level government employees meddle very specifically in particular details of individual lives. While an unregulated society most likely does have market failures that legislatures can mitigate via general rules, it is harder to believe that low level employees know enough about particular people to meddle well in their details. Furthermore, detailed meddling allows more corruption and arrogance by officials, and induces more hurt pride and resistance by those controlled.

We can, I think, go further and agree that it seems harder to justify meddling in production, relative to consumption. For example, we may accept the government using a general rule to tell us how much we owe in taxes, but it seems harder to accept a government official telling us in particular what kind of career to go into, what job to take, or whether we must work this Saturday. Regulations about job safety, for example, work better as general rules that apply to all jobs, rather than being chosen at the discretion of a particular official regarding a particular workplace.

I propose that we all think about law vouching in this context. Just as a government who decides how much you owe in taxes does not decide how you acquire that money, a government who decides that you owe a legal debt due to a crime you’ve committed need not be empowered to decide how you pay that debt, if that you will in fact pay that debt.

In our world today, the judge who sentences a criminal not only decides the overall level of their “debt owed to society”, but also specifies the particular kind of punishment. Usually prison, but sometimes fines or community service. (And in the past: public shaming, torture, exile, or death.). And our governments and courts regulate those prisons in great detail. Even so, prisons are terribly expensive and yet not very effective at deterring crime. And as you leave prison, your parole board and officer will make many detailed decisions on how you can live your life.

Under vouching, there is no government parole officer and the judge would instead only specify the fine your owe, which would be paid by your voucher. (And could depend on your wealth.) Then you would be further punished according to your prior contract with your voucher. You and your voucher would also choose your privacy rights and freedoms of actions, and suffer larger fines if those make it harder to catch and convict your crimes. Furthermore, you and some close friends could together choose co-liability, to show you will watch each other.

Under vouching, you would repay your debt to society, and be in much more in control of how to repay that debt. Just as with tax debts now. Does anyone really think that judges, police, or prison officials are extra good at deciding what will deter crime in any one individual? Moreso than all the other government officials who we do not let dictate the details of our lives?

Not that I’m not pushing for some extreme libertopia where government has no powers. I’m instead appealing to a quite common feeling that government meddling should be limited and general; our default should be to avoid it, when possible.

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Why We Fight Over Fiction

By Robin Hanson · November 29, 2020 9:20 am · Comments (1)

We tell stories with language, and so prefer to tell the kind of stories that ordinary language can describe well.

Consider how language can describe a space of physical stuff and how to navigate through that stuff. In a familiar sort of space, a few sparse words can evoke a vivid description, such as of a city street or a meadow. And a few words relating to landmarks in such a space can be effective at telling you how to navigate from one place to another.

But imagine an arbitrary space of partially-opaque swirling strangeness, in a highly curved 11-dimensional space. In principle our most basic and general spatial language could describe this too, and instruct navigation there. But in practice that would require a lot more words, and slow the story to a crawl. So few authors would try, though a filmmaker might try just using visuals.

Or consider stories with non-human minds. In principle those who study minds in the abstract can conceive of a vast space of possible minds, and can use a basic and general language of mental acts to describe how each such mind might make a decision, or send a communication, and what those might be. But in practice such descriptions would be long, boring, and unfamiliar to most readers.

So in practice even authors writing about aliens or AIs stick to describing human-like minds, where their usual language for describing what actors decide and say is fast, fluid, and relatable. Authors even prefer human characters with familiar minds, and so avoid characters who think oddly, such as those with autism.

Just as authors focus on telling stories in familiar spaces with familiar minds, they also focus on telling stories in familiar moral universes. This effect is, if anything, even stronger than the space and mind effects, as moral colors are even more central to our need for stories. Compared to other areas of our lives, we especially want our stories to help us examine and affirm our moral stances.

In a familiar moral universe, there many be competing considerations re what acts are moral, making it sometimes hard to decide if an act is moral. Other considerations may weigh against morality, and reader/viewers may not always sympathize most with the most moral characters, who may not win in the end. Moral characters may have unattractive features (like being ugly). There may even be conflicts between characters who see different familiar moral universes.

These are the familiar sorts of “moral ambiguity” in stories said to have that feature, such as The Sopranos or Game of Thrones. But you’ll note that these are almost all stories told in familiar moral universes. By which I mean that we are quite familiar with how to morally evaluate the sort of actions that happen there. The set of acts is familiar, as are their consequences, and the moral calculus used to judge them.

But there is another sort of “moral ambiguity” that reader/viewers hate, and so authors studiously avoid. And that is worlds where we find it hard to judge the morality of actions, even when those actions have big consequences for characters. Where our usual quick and dirty moral language doesn’t apply very well. Where even though in principle our most basic and general moral languages might be able to work out rough descriptions and evaluations, in practice that would be tedious and unsatisfying.

And, strikingly, the large complex social structures and organizations that dominate our world are mostly not familiar moral universes to most of us. For example, big firms, agencies, and markets. The worlds of Moral Mazes and of Pfeffer’s Power. (In fiction: Jobs.) Our stories thus tend to avoid such contexts, unless they happen to allow an especially clear moral calculus. Such as a firm polluting to cause cancer, or a boss sexually harassing a subordinate.

As I’ve discussed before, our social world has changed greatly over the last few centuries. Our language has changed fast enough to describe the new physical objects and spaces that have arisen, at least those with which ordinary people must deal, if not the many new strange objects and spaces behind the scenes that enable our new world. But we have not gone remotely as fast at coming to agree on moral stances toward the new choices possible in such social structures.

This is why our stories tend to take place in relatively old fashioned social worlds. Consider the popularity of the Western, or of pop science fiction stories like Star Wars that are essentially Westerns with more gadgets. Stories that take place in modern settings tend to focus on personal, romantic, and family relations, as these remain to us relatively familiar moral universes. Or on artist biopics. Or on big conflicts like war or corrupt police or politicians. For which we have comfortable moral framings.

Stories we write today set in say the 1920s feel to us more comfortable than do stories set in the 2020s, or than stories written in the 1920s and set in that time. That is because stories written today can inherit a century of efforts to work out clearer moral stances on which 1920s actions would be more moral. For example, as to our eyes female suffrage is clearly good, we can see any characters from then who doubted it as clearly evil in the eyes of good characters. As clear as if they tortured kittens. To our eyes, their world has now clearer moral colors, and stories set there work better as stories for us.

This is also why science fiction tends to make most people more wary of anticipated futures. The easiest engaging stories to tell about strange futures are on how acts there that seem to violate the rules in our current moral universe. Like about how nuclear rockets spread radioactivity near their launch site, instead of the solar civilization they enable. Much harder to describe how new worlds will induce new moral universes.

This highlights an important feature of our modern world, and an important process that continues within it. Our social world has changed a lot faster than has our shared moral evaluations of typical actions possible in our new world. And our telling stories, and coming to agree on which stories we embrace, is a big part of creating such a fluid language of shared moral evaluations.

This helps to explain why we invest so much time and energy into fiction, far more than did any of our ancestors. Why story tellers are given high and activist-like status, and why we fight so much to convince others to share our beliefs on which stories are best. Our moral evaluations of the main big actions that influence our world today, and that built our world from past worlds, are still up for grabs. And the more we build such shared evaluations, the more we’ll be able to tell satisfying stories set in the world in which we live, rather than set in the fantasy and historical worlds with which we must now make do.

(This post is an elaboration of this Twitter thread.)

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Hidden Motives of Gratitude

By Robin Hanson · November 27, 2020 8:54 pm · Comments (0)

I recently got 568 Twitter folk to say which of these 4 things they are most thankful for:

Assume first that one is most thankful for the process which increased your gains by the highest ratio, relative to prior expectations. If we are just talking about such a degree of selectivity into a better position, then it seems to me that the first answer is obviously best: there are vastly more possible than actual creatures. If you get zero value from not existing, but a positive value from existing, and your prior odds of existing were tiny, then your gain ratio is astronomical.

However, some insist that they can only compare scenarios where they exist, and so reject the counterfactual possibility that they might not have existed. For them, the second option seems obviously the most selective among the remaining three. Humans are clearly enormously special compared to the vast number of species who will ever exist. For example, far more special than are humans in any one place and time compared to humans in others.

What if the goal of a poll respondent isn’t to identify the option from which they benefited more, but instead to use this poll as an opportunity to signal something about themselves. (Other than literal understanding and honesty.) The apparently most useful thing to signal then would be loyalty to one’s immediate associates, and confidence in one’s local roles. In which case the last poll option seems obviously best.

But oddly, 48% of poll respondents picked the third option! What goal could explain that choice? One possibility is that they sought to signal their “patriotism” toward their place and time in human history. People in different places often feel rivalrous toward each other. Different nations are in different places, and even within nations different culture, ethnic, and political “factions” tend to be in different places.

What about your time in history? Well first, there is less rivalry of feeling between different times, and less to gain by signaling loyalty to your time. Furthermore, if you think you’ve seen a trend in history toward times getting better, to make your time the best so far, you should expect the future to get even better, making your time not so great compared to all the times, past and future. So I suspect that many overt time affiliations are actually covert political affiliations.

Thus I’m led to conclude that the strongest motive in choosing what to be most thankful for is signaling loyalty to one’s region. Nationalism, racism, political alignment, and cultural rivalry. If you encourage people to be more grateful, that’s what you will be encouraging. Not what I would have guessed, but I guess not so crazy either.

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The Pandemic Monkey Trap

By Robin Hanson · November 27, 2020 4:45 pm · Comments (1)

Back in 2007 I said “cut medicine in half”, as its marginal value is too low. (Since then, US spending is up 40%!) But prestigious health economists said yes on average marginal value is low, but don’t I agree that some identified treatments have high value, and as there must be more like that, we should wait and not cut until we can identify which are high vs low. I say cut now, and only add back good things once you can identify them. Those hidden good treatments are the nut in a medical monkey trap, which prevents us from letting go of a larger gourd of wasteful spending.

My colleague Bryan Caplan says we should cut school spending, as its social value is on average low. Many critics say yes value may be low now, but it must be possible to create high value school programs, and so instead of cutting we should work on figuring how to increase school value. Caplan says to cut now, and only add back spending when you can actually identify high value programs.

Regarding pandemic prevention spending, both Caplan and I say that we seem to be spending way too much, and so we should cut back.

Me in October:

I’m comfortable with … an estimate of 3.0 [for the ratio of life-year value over annual income]. But … [that gives] $1.08T and $0.64T for covid death and impairment harms, which gives a prevention to harm cost ratio of 5.31. (Which is close to the 5.2 median estimate from my most recent poll.) And its crazy to think that on average we are getting a 5.31% cut in covid harm for each 1% increase in prevention cost we pay! But that’s what it would take to justify this level of prevention spending.

Bryan Caplan on Tuesday:

total loss comes to about 37 million years of life. That’s about 15 times the reported estimate of the direct cost of COVID. … If normal life had continued unabated since March, how many additional life-years would have been lost? … fifteen times? No way. Upshot: The total cost of all COVID prevention has very likely exceeded the total benefit of all COVID prevention.

Tyler Cowen today:

I don’t agree with Bryan’s numbers, but the more important point is one of logic. The higher the costs of reaction to Covid, the stronger the case for subsidizing vaccines, therapeutics, and other corrective measures. Would you accept this Bryan? You have numerous posts about risk overreaction, but not one (if I recall correctly) calling for such subsidies. …

A second question is whether moral suasion — “don’t overreact to Covid!” — is likely to prove effective. … Sweden didn’t do any better on the gdp front, and the country had pretty typical adverse mobility reactions. … Brazil … have a denialist president, a weak overall response, and a population used to a high degree of risk. … about overreaction. What kinds of reaction are you expecting or viewing as feasible and attainable? If overreacting is indeed a public bad, why think you can talk people down out of it? … they don’t and indeed can’t tell you how most of those [overreaction] costs were to be avoided, given how the public reacts to risk. …

If we instead look to the relevant changes in relative prices, that means subsidies for vaccines and tests, most of all through advance market commitments, but not only. And a full-scale commitment to implementing testing and masks and therapeutics. The more you push home points about overreaction, the more you ought to favor these subsidies. Libertarians out there, do you? This chicken has come home to roost, so please fess up and give the right answer here. Do you favor these subsidies?

Cowen seems to divide pandemic prevention into two categories, the first of which is ineffective but simply cannot be avoided, while the second is highly effective and can in fact be changed, if only people like Bryan would speak up. In this case, the more there is of unavoidable ineffective prevention, the more valuable it is to spend more on effective prevention.

I question Cowen’s arbitrary claim that we intellectuals can only influence spending on very effective kinds of treatment, but not on others. We see variations in both kinds of policy across space and time, due both to private and government choices, all of which seem modestly influenceable by intellectuals like Caplan, Cowen, and I. There are people out there arguing to cut ineffective prevention, as well as people arguing to expand effective prevention, and both groups deserve our support. (“Spending” includes all choices that induce opportunity costs.)

But we should also consider the very real possibility that the political and policy worlds aren’t very capable of listening to our advice about which particular policies are more effective than others. They may well mostly just hear us say “more” or “less”, such as seems to happen in medical and education spending debates. In this case, we should consider the value of more or less prevention spending overall, holding constant the relative proportions of different kinds of spending. And in this case the clear answer seems to be: less; we should do less. Let go the nut of effective treatment in the pandemic-money-trap gourd of over-prevention. Don’t you agree Tyler?

Added 8pm: Though Tyler criticizes Caplan and my posts which are directly on the topic of overall covid over-prevention, he refuses to say if we are spending too much overall; he simply rejects the “framing” of this question. Seems a question he’d rather not talk about.

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Five Important Topics

By Robin Hanson · November 23, 2020 1:40 pm · Comments (0)

Some topics are especially important. You might think that on such topics we’d try extra hard to be more accurate, both individually and institutionally. Alas, we are also more likely to self-deceive on them, both individually and institutionally.

So on such topics you should less trust both your intuition and the usual institutions. Be more skeptical of all sources, and more eager to find especially reliable sources. At least if you were trying to be accurate. Which you probably aren’t.

What are these most important topics? Simple biology predicts (at least) the following five, ordered from the top down by the fraction of species for which they are important:

Death – All individuals of all species die, which is a terribly important event. As La Rochefoucauld said “Neither the sun nor death can be looked at with a steady eye.” For poor humans food, water, shelter, and many other topics are about death.

Sex/Fertility – All species reproduce, and most do this via sex. For sexual species, sex is as important as death, and easier to deceive associates about.

Status – Many animal species maintain status hierarchies, and in such species it is important both to rise in status, and to judge status well. We self-deceive on our own suitability for status, and on how high status folks differ.

Politics – Primate social groups often split into conflicting coalitions. In that case it is important to be an attractive coalition partner, and to judge partners well. We self-deceive on how our coalitions differ, and on other topics to show loyalty to our faction.

Honesty – Only a species that can communicate can care about honesty (I.e., accuracy), but humans communicate by far the most. And if we are dishonest on important topics, then we must also be dishonest on the topic of our honesty. Yet our reputations for honesty are important to us.

Note that these are also topics on which many seem quite emotionally sensitive, and where norms, laws, and retribution often limit who can say what. And even when people claim to not care about such things, those meta opinions seems to be very important to them.

Note also that many other important topics can be seem as combinations of the above. For example, class is inherited (i.e., fertility driven) status, medicine is death managed by status, and males are the sex designed to die more easily.

I’m painfully aware of how sensitive is the topic of sex/fertility, as I’ve been partially cancelled on the basis of a few brief remarks on that. But if this is a topic on which accuracy is harder, shouldn’t I be more reluctant to have opinions on it?

Yes, but the main thing I said that bothered people was to suggest that sex/fertility might be important to big groups of people. (To husbands who raise kids not theirs, and to people who get zero sex.) And one thing it seems we can be especially confident about these topics is that they are probably important to many people. We are evolved talking social creatures, and these topics are important to the survival and selection of such creatures. Thus I defended a claim about which we can all be especially sure, and doing that apparently induces an unusually strong retribution.

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Who Wants Social Insurance?

By Robin Hanson · November 23, 2020 5:20 am · Comments (0)

During the Biden administration, we will hear many argue that we should hand out more benefits to more people. Now when we economists argue for policy, we usually make economic efficiency arguments. So it is worth noting that for many of these policies, the main economic efficiency rationale for such handouts is “social insurance”. We are already seeing related arguments regarding pandemic relief and school loan forgiveness.

The “social insurance” argument posits a scenario where many people would have wanted to buy private insurance against big risks that they (or their descendants) face, but private insurance markets failed to offer such insurance. And thus the government should step in and produce the effect that such insurance would have produced, which is to pay certain people in certain situations, and tax everyone else to pay for it.

Now it is certainly true that insurers don’t offer all possible kinds of insurance. This can be due to legal restrictions, transaction costs, and information asymmetries. But it can also be due to limited demand. What if most people don’t actually want the insurance that “social insurance” would provide?

We already see many puzzling patterns in common insurance choices. Insurance was long illegal most everywhere, but then in the 1800s the first big retail success of insurance was life insurance sold to husbands as a way to signal devotion to their wives. Today, people often insure small risks like a new piece of electronics breaking, but fail to insure many of the largest risks in their lives, like failures at school, career, or marriage. And when I’ve asked students if they want to insure against such big risks, most usually say no, they don’t.

To explore this further, I did some Twitter polls on willingness to pay for 15 kinds of risks. Here are those risks, sorted by the fraction of respondents who says they would find value in fairly-priced insurance:

Note that only a majority favors private insurance for the top six items, and private insurance is in fact available for all of these today. Note also that these results are from the 3rd version of these polls that I tried. I found smaller fractions wanting insurance in the 2nd and 1st sets.

Of course people aren’t always honest in polls; maybe they really do want to insure far more risks than they say. And the fact that people often push political systems for “social insurance” policies is supporting evidence. But equally plausible, I think, is the theory that many really just want to use government to induce transfers, but when those folks are economists they try to justify such plans using econ efficiency lingo.

A clean test would be for the government to offer fairly-priced insurance against many risks, to ensure that no market failures prevents the availability of such insurance. Or even to subsidize such insurance. If there were actually a market failure preventing such insurance, that seems the most direct way to fix the problem. Yet we almost never see proposals like this; people almost always just push for more handouts. I wonder why.

Added 9a: The usual insurance “market failures” are:

  1. Moral hazard – which government can only fix if it can see more private acts than can private insurers.
  2. Adverse selection – which can be solved by requiring purchase of private insurance, and whose existence requires the opposite correlation between risk level and insurance quantity than the one we usually see,
  3. Scale economics – which private insurers might also achieve if not forbidden by antitrust rules.

To get private long term insurance, we could let kids sign insurance contracts when young, or empower their parents or grandparents to agree on their behalf. Note that today parents could, but usually do not, implement partial poverty insurance by insisting that their richer kids transfer to their poorer kids. As more than half of of national income variance is of this within-family form, this could achieve more than half of the gains possible from poverty insurance within a nation. And parents are much better placed than government to adjust for moral hazard of varying child efforts.

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Easy Conspiracy Tests

By Robin Hanson · November 17, 2020 1:45 pm · Comments (0)

The most obvious kind of conspiracies to expect in the world are ones between your local organized crime, police, and political powers. These powers should each see each other as rivals to their dominance. So to reduce such threats they should should seek to either weaken each other,  or to ally with each other. There are rumors that such alliances are common around the world, and there is clear data that they have often happened in the past. 

So this is no mere theoretical conspiracy theory, to be dismissed by claiming that too many people would know to keep it a secret. This sort of conspiracy is not only verifiably common, it also has a quite credible threat of punishing those who too publicly expose it.

Given that this seems to usually be a real possibility, what sort of evidence might speak to it? Here are some indicators that, if true about your area, are at least weak evidence against such a local alliance:

  1. You see very little profitable crime in your area, such as gambling, drugs, or prostitution.
  2. You see profitable crime, but also conflicts over its control. E.g., wars over drug-selling territory.
  3. You see profitable crime, and little fighting for its control, but its consumer prices are quite near average costs.
  4. You see profitable crime, and see that those who enter such industries fear only police and competitors, not organized crime.
  5. You see a big conflicts in your area between police and organized crime. 
  6. Police in your area are bounty hunters, who regularly gain bounties from catching each other, and judges are clearly not corrupted.
  7. You do elections in a way that lets organized crime steal elections, yet they are clearly not being stolen.
  8. (what else?)

Now if you don’t see any of these signs in your area, you should estimate a higher than average chance that you have a crime-police-politics conspiracy in your area. And as the base rate is already substantial, your estimate should be even higher than that. 

If people were concerned about such conspiracies, they’d pay to hear from folks who collected and published stats on these indicators. And pay even more for stats that made it easier for skeptical observers to check on how such stats were collected and constructed. And then those with the worse indicators, suggesting local conspiracies, could learn about that fact, and perhaps coordinate to change it. 

So what does it tell you if few seem to care enough to even know if such stats are published?

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Centrists Outside The Overton Window

By Robin Hanson · November 16, 2020 5:00 pm · Comments (1)

Overton window – the spectrum of ideas on public policy and social issues considered acceptable by the general public at a given time.

The main thing that sets the size of the world economy today is the amount of innovation that has happened before today. In general we don’t induce enough innovation, as innovators tend to benefit society more than themselves. Thus better innovation institutions, which offer stronger incentives to innovate well, are probably the main way to make a better wealthier more prosperous tomorrow.

Innovation is also terribly important in politics and governance. Most of today’s official policies today were once only proposals, and before that quite unpopular proposals. That is, most current policies were once outside the Overton window of policies seen as acceptable to at least consider. 

The usual political and governance processes are about choosing among policies within the Overton window. Almost everything you see in government, politics, and the media is part of this process. As well as a great many things you don’t see. But just as important are the less visible processes that happen outside the Overton window, processes which decide which of the vast space of logically possible policies are moved closer to the edge of that window, where random fluctuations might tip them in. 

These processes by which outside proposals are honed and selected seem especially neglected today. The main groups who attend to them seem to be political extremists, whose ideal policies are far outside the current Overton window. Such extremists seek ways to reframe political alliances or issues to move the Overton window, and thus gain more favorable consideration for their extreme ideal points. 

Now given how important is innovation, and how neglected is the vast space of policies outside the tiny Overton window, it is good that at least some are thinking outside this “box”. But it also seems a shame that these are mainly extremists. 

Our usual business and tech innovation would be worse if most of this was done by extremists pushing unusual agendas regarding how we should all want to live. For example, imagine if cell phones were only likely to be developed by religious cults with a deep hatred of wires. It is good that instead most business and tech innovation is instead driven by profit incentives, as that drives them to explore a much wider space of possibilities. 

This common diagram describing the Overton window is seriously misleading, as it presents policy as a one-dimensional spectrum. In fact, the real space of policies is hugely multi-dimensional, with a “Overton hypercube” that takes up only tiny fraction of this vast space. It is thus perfectly rational to want to explore that vast space, even by those who are “centrists” with respect to the usually small number of ideological dimensions. There are surely a great many good policies out there in that vast space which are attractive to centrists, if only they can find and hone them.

Thus we want many such centrists to help explore this space, and not just a few extremists. Perhaps in future posts I’ll make some new more concrete proposals for how to better recruit centrists, and most everyone, to explore the vast space of possible policies that lie outside the tiny Overton hypercube. To help hone and select candidates, moving them closer to the edge of this Overton “window.” After which they may later drift inside that window, to become live possibilities for adoption. The better we explore the total space of policy options, the better will be the policies that we adopt. 

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