Tag Archives: Regulation

Elois Ate Your Flying Car

J Storrs Hall’s book Where Is My Flying Car?: A Memoir of Future Past, told me new things I didn’t know about flying cars. The book is long, and says many things about tech and the future, including some with which I disagree. But his main thesis is a contrarian one that I’ve heard many times from engineers over my lifetime. Which is good, because by putting it all in one place, I can now tell you about it, and tell you that I agree:

We have had a very long-term trend in history going back at least to the Newcomen and Savery engines of 300 years ago, a steady trend of about 7% per year growth in usable energy available to our civilization. …

One invariant in futurism before roughly 1980 was that predictions of social change overestimated, and of technological change underestimated, what actually happened. Now this invariant itself has been broken. With the notable exception of information technology, technological change has slowed and social change has mounted its crazy horse. …

In the 1970s, the centuries-long growth trend in energy (the “Henry Adams curve”) flatlined. Most of the techno-predictions from 50s and 60s SF had assumed, at least implicitly, that it would continue. The failed predictions strongly correlate to dependence on plentiful energy. American investment and innovation in transportation languished; no new developments of comparable impact have succeeded highways and airliners. …

The war on cars was handed off from beatniks to bureaucrats in the 70s. Supersonic flight was banned. Bridge building had peaked in the 1960s. … The nuclear industry found its costs jacked up by an order of magnitude and was essentially frozen in place. Interest and research in nuclear physics languished. … Green fundamentalism has become the unofficial state church of the US (and to an even greater extent Western Europe). …

In technological terms, bottom line is simple: we could very easily have flying cars today. Indeed we could have had them in 1950, but for the Depression and WWII. The proximate reason we don’t have them now is the Henry Adams curve flatline; the reasons for the flatline have taken a whole book to explore. We have let complacent nay-sayers metamorphose from pundits uttering “It can’t be done” predictions a century ago, into bureaucrats uttering “It won’t be done” prescriptions today. …

Nanotech would enable cheap home isotopic separation. Short of that, it would enable the productivity of the entire US military-industrial complex in an area the size of, say, Singapore. It’s available to anyone who has the sense to follow Feynman’s pathway and work in productive machinery instead of ivory-tower tiddley-winks. The amount of capital needed for a decent start is probably similar to a well-equipped dentist’s office.

If our pre-1970 energy use trend had continued, we’d now use ~30 times as much energy per person, mostly via nuclear power. Which is enough energy for cheap small flying cars. The raw fuel cost of nuclear power is crazy cheap; almost all the cost today is for reactors to convert power, a cost that has been made and kept high via crazy regulation and liability. Like the crazy restrictive regulations that now limit innovation in cars and planes, destroyed the small plane market, and prevented the arrival of flying cars.

Anything that goes into a certificated airplane costs ten times what the thing would otherwise. (As a pilot and airplane owner, I have personal experience of this.) It’s a lot like the high cost of human medical drugs compared with the very same drugs for veterinary use.… Building of airports remains so regulated (not just by the FAA) that only one major new one (KDEN) has been built [since 1990]. …

It seems virtually certain that if we had had [recent] cultural and regulatory environment … from, say, 1910, the development of universal private automobiles would have been suppressed. … By the end of the 70s there was virtually nothing about a car that was not dictated by regulation.

With nuclear power, we’d have had far more space activity by now. Without it, most innovation in energy intensive things has gone into energy efficiency, and into smaller ecological footprints. Which has cut growth and prevented many things. The crazy regulation that killed nuclear energy is quite unjustified, not only because according to standard estimates nuclear causes far fewer deaths, but also because standard estimates are greatly inflated via wide use of a “linear no threshold model”, regarding which there are great doubts:

Several places are known in Iran, India and Europe [with high] natural background radiation … However, there is no evidence of increased cancers or other health problems arising from these high natural levels. The millions of nuclear workers that have been monitored closely for 50 years have no higher cancer mortality than the general population but have had up to ten times the average dose. People living in Colorado and Wyoming have twice the annual dose as those in Los Angeles, but have lower cancer rates. Misasa hot springs in western Honshu, a Japan Heritage site, attracts people due to having high levels of radium, with health effects long claimed, and in a 1992 study the local residents’ cancer death rate was half the Japan average.

To explain this dramatic change of regulation and litigation, Hall says culture changed:

Western culture had essentially succeeded in supplying the needs of the physical layers of [Maslow’s] hierarchy, including the security of a well-run society; and that the shift to the Eloi [of the Well’s Time Machine story] could be thought of as people beginning to take those things—the Leave It To Beaver suburban life—for granted, and beginning to spend the bulk of their energy, efforts, and concerns on the love, esteem, and self-actualization levels. … “Make Love, Not War” slogan of the 60s … neatly sums up the Eloi shift from bravery to sensuality. …

The nuclear umbrella meant that economic, political, and moral strength of the society was no longer at a premium.

I’ll say more about explaining this cultural change in another post.

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Dominance Explains Paternalism

My Ph.D. is in formal political theory, but I’ve come to realize that it is usually best to think of political behavior not as some different kind of thing, but instead as an extension of or variation on ordinary behavior. This seems to me especially true for paternalism, which I’ve spend much effort pondering. I did a game theory analysis of it for my job talk long ago, and Bryan Caplan just reviewed what seems to be a nice book puzzling over “behavioral” explanations. But on reflection a key explanation seems pretty simple.

In our personal lives, we all know that some of the people around us are more “control freaks”; they push harder for control over what they and their associates do. First they push to control their own lives, then they push for more control of shared context and choices, like which restaurant a group goes to, and finally they push for control over the lives of others. Such as by nagging and berating others re what to eat or wear, or with whom to associate. Or by becoming official leaders and authorities, with formal power to make people do what they say.

I just did two polls that say that most of us think that this control freak pressure tends to hurt associates, and also that control freaks tend more to be “do-gooders”, who talk more about making the world better, and more give that rationale for things they do:

Dominance seems to me the obvious interpretation here. Like most animals, humans strive to dominate each other, in order to rise in the local “pecking order”. And control over ourselves and others not only brings many direct benefits, it is widely taken as one of the strongest signs of dominance and non-submission. But unlike other animals, humans have norms against overt dominance and submission, and norms promoting pro-social behavior, that helps others. So we do push to dominate, but we pretend that we are actually just trying to help. And as usual, we are typically not consciously aware of our hypocrisy. In our mind, we are mainly aware of how they are doing the wrong things, and how they would be so much better off if only we could make them do things our way.

It is not just individuals who try to dominate to gain status; groups coordinate to dominate together as well. For example, parents coordinate to dominate their kids. So we push for our groups to have autonomy, and also control over other groups. And so in politics, where our main motive is to show loyalty to our allies, we each push for our political coalitions to have more self-control, and more control over other groups. So when there is an option for “regulators” or other authorities to take more control over ordinary lives, we tend to support that when we see those authorities as part of our coalition, and those “helped” as part of rival coalitions. Else we may resist.

Of course we actually do often need leaders to make central decisions that effect many others. And people do sometimes make bad decisions that can be improved via pressures from others around them. So dominance isn’t the only cause of leadership or paternalism. This is another example of a key principle: people can only successfully pretend to have motive X to cover real motive Y if sometimes X really is a substantial motive. “The dog ate my homework” works better as an excuse than “The dragon ate my homework.” For a cover to work, it has to be sufficiently plausible. So all the motives we pretend to have really do apply to some people at some times; just not nearly as often as we suggest.

So the claim is not that paternalism or dominant leaders can never be appropriate. Instead, the claim is that there’s a strong tendency to try to justify other more selfish and harmful behaviors via such needs. So we need to hold a much higher standard on leadership than “we should do whatever leaders say because we need leaders.” And we need to hold a higher standard on paternalism than “you should do what regulators say because they are authorities.” Leaders and authorities should be accountable to make their choices actually help via more than a mere dominance struggle for power to grab such positions.

In small firms, leaders are often given rewards that depend on the overall success of those firms. And subordinates who feel they are treated badly may well leave. Together, these can greatly temper leader temptations to use powers of their dominant positions to seek to gain status over their subordinates, relative to actually helping their groups. And in the distant past, in small groups within very war-like areas, dominant leaders faced related outside threats of military competition, and of subordinates running away to other nearby areas.

But today in large mostly-peaceful nations, political leaders tend to lack these other disciplines to temper their tyranny. Which is why it becomes so important today to find other ways to hold political leaders and authorities accountable, to limit their arbitrary dominance. Such as via elections, law, and property rights. I’ve tried to explore new methods, such as futarchy and vouching. But until they are fielded we should keep the old ways, and hold our leaders and authorities to much higher standards than “because I said so”.

In our society today, paternalistic authorities often claim that they are disciplined not so much by profit, voters, or law, but by “science”. You see, they only make people do things when “science” says that is for the best. Having seen how such “science” actually works in these contexts, I’m relatively skeptical of this as an effective discipline today. Too often, this is just a way to justify applying the widespread opinions of social classes and coalitions with which regulators ally.

Added 1p: Teaching kids to play a musical instrument is a striking example of paternalism. Even though data doesn’t suggest that it improves discipline or other academic performance, many passionately want to force this on not only their own kids, but also the kids of others, even those who feel strongly that they don’t want to play. Though most adults enjoy listening to music, few of them choose to play instruments, especially among those who were forced.

Yet people argue that we must force all kids to play so that they can enjoy music as adults and be more attractive as mates, or so that we can find the few good musicians, or so that we can increase the supply of music. Which seem pretty laughable arguments. More plausibly people identify with musicians and cultures that respect them, and so want to force others to respect them as well, especially kids whose status contributes to their own personal status.

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Remote Work Specializes

We seem on track to spend far more preventing pandemic health harm than we will suffer from it, which seems too much spending given the apparent low elasticity of harm w.r.t. prevention. But an upside is that some of this prevention effort is being invested in remote work, which is helping to develop and innovate such capacities. Which matters because remote work (a.k.a. telecommuting) is my guess for the most important neglected trend over the next 30 years. (At least of trends we can foresee now.)

My recent polls put remote work at #24 out of 44 future trends, which IMHO greatly underrates it. AGI, biotech, crypto, space, and quantum computing are far overrated (due to drama & status). Automation matters but will continue steadily as it has for many decades, not causing much trend deviation. Global warming, non-carbon energy, the rise of Asia, falling fertility, and the rise of cybersecurity and privacy are important trends, but their trend deviation implications tend more to be correctly anticipated. However, I see remote work as big and mattering more than and driving trends in migration, aug./virtual reality, and self-driving cars. And remote work implications seem neglected and unappreciated.

Remote work has been a topic of speculation for many decades, so likely somewhere out there is an author who sees it right. But I haven’t yet found that author. I’ve recently read a dozen or so recent discussions of remote work, and all of them seem to miss the main reason that remote work will be such a big deal: specialization due to agglomeration (i.e., more interaction options). The two most formal math analyses I could find actually explicitly assume that remote work, in contrast to traditional work,  produces no agglomeration gains! In contrast, these discussions get closer to the truth: Continue reading "Remote Work Specializes" »

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Board Games As Policy Arguments

When we want to convince others to support our policy positions, we often tell stories. We tell people about things that happened to us, to people we know, and to people we’ve heard of. Journalists tell stories about what happened to famous people recently, or to whole sets of people in “studies”. Popular books also include such policy-lesson stories. And fiction often tries to persuade about policy using “true-like” stories, which are not actually true.

The way that these stories are supposed to support policies is that we are invited to imagine how such stories would have turned out better with different policies. That is the policy “moral” of a story. A big problem with this approach, however, is that even if the story is true, and even if we can correctly judge how a policy would have changed a story, each policy influences a great many other stories. Policy advocates are likely to select the stories that make their policy look best, out of all the other possible stories they could tell.

Academias often tell these kinds of stories, but we also tell other kinds that better avoid this problem. For example, formal game theory models describe entire formal worlds, including agents, resources, actions, info, locations, and preferences. So one can judge if a policy is good overall in such a world. A similar benefit holds for agent-based simulations, lab experiments, and field experiments. In each case, one can judge how much a policy helps or hurts overall for the world that is studied.

Of course most of these methods actually only consider relatively small worlds, which at best correspond to small parts of our big world. So if a policy has effects outside of the scope of the world that it considers, these methods won’t see that. You can try to analyze the many small worlds that a policy influences, and add up the overall effect across them all, but that is hard to do well.

These sorts of small world models also make many assumptions about the basic situations in the small worlds that they consider. So the lessons that they draw from their small worlds need not apply to the corresponding parts of our big world, if those assumptions are bad approximations to our big world. This is less of a problem when one relies on true stories drawn from our actual world. So both sorts of methods have their advantages and disadvantages, and one should plausibly use both when drawing policy conclusions.

All these methods by which academics model policy in small worlds have one big disadvantage: it is hard to use them to persuade ordinary people. They and their supporting analysis can be complex, and also just boring, and thus not emotionally engaging. Dramatic stories from the real world can overcome these big disadvantages.

However, there is another kind of policy story that has so far been neglected, but which can combine the advantages of a wholistic policy evaluation across an entire small world, with the advantages of being simple enough for ordinary people to understand, and also emotionally engaging enough to get them to pay attention. And that is board games. Consider Monopoly:

In 1903, Georgist Lizzie Magie applied for a patent on a game called The Landlord’s Game with the object of showing that rents enriched property owners and impoverished tenants. She knew that some people would find it hard to understand the logic behind the idea, and she thought that if the rent problem and the Georgist solution to it were put into the concrete form of a game, it might be easier to demonstrate. …

Also in the 1970s, Professor Ralph Anspach, who had himself published a board game intended to illustrate the principles of both monopolies and trust busting, fought Parker Brothers and its then parent company, General Mills, over the copyright and trademarks of the Monopoly board game. (More)

The rules of each board game describe both an entire small world, and also the policies that govern player actions in that world. So when people play a board game, they get an intuitive feel for how that world works, how much they enjoy living in that world, and how alternate rules would change their enjoyment. At which point they are ready to hear and understand this policy argument:

If we changed these policy-setting rules (as opposed to these world-defining rules) in this game, that would turn this into a more enjoyable game, and/or make the world it describes more admirable. So to the extent that an important part of our real larger world is like this game world, we should try to move our real policies more toward these better game policies.

Now as far as I can tell, these policy argument fail badly in the case of Monopoly. People like playing the Monopoly game as it is, and do not enjoy it as much when its rules are changed to embody the alternate property and tax policies favored by those who designed and developed it. But the basic approach to policy argument seems valid, at least as a complement to our other story approaches.

Yes, people may have different agendas and priorities regarding life in a board game, relative to their own real lives. But that critique applies as well to all the other kinds of stories that people use to argue for policies. For example, your priorities about the characters in a story you hear may not be the same as your priorities if you were in the story yourself. Yes, to the extent that video games have board game elements, with rules on how players relate to each other, video games can also support policy arguments.

So I’d like to see more people try to make policy arguments in the context of board games. Show us two variations on a game, where the more fun or admirable version corresponds to the policies that you prefer, while the other version corresponds to policies closer to what we have now. Let us prove your claim to ourselves by playing your game. Or maybe find other rules that we enjoy even more, and invite you to prove that claim to yourself by playing.

Yes, I might still not like your policy, because I think your world differs from our real world, or our priorities differ between games and real life.  And yes, the space of fun board games is far smaller than the space of games, so that fun games are far from representative of the larger space. But still, from the point of view of convincing ordinary people about policies, adding game policy arguments probably puts us in a better position than we are in now relying mainly on personal stories, fictional stories, and academic authority.

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Risk-Aversion Sets Life Value

Many pandemic cost-benefit analyses estimate larger containment benefits than did I, mainly due to larger costs for each life lost. Surprised to see this, I’ve been reviewing the value of life literature. The key question: how much money (or resources) should you, or we, be willing to pay to gain more life? Here are five increasingly sophisticated views:

  1. Infinite – Pay any price for any chance to save any human life.
  2. Value Per Life – $ value per human life saved.
  3. Quality Adjusted Life Year (QALY) – $ value per life year saved, adjusted for quality.
  4. Life Year To Income Ratio – Value ratio between a year of life and a year of income.
  5. Risk Aversion – Life to income ratio comes from elasticity of utility w.r.t. income.

The first view, of infinite value, is the simplest. If you imagine someone putting a gun to your head, you might imagine paying any dollar price to not be shot. There are popular sayings to this effect, and many even call this a fundamental moral norm, punishing those who visibly violate it. For example, a hospital administrator who could save a boy’s life, but at great expense, is seen as evil and deserving of punishment, if he doesn’t save the boy. But he is seen as almost as evil if he does save the boy, but thinks about his choice for a while.

Which shows just how hypocritical and selective our norm enforcement can be, as we all make frequent choices that express a finite values on life. Every time we don’t pay all possible costs to use the absolutely safest products and processes because they cost more in terms of time, money, or quality of output, we reveal that we do not put infinite value on life.

The second view, where we put a specific dollar value on each life, has long been shunned by officials, who deny they do any such thing, even though they in effect do. Juries have awarded big claims against firms that explicitly used value of life calculations to not to adopt safety features, even when they used high values of life. Yet it is easy to show that we can have both more money and save more lives if we are more consistent about the price we pay for lives in the many different death-risk-versus-cost choices that we make.

Studies that estimate the monetary price we are willing to pay to save a life have long shown puzzlingly great variation across individuals and contexts. Perhaps in part because the topic is politically charged. Those who seek to justify higher safety spending, stronger regulations, or larger court damages re medicine, food, environmental, or job accidents tend to want higher estimates, while those who seek to justify less and weaker of such things tend to want lower estimates.

The third view says that the main reason to not die is to gain more years of life. We thus care less about deaths of older and sicker folks, who have shorter remaining lives if they are saved now from death. Older people are often upset to be thus less valued, and Congress put terms into the US ACA (Obamacare) medicine bill forbidding agencies from using life years saved to judge medical treatments. Those disabled and in pain can also be upset to have their life years valued less, due to lower quality, though discounting low-quality years is exactly how the calculus says that it is good to prevent disability and pain, as well as death.

It can make sense to discount life years not only for disability, but also for distance in time. That is, saving you from dying now instead of a year from now can be worth more than saving you from dying 59 years from now, instead of 60 years from now. I haven’t seen studies which estimate how much we actually discount life years with time.

You can’t spend more to prevent death or disability than you have. There is thus a hard upper bound on how much you can be willing to pay for anything, even your life. So if you spend a substantial fraction of what you have for your life, your value of life must at least roughly scale with income, at least at the high or low end of the income spectrum. Which leads us to the fourth view listed above, that if you double your income, you double the monetary value you place on a QALY. Of course we aren’t talking about short-term income, which can vary a lot. More like a lifetime income, or the average long-term incomes of the many associates who may care about someone.

The fact that medical spending as a fraction of income tends to rise with income suggests that richer people place proportionally more value on their life. But in fact meta-analyses of the many studies on value of life seem to suggest that higher income people place proportionally less value on life. Often as low as value of life going as the square root of income.

Back in 1992, Lawrence Summers, then Chief Economist of the World Bank, got into trouble for approving a memo which suggested shipping pollution to poor nations, as lives lost there cost less. People were furious at this “moral premise”. So maybe studies done in poor nations are being slanted by the people there to get high values, to prove that their lives are worth just as much.

Empirical estimates of the value ratio of life relative to income still vary a lot. But a simple theoretical argument suggests that variation in this value is mostly due to variation in risk-aversion. Which is the fifth and last view listed above. Here’s a suggestive little formal model. (If you don’t like math, skip to the last two paragraphs.)

Assume life happens at discrete times t. Between each t and t+1, there is a probability p(et) of not dying, which is increasing in death prevention effort et. (To model time discounting, use δ*p here instead of p.) Thus from time t onward, expected lifespan is Lt = 1 + p(et)*Lt+1. Total value from time t onward is similarly given by Vt = u(ct) + p(et)*Vt+1, where utility u(ct) is increasing in that time’s consumption ct.

Consumption ct and effort et are constrained by budget B, so that ct + etB. If budget B and functions p(e) and u(c) are the same at all times t, then unique interior optimums of e and c are as well, and also L and V. Thus we have L = 1/(1-p), and V = u/(1-p) = u*L.

In this model, the life to income value ratio is the value of increasing Lt from L to L+x, divided by the value of increasing ct from c to c(1+x), for x small and some particular time t. That is:

(dL * dV/dL) / (dc * dV/dc) = xu / (x * c  * du/dc) = [ c * u’(c) / u(c) ]-1.

Which is just the inverse of the elasticity of with respect to c.

That non-linear (concave) shape of the utility function u(c) is also what produces risk-aversion. Note that (relative) risk aversion is usually defined as -c*u”(c)/u’(c), to be invariant under affine transformations of u and c. Here we don’t need such an invariance, as we have a clear zero level of c, the level at which u(c) = 0, so that one is indifferent between death and life with that consumption level.

So in this simple model, the life to income value ratio is just the inverse of the elasticity of the utility function. If elasticity is constant (as with power-law utility), then the life to income ratio is independent of income. A risk-neutral agent puts an equal value on a year of life and a year of income, while an agent with square root utility puts twice as much value on a year of life as a year of income. With no time discounting, the US EPA value of life of $10M corresponds to a life year worth over four times average US income, and thus to a power law utility function where the power is less than one quarter.

This reduction of the value of life to risk aversion (really concavity) helps us understand why the value of life varies so much over individuals and contexts, as we also see puzzlingly large variation and context dependence when we measure risk aversion. I’ll write more on that puzzle soon.

Added 23June: The above model applies directly to the case where, by being alive, one can earn budget B in each time period to spend in that period. This model can also apply to the case where one owns assets A, assets which when invested can grow from A to rA in one time period, and be gambled at fair odds on whether one dies. In this case the above model applies for B = A*(1-p/r).

Added 25June: I think the model gives the same result if we generalize it in the following way: Bt, and pt(et,ct) vary with time, but in a way so that optimal ct = c is constant in time, and dpt/ct = o at the actual values of ct,et.

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Philosopher Kings in Blue?

When things go wrong in our lives, we are often tempted to invoke governments to fix them. So we add more systems wherein governments do things, and we make more laws to influence what other people do. However, in the messy process of translating our general purposes into particular system and rules, we often allow various groups to control important details, and turn them more to their purposes. We also get random outcomes due to randomness in which political factions happen have more control when we turn our attention to changing each particular system or rule. In addition, we often leave out details because we are hypocritical, and unwilling to fully admit our real purposes. For example, we often want to appear to oppose things more than we do, like say drug use, prostitution, or adultery.

The net effect of these many messy processes is that our government systems and rules are poorly integrated, clumsy, and vague. We don’t bother to work out many details, and we don’t decide how to make key tradeoffs between different systems and rules. For such elaboration, the public and their politicians often punt to judges and government agencies. And for details where agencies don’t set policies, they punt to individual civil servants.

To influence these agencies and their civil servants, we set bosses who can give them orders, and perhaps promote or fire them. Bosses who have other bosses all the way up to the politicians we elect. But we are afraid of new politicians taking too much hidden control over these agencies, say by firing everyone and hiring all their friends. So we often limit politicians’ powers to direct and fire civil servants. This gives agencies and civil servants more discretion, to do what they choose.

Of course in any one social equilibrium, an individual civil servant may not feel they have great discretion. But that doesn’t contradict the claim that collectively they have a lot. That is, there can be many possible government equilibria consistent with the overall government rules and larger political and social worlds. Some of this government discretion may be captured by the schools and other systems that train people to become civil servants.

To enforce rules on both civil servants, and on ordinary people, we threaten to punish people for violating rules. The civil servants we put in charge of this enforcement process are “police” (in which I include prosecutors, judges, and other civil servants with rule-enforcing discretion). And to help police in these roles, we give them various budgets and powers.

The above description so far is pretty generic, applying nearly as well to a quite minimal state as to a strong “police state”, wherein police have strong powers to punish most anyone they choose. Where any one state sits on this spectrum is determined by many factors, including (1) police monetary budgets, (2) police direct powers to invade spaces, demand info, etc., (3) police negotiating powers regarding court proceedings, and (4) the frequency and severity of rules that people frequently violate.

While once upon a time (say two centuries ago) the U.S. system looked more like a minimal state, today it looks more like a police state. Maybe not as bad a police state as the old Soviet Union, but still, a police state. This transformation is detailed in William Stuntz’ excellent book The Collapse of American Criminal Justice. Some key changes:

  1. We’ve added a lot more laws, so many that we don’t understand most, and regularly violate many.
  2. We’ve cut the use of juries and also many legal defenses, which previously helped evade guilty verdicts.
  3. Rise of big cities means county-set laws are set by folks different from those suffer, cause most crime.
  4. States, who set prison budgets but don’t control conviction rates, greatly increased prison budgets.
  5. Legal trial complexity & cost has risen greatly, and is now beyond what most can afford.
  6. Plea bargaining is now allowed, which strongly pushes people to plead guilty, even when they aren’t.
  7. The new doctrine of qualified immunity protects government officials from many lawsuits.
  8. Most complaints about police have long been investigated by the same agency that employs them.
  9. The rise in civil servant unions, especially police unions.
  10. Surveillance, tracking, and info collection has in many ways become much cheaper.

(Some of these changes resulted from courts seeking to encourage big moral movements, such as those against slavery, alcohol, drugs, prostitution, polygamy, and gambling.)

The net effect of all this is that police can, if they so choose, target most anyone for punishment. That is, for most any target, police can relatively cheaply find a rule the target violated, pressure others to testify against the target, and then finally pressure the target to plead guilty. And police collectively have a lot of discretion in how they use this power. (The rich and politically well-connected may of course be able to discourage such use of power against themselves.)

Of course, the fact that police are powerful hardly implies that they use such powers badly. It remains quite possible that, like the proverbial super-hero, they use their super-powers for good. Many people have long claimed that the best form of government is one run by good-hearted but unconstrained philosopher kings.

This is the context in which I’d like you to consider current complaints about police mistreatment of detainees. Police must make difficult and context-dependent tradeoffs between how carefully to avoid hurting detainees, and how aggressively to discourage them from defiance or escape.

These are the sort of areas where, in our system, local civil servants and their agencies have great discretion, and where the basic nature of our government and legal systems makes it hard to pull back such discretion. I’m not saying that nothing can be done; things can and should be done. But I’m pretty sure that the sort of modest changes being now considered (more training, more record keeping, “requiring” body cams, etc.) can’t greatly change what is in essence a police state. (In contrast, changing to a bounty system might do a lot more.)

Look, imagine that while interacting with police you started to insult them and call them terrible ugly names. In many places, this is probably perfectly legal. However, you’d be rightly reluctant to do this, as you’d know they have a many ways to retaliate. If their local people and culture are inclined to retaliate, and to build a “blue wall of silence” around it, there is little most people can do to protect themselves.

This is why you can’t really count on laws that say you have the right to film police, etc. We basically live in a police state, and in such a state its hard for mere rules to greatly change police behavior. We may well be gaining some benefits from such a police state, but being able to exert detailed control over police and how they use their great discretion is just not one of them.

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Why Does Govt Do Stuff?

Looking across the many different activities and sectors of society, how well can we predict where governments get more vs. less involved?

Though this is an oft discussed topic, I can’t recall seeing an overall theory summary. So I thought I’d write one up. Here are some big relevant factors, and areas they may explain. Most are tentative; you may well convince me to move/change/add them.

Control – Whomever runs the government prefers to control areas that can be used to prevent and resist opposition and rivals.
Predicts more: religion, military, police, law, news, schools, disaster response, electricity, energy, banking.

Scale – If supplying a product or service has strong economies of scale, network, or coordination, it can be cheaper to use one integrated organization, who if private may demand excessive prices and thereby threaten control.
Predicts more: military, “roads” (including air, boat travel support), social media, money, language, electricity, telecom, water, sewer, trash, parks, fire, software, fashion, prestige
Predicts less: housing, food, medicine, art, entertainment, news, police, jail.

Innovation – As governments seem less able to encourage or accommodate effective innovation, governments tend to be less involved in rapidly evolving sectors.
Predicts more: roads, water, sewer, track, parks.
Predicts less: military hardware, vehicles, tech/computers, entertainment, social networks.

Variety – Governments tend to encourage and be better at relatively standardized products and services, done with fewer versions, more the same for everyone everywhere at all times.
Predicts more: war, medicine, schools, disaster response, roads.
Predicts less: housing, food, entertainment, romance, parenting, friendship, humor.

Norms – Norms are shared, and we like to enforce them together, officially.
Predicts more: religion, law, war, romance, parenting, medicine, drugs, gambling, slavery, language, manners, sports.

Show Unity – As we want to show that we are together, and care about each other, we like to do the things we to do to show such care together in a unified way.
Predicts more: religion, poverty/unemployment/health insurance, school, medicine, fire, parks, housing, food, disaster response, trash/sewer, coverage expansion subsidies.

Show Off – We want to impress outsiders with our tastes, abilities.
Predicts more: research, schools, high art, high sport, roads, parks, shared space architecture, trash/sewer.
Predicts less: low art/entertainment, low sport, gossip.

Hypocrisy – When we profess some motives, but others are stronger, the opacity and slack of government agencies, and better ability to suppress critiques, makes them better able to hide such differences.
Predicts more: medicine, drugs, gambling, schools, police, jail, courts, romance, zoning, building codes, war, banking.
Predicts less: water, sewers, electricity.

If we could collect even crude stats on how often or far govt is involved in each area, and crudely rate each area-factor combo for how strongly that factor applies to that area, we could do a more formal analysis of which of factors predict better where.

Note that scale is the strongest factor suggesting that govt does more when more govt helps more. Innovation and variety suggest that also when those factors are the cause of govt involvement, but much less so if those features are the result. While norms are on average valuable, it is much less clear when govt support improves them. Most signaling likely helps each society that does it, but is done too much for the good of the world overall.

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Peter Doherty on Variolation

Two noteworthy media mentions of variolation:

1. The New Yorker features Douglas Perednia talking about controlled infection and variolation, as its Exhibit A on on why conservative media shouldn’t presume to write on health/medicine, as they will only say stupid obviously terrible things:

After the Federalist tweeted it out, Twitter, which has been cracking down on coronavirus misinformation, temporarily locked the Federalist’s account. … He’d submitted it to a number of medical journals and blogs. “They all turned it down with no comment,” … tried the Federalist, almost at random. … The site accepted his article the next day, no questions asked. …

On the site … most commenters found Perednia’s idea absurd, dangerous, hilarious, or all three. … many angry e-mails and calls … Andrew Lover, an assistant professor of epidemiology at the University of Massachusetts-Amherst, told the Times that Perednia’s article was “exceedingly ill-advised and not evidence-based in any way shape or form.” …

Perednia [said] the way to adapt his idea to this reality was to make sure that the infecting was done with ‘the lowest possible dose’ … a concept known as variolation—which, he thought, would cut the death rate among those who chose to take part. (more)

2. A month ago, Adam Ford interviewed me on voluntary infection. Yesterday, Ford posted his interview with Nobel laureate Peter Doherty, author of Pandemics (2012), wherein Ford asked Doherty about variolation. Here are selected quotes from that discussion (fuller quotes below the fold):

47:10 Ford: “Controversially, in leu of actual vaccine that could come, hopefully in 9 months, but maybe even in 18 months if things go okay, if social isolation doesn’t work well enough too, would something like strategic or voluntary small dose low dose infection, like variolation, work in order to gain immunity, or nudge herd immunity? Is that something that we should be considering?

Doherty: (laughing) “Well let’s tell people what variolation was. … What they did was do this in young children, young children had a good immune response, generally survived smallpox, so what they were doing essentially is giving them smallpox, and they survived, whereas if they got it when they were older, they’d have a much worse disease. … So its not an unthinkable thing. …

52:40 With Covid19 I don’t know, but it would take a brave soul to be a test candidate, With younger people who are not severely affected, it’s possible. But you’d have to be enormously careful that they didn’t get any dose through their nose. But there would be ways of doing this. …

53:40 Ford: Is this something that could be achieved in the near term, if the vaccine timeline ends up looking like its going to be longer?

Doherty: If it was an absolutely catastrophic situation, if it was like the situation that is depicted in Contagion, where everyone who is within 100 feet of the virus gets it and dies, yes it could be reasonable. But I think for a virus where 80+% of people are definitely mildly infected at worse, or not sick enough to go into hospital, I don’t think you would take risk of that. The thing about a vaccine is that you have to give it to large numbers of normal people. You can’t take risks with vaccines.

You can take risks with end stage therapy. If someone is very very sick, and you’ve got something you think might work, you can try it pretty easily. People will approve that, … But you can’t take risks with vaccines. And the magnitude of the severity of this threat is not great enough to do that. You could say, … we’ll take a vaccine that looks a bit risky, maybe, and we’ll give it to the elderly. These are the people who are at risk, they can try it. … People like me, say would volunteer, I certainly would. I’d give it a go, and see if that works. But I wouldn’t want to be giving a vaccine that had any risk at all to younger people. You know, these are all theoretical arguments. But there is no way anything is ever given to anybody in this sense without going through extremely thorough review processes. … I think it is pretty unlikely.

So Doherty accepts “variolation” as a term that applies outside the context of smallpox. He thinks it could work, but oddly seems to see the main concept as infecting the young, rather than controlling dose, delivery vector, or strain. And he sees it only as justified in extreme circumstances, which Covid19 will never be, as it isn’t deadly enough. Even if the Great Suppression crashes the economy worse than the Great Depression, and even if millions will likely die from accidental infections, in his eyes and those of regulators that’s no excuse for letting healthy people voluntarily take substantial personal risks. Continue reading "Peter Doherty on Variolation" »

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Do You Feel Lucky, Punk?

A recent influential report posed the key Covid-19 issue today as: to mitigate or suppress? Should we focus on “flattening the curve” under the assumption that most everyone will get it soon, or adopt even stronger measures in an attempt to squash it, so most never get it.

Some simple obvious considerations are:

  1. if successful, squashing saves many more lives,
  2. you have to do a lot more to squash than to flatten,
  3. while flattening policies need be maintained only for a few months, squashing policies must be maintained until a strong treatment is available, probably years, and
  4. squashing is far easier when you have only a few infected and when your trading, travel, and physical neighbors don’t have many infected.

Several nations, mostly Asian, seem to have successfully squashed so far, though they started when they had few infected. China and perhaps S. Korea are the main examples of squashing more than a tiny number of infected, though even they had far fewer than we do now in the West where so many are suddenly eager to squash. China had much recent experience with mass surveillance, controlling population movements, and enforcing strict rules. Even so, they screwed up badly early on, and it isn’t at all obvious that China’s squashing will keep working as they let people go back to work, or when many big neighbors get highly infected.

The main point I want to make in this post is that trying to get your Western government to suppress Covid-19 in the usual way is making a big bet on the quality of they and typical neighboring governments. And also of your public’s commitment. As in the famous Dirty Harry (non-)quote, I ask: “Do you feel lucky, punk?”

Western government agencies and expert communities so far have had a bad record dealing with Covid-19. At first they criticized China’s strong measures and focused on signaling political correctness. The US government badly screwed up the generation and regulation of tests and masks, and the West continues to fail to cut regulation preventing rapid expansion of medical personnel and resources. Western governments only changed policies when public opinion changed, and even now seem more focused on handing out cash to allies, and symbolic but useless acts like banning bicycles.

As with most policy, you must expect that the details matter a lot. So even if you see China policy as a success, you shouldn’t have high hopes if your government merely copies a few surface features of China policy. That only works if this is a simple problem, with simple solutions, and few problems are that simple. This is not just a problem of insufficient moral fervor.

You should have higher hopes if they copied the whole China policy package relatively exactly, and even higher if the Chinese officials who managed their policy implementation personally came to manage implementation here. Even then climate, cultural, or infrastructure differences might mean their policies don’t work here. But no government seems even interested in copying the exact China package, and in my recent poll, 80% of 927 opposed this last idea of Chinese management.

Dear Western citizen, your government has already demonstrated incompetence at dealing with this in the absence of public pressure, and public pressure will mainly push them to do what they guess they would be most blamed by the public for not doing if things go badly. Regardless of whether that actually works; the public may never learn what actually works.

This pandemic has already been allowed to get much bigger than any that has ever been squashed before, and it is harder to squash than most, passing via the air, living on surfaces for days, and with infected folks showing no symptoms for over a week. And in contrast to China, your government doesn’t have much recent experience with the mass surveillance, movement controls, and strict rule enforcement.

And yet now at this late date, you are considering if to authorize these same governments to oversee not just large efforts to flatten the curve, but the more extreme efforts required to squash it. Even knowing that to make it work you’ll need very strong public support in a far less-communal culture than those that have so far managed to squash.

Mind you, you are now considering this not because you have great confidence in your government’s competence, or your public’s support. But mostly, it seems, because it would look morally bad for you to give up hope on the millions who will die even if we flatten the curve well. Really, do you feel lucky, punk?

Also consider: even if your local government manages to successfully squash its internal infections temporarily, what happens if half of its neighbors fail, and become mostly infected? Or what if they succeed for a while, but half of their neighbors fail? What will it take to keep external infections from overwhelming you then? Or what will it take for your government and others to coordinate to ensure that most governments succeed? Remember, these are the governments who have so far largely failed to prevent massive illegal immigration, and who continue to fail to coordinate to limit global warming, war, and ocean overfishing, or to promote global innovation.

This wouldn’t matter much if the policies for squashing looked much like the policies to flatten, so we could actually flatten but pretend for a while that we were trying to squash. But there are policies that could help to flatten that look obviously bad for squashing, such as deliberate exposure, which might cut 3/4 of life-years lost. And locking down the economy and social contacts for many years at a level that looks at all like it might succeed in squashing is going to involve enormous costs to the economy and your freedoms.

In my recent polls, 73% and 74% of 393 and 533 respondents predicted US and world (respectively) will become >25% infected before an >80% effective treatment was given to >80% of world. So 3 in 4 agree that global containment just isn’t going to happen. Yet, to show that they care, most governments are giving lip service to squashing as their goal, not flattening. How far will we all go in paying huge costs to pretend that this is at all likely?

Before we all jump off this cliff together, can we at least collect and publish some honest estimates of our chances of success? Such as perhaps via conditional betting markets? If you aren’t willing to exactly copy the whole China policy, or have them manage it, how serious could you really be about succeess?

Look, this is like starting a war. Its not enough to ask “would it be nice to win such a war”; we also need to ask “can we actually win?” Don’t start what you can’t finish.

I fear suppression is a monkey trap; afraid to let go the nut of saving everyone, we’ll be trapped in the gourd of not saving nearly as many as we could have.

Added 20Mar: Note that the many responses defending suppression talk about how many lives could be saved, and how they can imagine a plan that would work, but none address the issue of how competent is our government to implement such plans. Amazing how easily people slip from “it could be done” to “my government could do this”.

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For Fast Escaped Pandemic, Max Infection Date Variance, Not Average

In an open column, … to provide greater dispersion, the vehicle distance varies from 50 to 100 meters, … distance between dismounted soldiers varies from 2 to 5 meters to allow for dispersion and space for marching comfort. (More)

The troop density has decreased through military history in proportion to the increase in lethality of weapons being use in combat. (More)

Armies moving in hostile areas usually spread out, as concentrations create attractive targets for enemy fire. For soldiers on foot, it might be possible to try to induce such dispersion by having a vicious wild animal chase them. After all, in the process of running fast to escape, they might spread out more than they otherwise might. But this would be crazy – there’s no reason to think this would induce just the right level of dispersion, and it would have many bad side effects. Better just to order soldiers to deliberately space the right distance. 

For a very infectious pandemic like COVID-19, clearly not contained and with no strong treatment likely soon, the fact that medical resources get overwhelmed toward a pandemic peak creates a big value in dispersion – spreading out infection dates. But, alas, our main method is that crazy “chased by a wild animal” approach, in this case chased by the virus itself. 

That is, each person tries to delay their infection as long as possible, in part via socially destructive acts like staying home instead of working. Like soldiers running from a wild animal, our varying efforts at delay do create some variance as a side effect. But probably less than optimal variance, and at great cost. 

Yes, delay has some value in allowing more stockpiling. For example, we should (but apparently aren’t) mass training more medical personnel who can function in makeshift ICU tents. But increasing average delay is can be less valuable than increasing delay variance. Even if we can’t just tell each person when to get infected, like telling soliders where to walk, we have several relevant policy levers. 

First, as I’ve discussed before, we might pay people to be deliberately exposed, and covering the cost of their medical treatment and quarantine until recovery. Yes, if their immunity has a limited duration, then we might want to not start deliberate exposure until there’s less than that duration before the pandemic peak. But there’s still big potential value here, especially via targeting medicine and critical infrastructure workers. 

Second, this is a situation were inequality of wealth, health, and social connections is good. In the last few years, many have loudly lamented many kinds of social inequalities that make the low feel ashamed and unloved, resulting in their more often becoming lonely and sick. Some are enough friends and money that they can afford go to all the parties, while others suffer in poverty alone. And no doubt many will cry loudly when such inequality makes the low get infected before the high.

But however bad such inequality might usually be, in a pandemic it is exactly what the doctor should order, if he could. Among a community close enough to share the same medical resources, the more that individuals vary in their likeliness of catching and passing on the pandemic, the better! Those who catch it early or late will do better than those who catch it just at the peak.  So for this pandemic, let’s maybe back off on whatever we now do to cut inequality, and maybe even open up more to whatever we are not doing that could increase inequality. 

In my next post, I’ll describe some simple concrete sim models supporting these claims.

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