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AI Persuasion Experiment

I’ve been trying to write a persuasive essay about AI risk, but there are already a lot of those out there and I realize I should see if any of them are better before pushing mine. This also ties into a general interest in knowing to what degree persuasive essays really work and whether we can measure that.

So if you have time, I’d appreciate it if you did an experiment. You’ll be asked to read somebody’s essay explaining AI risk and answer some questions about it. Note that some of these essays might be long, but you don’t have to read the whole thing (whether it can hold your attention so that you don’t stop reading is part of what makes a persuasive essay good, so feel free to put it down if you feel like it).

Everyone is welcome to participate in this, especially people who don’t know anything about AI risk and especially especially people who think it’s stupid or don’t care about it.

I want to try doing this two different ways, so:

If your surname starts with A – M, try the first version of the experiment here at

If your surname starts with N – Z, try the second version at

Thanks to anyone willing to put in the time.

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Links 9/16: URL Of The Chaldees

500 BC: Buddha preaches a message of peace and compassion. 1411 AD: China and Sri Lanka go to war over the Buddha’s tooth.

More on confusing effects of school entry age: in Brazil, students who enter first grade later get higher test scores and are more likely to go to college

I recommend against naming ships Windoc until this phenomenon is investigated more thoroughly.

There’s been some recent buzz about Tom Wolfe’s book attacking Noam Chomsky. I can’t comment on the linguistic elements, but it has an unfortunate tendency to take its opposition to evolution’s role in human psychology/society so far that it seems to be denying evolution itself: “I think it’s misleading to say that human beings evolved from animals — actually, nobody knows whether they did or not. There are very few physical signs, aside from the general resemblance of apes and humans.” Jerry Coyne is suitably dismissive. And Nathan Robinson gets into a side debate on Chomsky’s opinion of intellectual elitists (against). On the other hand, here are some apparently sober people disagreeing with Chomsky.

Guests on the TV show Firing Line included Richard Nixon, Saul Alinsky, Noam Chomsky, B.F. Skinner, Allen Ginsberg, John Kenneth Galbraith, Jorge Luis Borges, the Dalai Lama, Jack Kerouac, and Mother Teresa. Though not all at once.

Birth certificate suggests man in Indonesia is 145 years old. Statistical common sense, not to mention the Gompertz-Makeham Law, suggest otherwise.

Professor Stuart Russell at UC Berkeley is opening the Center For Human-Compatible AI to study AI risk in a fully academic setting; they have already received a $5,555,550 grant from OpenPhil.

SETI has detected a suspicious signal from a sunlike star 95 light-years away. Signal strength is high enough that any civilization sending it would have to be well beyond humans. But how could a posthuman civilization exist 95 light-years away from us without us noticing until now? (EDIT: likely false alarm)

Hey, remember how well it worked last time the our society declared war on a commonly used recreational plant with many medical uses and few side effects? No? Well, the DEA certainly does, which is why they’ve decided to expand the drug war by making kratom a Schedule 1 substance. If you feel like doing something meaningless, there’s a petition you can sign.

In 1999 South Korea passed a law mandating that all online commerce be done on Internet Explorer, saying it was the only way to ensure consumer safety. Thank goodness for international differences in regulatory regimes; otherwise people might be tempted to take their own country’s rules seriously.

EpiPen prices have been rising gradually for years. Why did it only become a big news story recently? investigates. Their answer: Bernie Sanders!

Activation of mu opioid receptors might trigger several different signaling cascades, raising the prospect of selective agonists that can trigger good effects (like pain relief) but not bad ones (like respiratory supression).

Dystopian ant society in nuclear bunker goes exactly as well as you would expect.

FDA orders antibacterials removed from consumer soap. I actually support this one: there’s no evidence antibacterials help with much, and there’s some concern that they can increase antibiotic resistance.

Contra a study from a couple of links posts ago, the latest replication attempt suggests democracy does not increase economic growth.

A boon doggle is a cutesy braid thing you can make with lace or rope. In 1935, the press excoriated FDR’s New Deal for spending $3 million giving unemployed people crafts lessons where they made boon doggles, and the word became a nickname for any overpriced useless government project.

There have been so many conflicting experiments and arguments about the supposedly physics-defying EMDrive that the debate will probably only get resolved once somebody launches one into space and tries it.

Why Don’t We Have Pay Toilets In America? Short answer: some college kids launched a wildly successful campaign to ban them. On the other hand, it looks like pay toilets only cost a dime, whereas it costs me $2 or $3 to buy a coffee in a cafe just so I can use the cafe’s Customer Only non-pay toilet, plus it’s a waste of coffee.

Some SSC readers ask me to inform you of e-quilibrium, an attempt to make e-cigarette fluid that mimics the chemical composition of tobacco as closely as possible (except for the part where tobacco kills you). I do not know anything about this field and can neither endorse nor specifically anti-endorse this.

You know that weird thing where no matter what happens in the real world, US economic growth keeps to a perfectly straight line on the decades-or-above timescale? There’s a field studying that, it’s called balanced growth economics, and it’s pretty much as confusing as you would expect.

GiveDirectly’s basic income experiment runs into unexpected trouble as some poor people refuse their cash grants, suspecting it might be a scam. I guess if somebody offered me a year’s salary for no reason I would probably suspect it was a scam too.

How Seattle Killed Microhousing. It’s not just San Francisco that wants to make affordable housing illegal.

I’m not really qualified to have an opinion on it, but MIRI is very excited about their most recent paper, Logical Induction, which is apparently a big step in relating inductive reasoning to mathematical proof.

Scott Aaronson suggests that people with computer skills can best fight Trump by creating vote-trading websites that allow people in safe states to vote third-party in exchange for third-party supports in swing states voting Hillary. Apparently this has been confirmed legal by the court system. See also existing vote-trading websites like makeminecount.

Explain this one: Haitian-Americans have one of the lowest crime rates in the country, well below other blacks, Latinos, and whites.

The Missing Slate: “Marginal Revolution may well be the finest blog ever; if we wanted to put a blog in the Smithsonian to show future generations what happened when smart people in our time spoke their minds, then Marginal Revolution would be my choice.”

“Most critics of neoliberalism on the left point to the dramatic reduction in the scale of government activities since the 80s – the privatisation of state-run enterprises, the increased dependence upon private contractors for delivering public services etc. Most right-wing critics lament the increasing regulatory burden faced by businesses and individuals and the preferential treatment and bailouts doled out to the politically well-connected. Neither the left nor the right is wrong. But both of them only see one side of what is the core strategy of neoliberal crony capitalism – increase the scope and reduce the scale of government intervention.”

A Genetically Informed Study Of The Association Between Harsh Punishment And Offspring Behavioral Problems: adjust for genetics, and “mild” physical punishment like spanking seems to affect children slightly at most; outright abuse seems to have very strong negative effects.

The most prestigious scientific journals may publish the worst research.

Maybe the most popular Major League Baseball promotion of all time was Disco Demolition Night, when the Chicago White Sox suggested that people who hated disco bring disco records to their game and they would destroy all of them in a big explosion. It ended in fires, rioting, accusations of racism, police intervention, a forfeited game, and possibly the decline of disco nationwide.

A two year old’s solution to the trolley problem

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Some Context For That NYT Sugar Article

Imagine a political historian discovers that Lyndon Johnson accepted a campaign contribution from a big Wall Street bank. Since Johnson’s policies helped shape the modern Democratic Party, everyone agrees the Democrats are built on a foundation of lies. “Republicans Vindicated; Small-Government Conservativism Was Right All Along”, say the headlines of all the major newspapers.

This is kind of how I feel about the reaction to the latest New York Times article.

How The Sugar Industry Shifted Blame To Fat describes new historical research that finds that the sugar industry sponsored a study showing that fat (and not sugar) was the major risk factor for cardiovascular disease. They tie this into a bigger narrative about how sugar is the real dietary villain, and it’s only the sugar industry’s successful bribery work that made us suspect fat for so long:

The revelations are important because the debate about the relative harms of sugar and saturated fat continues today, Dr. Glantz said. For many decades, health officials encouraged Americans to reduce their fat intake, which led many people to consume low-fat, high-sugar foods that some experts now blame for fueling the obesity crisis.

“It was a very smart thing the sugar industry did, because review papers, especially if you get them published in a very prominent journal, tend to shape the overall scientific discussion,” he said […]

I’m glad researchers have discovered this. But treating it as a smoking gun which exonerates fat and blames sugar is like the political example above. Yes, it’s sketchy for LBJ to take Wall Street money. But this kind of low-level corruption is so universal that concentrating on any one example is likely to lead to overcorrection.

Yes, the sugar lobby sponsors some research, but the fat lobby has researchers of its own. They tend to be associated with the dairy and meat industries, both of which are high in saturated fat and both of which are very involved in nutrition research. For example, Siri-Tarino et al’s Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease finds that saturated fat does not increase heart disease risk, but it has a little footnote saying that it’s supported by the National Dairy Council. Modulation of Replacement Nutrients, which finds that replacing dietary fat with dietary sugar doesn’t help and may worsen heart disease, includes two authors affiliated with the National Dairy Council and one affiliated with the National Cattleman’s Beef Association.

Mother Jones does a dairy industry expose and finds:

[Industry] ties can sometimes be hard to avoid, since much of the research on dairy is funded by a constellation of industry-backed institutes, including the Nestlé Nutrition Institute, the Dannon Institute, and the Dairy Research Institute, which spends $19 million a year “to establish the health benefits of dairy products and ingredients.” Even Willett acknowledges that he has received a “very small” dairy industry grant. Dairy companies also donate heavily to the American Society for Nutrition, which publishes the influential American Journal of Clinical Nutrition, and the Academy of Nutrition and Dietetics, “the world’s largest organization of food and nutrition professionals.”

Then there are the industry’s donations to politicians. Dairy companies spent nearly $63 million on federal lobbying and gave $24 million to candidates between 2004 and 2014.

As Jim Babcock points out in the comments, some of the agendas are more complicated than I’m making them sound. Dairy was pretty okay with the low-fat craze for a while, because it let them market low-fat milk. But they do seem to be behind a lot of the pro-saturated-fat research going on right now, and their website does promote pro-saturated-fat articles (1, 2, 3). Overall they seem to be taking a low-key approach where they roll with some studies and push back on others.

In any case, claims that the sugar industry sponsored one study back in the 1960s, and this means everything we’ve ever thought is wrong and biased against fat and in favor of sugar, miss the point (especially since there are probably problems with both sugar and fat). Whatever study the New York Times has dredged up was one volley in an eternal clandestine war of Big Fat against Big Sugar, and figuring out who’s distorted the science more is the sort of project that’s going to take more than one article.

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It’s Bayes All The Way Up

[Epistemic status: Very speculative. I am not a neuroscientist and apologize for any misinterpretation of the papers involved. Thanks to the people who posted these papers in r/slatestarcodex. See also Mysticism and Pattern-Matching and Bayes For Schizophrenics]

Bayes’ Theorem is an equation for calculating certain kinds of conditional probabilities. For something so obscure, it’s attracted a surprisingly wide fanbase, including doctors, environmental scientists, economists, bodybuilders, fen-dwellers, and international smugglers. Eventually the hype reached the point where there was both a Bayesian cabaret and a Bayesian choir, popular books using Bayes’ Theorem to prove both the existence and the nonexistence of God, and even Bayesian dating advice. Eventually everyone agreed to dial down their exuberance a little, and accept that Bayes’ Theorem might not literally explain absolutely everything.

So – did you know that the neurotransmitters in the brain might represent different terms in Bayes’ Theorem?

First things first: Bayes’ Theorem is a mathematical framework for integrating new evidence with prior beliefs. For example, suppose you’re sitting in your quiet suburban home and you hear something that sounds like a lion roaring. You have some prior beliefs that lions are unlikely to be near your house, so you figure that it’s probably not a lion. Probably it’s some weird machine of your neighbor’s that just happens to sound like a lion, or some kids pranking you by playing lion noises, or something. You end up believing that there’s probably no lion nearby, but you do have a slightly higher probability of there being a lion nearby than you had before you heard the roaring noise. Bayes’ Theorem is just this kind of reasoning converted to math. You can find the long version here.

This is what the brain does too: integrate new evidence with prior beliefs. Here are some examples I’ve used on this blog before:

All three of these are examples of top-down processing. Bottom-up processing is when you build perceptions into a model of the the world. Top-down processing is when you let your models of the world influence your perceptions. In the first image, you view the center letter of the the first word as an H and the second as an A, even though they’re the the same character; your model of the world tells you that THE CAT is more likely than TAE CHT. In the second image, you read “PARIS IN THE SPRINGTIME”, skimming over the duplication of the word “the”; your model of the world tells you that the phrase should probably only have one “the” in it (just as you’ve probably skimmed over it the three times I’ve duplicated “the” in this paragraph alone!). The third image might look meaningless until you realize it’s a cow’s head; once you see the cow’s head your model of the world informs your perception and it’s almost impossible to see it as anything else.

(Teh fcat taht you can siltl raed wrods wtih all the itroneir ltretrs rgraneanrd is ahonter empxlae of top-dwon pssirocneg mkinag nsioy btotom-up dtaa sanp itno pacle)

But top-down processing is much more omnipresent than even these examples would suggest. Even something as simple as looking out the window and seeing a tree requires top-down processing; it may be too dark or foggy to see the tree one hundred percent clearly, the exact pattern of light and darkness on the tree might be something you’ve never seen before – but because you know what trees are and expect them to be around, the image “snaps” into the schema “tree” and you see a tree there. As usual, this process is most obvious when it goes wrong; for example, when random patterns on a wall or ceiling “snap” into the image of a face, or when the whistling of the wind “snaps” into a voice calling your name.

Corlett, Frith & Fletcher (2009) (henceforth CFF) expand on this idea and speculate on the biochemical substrates of each part of the process. They view perception as a “handshake” between top-down and bottom-up processing. Top-down models predict what we’re going to see, bottom-up models perceive the real world, then they meet in the middle and compare notes to calculate a prediction error. When the prediction error is low enough, it gets smoothed over into a consensus view of reality. When the prediction error is too high, it registers as salience/surprise, and we focus our attention on the stimulus involved to try to reconcile the models. If it turns out that bottom-up was right and top-down was wrong, then we adjust our priors (ie the models used by the top-down systems) and so learning occurs.

In their model, bottom-up sensory processing involves glutamate via the AMPA receptor, and top-down sensory processing involves glutamate via the NMDA receptor. Dopamine codes for prediction error, and seem to represent the level of certainty or the “confidence interval” of a given prediction or perception. Serotonin, acetylcholine, and the others seem to modulate these systems, where “modulate” is a generic neuroscientist weasel word. They provide a lot of neurological and radiologic evidence for these correspondences, for which I highly recommend reading the paper but which I’m not going to get into here. What I found interesting was their attempts to match this system to known pharmacological and psychological processes.

CFF discuss a couple of possible disruptions of their system. Consider increased AMPA signaling combined with decreased NMDA signaling. Bottom-up processing would become more powerful, unrestrained by top-down models. The world would seem to become “noisier”, as sensory inputs took on a life of their own and failed to snap into existing categories. In extreme cases, the “handshake” between exuberant bottom-up processes and overly timid top-down processes would fail completely, which would take the form of the sudden assignment of salience to a random stimulus.

Schizophrenics are famous for “delusions of reference”, where they think a random object or phrase is deeply important for reasons they have trouble explaining. Wikipedia gives as examples:

– A feeling that people on television or radio are talking about or talking directly to them

– Believing that headlines or stories in newspapers are written especially for them

– Seeing objects or events as being set up deliberately to convey a special or particular meaning to themselves

– Thinking ‘that the slightest careless movement on the part of another person had great personal meaning…increased significance’

In CFF, these are perceptual handshake failures; even though “there’s a story about the economy in today’s newspaper” should be perfectly predictable, noisy AMPA signaling registers it as an extreme prediction failure, and it fails its perceptual handshake with overly-weak priors. Then it gets flagged as shocking and deeply important. If you’re unlucky enough to have your brain flag a random newspaper article as shocking and deeply important, maybe phenomenologically that feels like it’s a secret message for you.

And this pattern – increased AMPA signaling combined with decreased NMDA signaling – is pretty much the effect profile of the drug ketamine, and ketamine does cause a paranoid psychosis mixed with delusions of reference.

Organic psychosis like schizophrenia might involve a similar process. There’s a test called the binocular depth inversion illusion, which looks like this:


The mask in the picture is concave, ie the nose is furthest away from the camera. But most viewers interpret it as convex, with the nose closest to the camera. This makes sense in terms of Bayesian perception; we see right-side-in faces a whole lot more often than inside-out faces.

Schizophrenics (and people stoned on marijuana!) are more likely to properly identify the face as concave than everyone else. In CFF’s system, something about schizophrenia and marijuana messes with NMDA, impairs priors, and reduces the power of top-down processing. This predicts that schizophrenics and potheads would both have paranoia and delusions of reference, which seems about right.

Consider a slightly different distortion: increased AMPA signaling combined with increased NMDA signaling. You’ve still got a lot of sensory noise. But you’ve also got stronger priors to try to make sense of them. CFF argue these are the perfect conditions to create hallucinations. The increase in sensory noise means there’s a lot of data to be explained; the increased top-down pattern-matching means that the brain is very keen to fit all of it into some grand narrative. The result is vivid, convincing hallucinations of things that are totally not there at all.

LSD is mostly serotonergic, but most things that happen in the brain bottom out in glutamate eventually, and LSD bottoms out in exactly the pattern of increased AMPA and increased NMDA that we would expect to produce hallucinations. CFF don’t mention this, but I would also like to add my theory of pattern-matching based mysticism. Make the top-down prior-using NMDA system strong enough, and the entire world collapses into a single narrative, a divine grand plan in which everything makes sense and you understand all of it. This is also something I associate with LSD.

If dopamine represents a confidence interval, then increased dopaminergic signaling should mean narrowed confidence intervals and increased certainty. Perceptually, this would correspond to increased sensory acuity. More abstractly, it might increase “self-confidence” as usually described. Amphetamines, which act as dopamine agonists, do both. Amphetamine users report increased visual acuity (weirdly, they also report blurred vision sometimes; I don’t understand exactly what’s going on here). They also create an elevated mood and grandiose delusions, making users more sure of themselves and making them feel like they can do anything.

(something I remain confused about: elevated mood and grandiose delusions are also typical of bipolar mania. People on amphetamines and other dopamine agonists act pretty much exactly like manic people. Antidopaminergic drugs like olanzapine are very effective acute antimanics. But people don’t generally think of mania as primarily dopaminergic. Why not?)

CFF end their paper with a discussion of sensory deprivation. If perception is a handshake between bottom-up sense-data and top-down priors, what happens when we turn the sense-data off entirely? Psychologists note that most people go a little crazy when placed in total sensory deprivation, but that schizophrenics actually seem to do better under sense-deprivation conditions. Why?

The brain filters sense-data to adjust for ambient conditions. For example, when it’s very dark, your eyes gradually adjust until you can see by whatever light is present. When it’s perfectly silent, you can hear the proverbial pin drop. In a state of total sensory deprivation, any attempt to adjust to a threshold where you can detect the nonexistent signal is actually just going to bring you down below the point where you’re picking up noise. As with LSD, when there’s too much noise the top-down systems do their best to impose structure on it, leading to hallucinations; when they fail, you get delusions. If schizophrenics have inherently noisy perceptual systems, such that all perception comes with noise the same way a bad microphone gives off bursts of static whenever anyone tries to speak into it, then their brains will actually become less noisy as sense-data disappears.

(this might be a good time to remember that no congentally blind people ever develop schizophrenia and no one knows why)


Lawson, Rees, and Friston (2014) offer a Bayesian link to autism.

(there are probably a lot of links between Bayesians and autism, but this is the only one that needs a journal article)

They argue that autism is a form of aberrant precision. That is, confidence intervals are too low; bottom-up sense-data cannot handshake with top-down models unless they’re almost-exactly the same. Since they rarely are, top-down models lose their ability to “smooth over” bottom-up information. The world is full of random noise that fails to cohere into any more general plan.

Right now I’m sitting in a room writing on a computer. A white noise machine produces white noise. A fluorescent lamp flickers overhead. My body is doing all sorts of body stuff like digesting food and pumping blood. There are a few things I need to concentrate on: this essay I’m writing, my pager if it goes off, any sorts of sudden dramatic pains in my body that might indicate a life-threatening illness. But I don’t need to worry about the feeling of my back against the back fo the chair, or the occasional flickers of the fluorescent light, or the feeling of my shirt on my skin.

A well-functioning perceptual system gates out those things I don’t need to worry about. Since my shirt always feels more or less similar on my skin, my top-down model learns to predict that feeling. When the top-down model predicts the shirt on my skin, and my bottom-up sensation reports the shirt on my skin, they handshake and agree that all is well. Even if a slight change in posture makes a different part of my shirt brush against my skin than usual, the confidence intervals are wide: it is still an instance of the class “shirt on skin”, it “snaps” into my shirt-on-skin schema, and the perceptual handshake goes off successfully, and all remains well. If something dramatic happens – for example my pager starts beeping really loudly – then my top-down model, which has thus far predicted silence – is rudely surprised by the sudden burst of noise. The perceptual handshake fails, and I am startled, upset, and instantly stop writing my essay as I try to figure out what to do next (hopefully answer my pager). The system works.

The autistic version works differently. The top-down model tries to predict the feeling of the shirt on my skin, but tiny changes in the position of the shirt change the feeling somewhat; bottom-up data does not quite match top-down prediction. In a neurotypical with wide confidence intervals, the brain would shrug off such a tiny difference, declare it good enough for government work, and (correctly) ignore it. In an autistic person, the confidence intervals are very narrow; the top-down systems expect the feeling of shirt-on-skin, but the bottom-up systems report a slightly different feeling of shirt-on-skin. These fail to snap together, the perceptual handshake fails, and the brain flags it as important; the autistic person is startled, upset, and feels like stopping what they’re doing in order to attend to it.

(in fact, I think the paper might be claiming that “attention” just means a localized narrowing of confidence intervals in a certain direction; for example, if I pay attention to the feeling of my shirt on my skin, then I can feel every little fold and micromovement. This seems like an important point with a lot of implications.)

Such handshake failures match some of the sensory symptoms of autism pretty well. Autistic people dislike environments that are (literally or metaphorically) noisy. Small sensory imperfections bother them. They literally get annoyed by scratchy clothing. They tend to seek routine, make sure everything is maximally predictable, and act as if even tiny deviations from normal are worthy of alarm.

They also stim. LRF interpret stimming as an attempt to control sensory predictive environment. If you’re moving your arms in a rhythmic motion, the overwhelming majority of sensory input from your arm is from that rhythmic motion; tiny deviations get lost in the larger signal, the same way a firefly would disappear when seen against the blaze of a searchlight. The rhythmic signal which you yourself are creating and keeping maximally rhythmic is the most predictable thing possible. Even something like head-banging serves to create extremely strong sensory data – sensory data whose production the head-banger is themselves in complete control of. If the brain is in some sense minimizing predictive error, and there’s no reasonable way to minimize prediction error because your predictive system is messed up and registering everything as a dangerous error – then sometimes you have to take things into your own hands, bang your head against a metal wall, and say “I totally predicted all that pain”.

(the paper doesn’t mention this, but it wouldn’t surprise me if weighted blankets work the same way. A bunch of weights placed on top of you will predictably stay there; if they’re heavy enough this is one of the strongest sensory signals you’re receiving and it might “raise your average” in terms of having low predictive error)

What about all the non-sensory-gating-related symptoms of autism? LRF think that autistic people dislike social interaction because it’s “the greatest uncertainty”; other people are the hardest-to-predict things we encounter. Neurotypical people are able to smooth social interaction into general categories: this person seems friendly, that person probably doesn’t like me. Autistic people get the same bottom-up data: an eye-twitch here, a weird half-smile there – but it never snaps into recognizable models; it just stays weird uninterpretable clues. So:

This provides a simple explanation for the pronounced social-communication difficulties in autism; given that other agents are arguably the most difficult things to predict. In the complex world of social interactions, the many-to-one mappings between causes and sensory input are dramatically increased and difficult to learn; especially if one cannot contextualize the prediction errors that drive that learning.

They don’t really address differences between autists and neurotypicals in terms of personality or skills. But a lot of people have come up with stories about how autistic people are better at tasks that require a lot of precision and less good at tasks that require central coherence, which seems like sort of what this theory would predict.

LRF ends by discussing biochemical bases. They agree with CFF that top-down processing is probably related to NMDA receptors, and so suspect this is damaged in autism. Transgenic mice who lack an important NMDA receptor component seem to behave kind of like autistic humans, which they take as support for their model – although obviously a lot more research is needed. They agree that acetylcholine “modulates” all of this and suggest it might be a promising pathway for future research. They agree with CFF that dopamine may represent precision/confidence, but despite their whole spiel being that precision/confidence is messed up in autism, they don’t have much to say about dopamine except that it probably modulates something, just like everything else.


All of this is fascinating and elegant. But is it elegant enough?

I notice that I am confused about the relative role of NMDA and AMPA in producing hallucinations and delusions. CFF say that enhanced NMDA signaling results in hallucinations as the brain tries to add excess order to experience and “overfits” the visual data. Fine. So maybe you get a tiny bit of visual noise and think you’re seeing the Devil. But shouldn’t NMDA and top-down processing also be the system that tells you there is a high prior against the Devil being in any particular visual region?

Also, once psychotics develop a delusion, that delusion usually sticks around. It might be that a stray word in a newspaper makes someone think that the FBI is after them, but once they think the FBI is after them, they fit everything into this new paradigm – for example, they might think their psychiatrist is an FBI agent sent to poison them. This sounds a lot like a new, very strong prior! Their doctor presumably isn’t doing much that seems FBI-agent-ish, but because they’re working off a narrative of the FBI coming to get them, they fit everything, including their doctor, into that story. But if psychosis is a case of attenuated priors, why should that be?

(maybe they would answer that because psychotic people also have increased dopamine, they believe in the FBI with absolute certainty? But then how come most psychotics don’t seem to be manic – that is, why aren’t they overconfident in anything except their delusions?)

LRF discuss prediction error in terms of mild surprise and annoyance; you didn’t expect a beeping noise, the beeping noise happened, so you become startled. CFF discuss prediction error as sudden surprising salience, but then say that the attribution of salience to an odd stimulus creates a delusion of reference, a belief that it’s somehow pregnant with secret messages. These are two very different views of prediction error; an autist wearing uncomfortable clothes might be constantly focusing on their itchiness rather than on whatever she’s trying to do at the time, but she’s not going to start thinking they’re a sign from God. What’s the difference?

Finally, although they highlighted a selection of drugs that make sense within their model, others seem not to. For example, there’s some discussion of ampakines for schizophrenia. But this is the opposite of what you’d want if psychosis involved overactive AMPA signaling! I’m not saying that the ampakines for schizophrenia definitely work, but they don’t seem to make the schizophrenia noticeably worse either.

Probably this will end the same way most things in psychiatry end – hopelessly bogged down in complexity. Probably AMPA does one thing in one part of the brain, the opposite in other parts of the brain, and it’s all nonlinear and different amounts of AMPA will have totally different effects and maybe downregulate itself somewhere else.

Still, it’s neat to have at least a vague high-level overview of what might be going on.

OT58: Opepipen Thread

This is the bi-weekly visible open thread. There are hidden threads every few days here. Post about anything you want, ask random questions, whatever. Also:

1. Comments of the week include Katja Grace on Economics Whack-A-Mole and dtsund on the evolutionary complexity argument in politics, grendelkhan on Nexium, Emirikol on the degree to which overpriced generics subsidize research, and especially Corey on how the government might save money by funding all drug research.

2. Marginal Revolution also gives a cute story about an FDA bureaucrat (but see also).

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Reverse Voxsplaining: Brand-Name Drugs

[Epistemic status: Uncertain, especially on the accuracy of the economic studies cited]


Sarah Kliff of Vox replies to my piece from last week. She writes:

Earlier this week I wrote about how a lack of drug price regulation in the United States allows pharmaceutical companies — including EpiPen’s manufacturer, Mylan — to charge exceptionally high prices for their products.

Scott Alexander at the blog Slate Star Codex argues that I’ve got it all wrong: The problem isn’t a lack of price regulation. Instead, its too much regulation, which has prevented generic competitors from entering the market and has left EpiPen’s price so high. […]

Alexander and I are both essentially pointing out two examples of how the United States has created a regulatory system that is incredibly favorable to pharmaceutical companies. We’ve set up a system that makes it incredibly easy for drug companies to score high profits and charge exceptionally high prices for their products.

One way it’s favorable is that we let drug companies pick their own prices — in this way the United States is exceptional, as the vast majority of developed companies regulate their drug prices. Another way we’ve created a favorable regulatory environment, as Alexander writes, is by allowing roadblocks to stand in the way of generic drug makers who want to enter.

More generics can help America’s drug spending problem. But they can’t solve it.

Greater use of generic drugs is widely accepted as a way to drive down drug spending. The FDA has found that drug prices decline to 55 percent of the brand-name price when two generic manufacturers begin making a product. Right now, the United States already uses a lot of generic drugs. In fact, about 90 percent of drugs prescribed in the country right now are generic. Brand name drugs are the reason that America has higher per-capita drug spending than other countries. Brand-name drugs make up just 10 percent of prescriptions filled in the United States, but account for 72 percent of drug spending.

Drugs that are under patent are the true source of high American drug costs. EpiPen is, in a way, a bit of a red herring […]

Harvoni, a [patented] pill that cures Hepatitis C, costs $32,114 here — and $22,554 in the United Kingdom. Less red tape around generic drug competition wouldn’t really change that fact. As long as we’re going to have patented drugs, letting drug manufacturers set their own prices will remain a key driver of America’s higher drug spending.

(the above is some excerpts stitched together to provide a taste; you should really read the whole thing)

First of all, thanks to Ms. Kliff and Vox for responding to me; it’s always neat to get featured in real news sources as if I were a real writer or something instead of just a guy with a blog. Additional thanks for a very measured and charitable tone despite my own tendency toward snarkiness. I worry that I am being unfair by acting snarky to somebody who is writing for a professional publication and so is not allowed to be snarky back; if so, I’m sorry and will try to control myself as best I can, which admittedly is not very good.

That having been said, I’m super against all of this and think it’s totally wrong.

I would kind of like to complain about Vox calling EpiPen a “red herring” when they were the ones who brought it up, but I think the problem is deeper than that. Discussing generic drug costs is completely different from discussing brand name drug costs, and the two issues have very different arguments around them. To transition fluidly from one to the other, saying we need more price controls for generics and then backing up your argument by saying that you were mostly thinking of brand-names after all – elides a distinction which is the heart of this entire subject.

Generic drugs are overpriced because we’re morons who can’t come up with a decent regulatory regime. Brand-name drugs are overpriced because of a deliberate decision to overprice them to encourage research.

The economic argument goes: the more profitable new drugs are, the more incentive a company has to make them. If we didn’t reward pharmaceutical companies for inventing new drugs, then they wouldn’t go through the $2.5 billion, ten-year hassle of seeking FDA approval with no guarantee of success. The way we reward them is by giving them a twenty-year monopoly when they can charge lots of money without anybody telling them not to.

(this isn’t quite right. The law says a twenty-year monopoly, but it’s dated from the time the drug is invented. Since it takes ten years to go through the FDA, it’s effectively more like a ten-year monopoly on actually selling the drug)

The reason I usually limit my griping about pharmaceutical overpricing to generics and avoid brand-names is that while high generic pricing is inexcusable, high brand-name pricing is debatably useful. Some people would say that the benefit of encouraging more drug development is worth the cost of higher prices, other people would say that it isn’t. I didn’t want to wade into this complicated debate.

But I guess now I have to. So. Lit review time. I searched the economics literature for studies, models, and arguments used to calculate whether price regulation would decrease drug development, and if so, how the benefits and risks balanced out. Here’s what I’ve got:

1. Golec & Vernon (2006) say that as a result of European drug price regulation, “EU consumers enjoyed much lower pharmaceutical price inflation, however, at a cost of 46 fewer new medicines introduced by EU firms.”

2. Eger and Mahlich (2014) find that among pharmaceutical companies, “a higher presence in Europe is associated with lower R&D investments. The results can be interpreted as further evidence of the deteriorating effect of regulation on firm’s incentives to invest in R&D.”

3. Kutyavina (2010) finds that “brand-name pharmaceutical firms characterized by large R&D expenditures decreased their R&D efforts post 1993 threat [to regulate drug prices] relative to firms that did not engage in as much innovative R&D”.

4. Acemoglu and Linn (2004) find that “We find a large effect of potential market size on the entry of nongeneric drugs and new molecular entities”, which I think is supposed to generalize to mean that the more money they expect to make the more research they do. I will count this as half a study since the connection is not explicit.

5. Danzon & Epstein (2008) analyze price regulations and new drugs invented in 15 countries and 12 drug classes, and find that “If price regulation reduces drug prices, it contributes to launch delay in the home country.

6. Troyer & Krasnikov (2002) find that “the empirical relationship between pharmaceutical industry revenues and pharmaceutical industry innovation is estimated, allowing for an exploration of the impact of the Medicaid rebate program [which regulated drug prices somewhat]. Using the empirical results, the opportunity cost of the Medicaid rebate program is found to be as high as four new drug approvals annually. Given the increased interest in a Medicare drug benefit, regulators should be aware of the hidden cost of price regulation for pharmaceuticals.”

7. Vernon (2005) finds that “I simulate how a new policy regulating pharmaceutical prices in the US will affect R&D investment. I find that such a policy will lead to a decline in industry R&D by between 23.4% and 32.7%. This prediction, however, is accompanied by several caveats.”

8. Golec, Hegde, and Vernon (2009) find that “Results show that the HSA [a bill to regulate drug spending in the US] had significant negative effects on stock prices and firm-level R&D spending. Conservatively, the HSA reduced R&D spending by about $1 billion even though it never became law.”

9. Santerre and Vernon (2006) use drug demand data to simulate various regulatory regimes, and find that a certain price regulation policy they test, continued over twenty years, would have cost gains of $472 billion (!) but also “have led to 198 new drugs being brought to the US market” (!!). They note that “Therefore, the average social opportunity cost per drug developed during this period was approximately $2.4 billion. Research on the value of pharmaceuticals suggests that the social benefits of a new drug are far greater than this estimate. Hence, drug price controls could do more harm than good.”

10. Keyhani, Carpenter, et al (2010) find that “The United States accounted for 42% of prescription drug spending and 40% of the total GDP among innovator countries and was responsible for the development of 43.7% of the NMEs [ie new drugs invented]. The United Kingdom, Switzerland, and a few other countries innovated proportionally more than their contribution to GDP or prescription drug spending, whereas Japan, South Korea, and a few other countries innovated less…higher prescription drug spending in the US does not disproportionately privilege domestic innovation, and many countries with drug price regulation were significant contributors to pharmaceutical innovation.” This study does not attempt to address the effects of price regulation, only to say that European countries seem to do pretty well at innovation despite price regulation, which is suggestive that price regulation does not hurt drug innovation but not really scientific evidence for it. I’m going to count this one as half a study too.

So by my count, there are eight-and-a-half studies concluding that price regulation would hurt new drug innovation, and one-half of a study concluding that it wouldn’t. I’ve tried to eliminate all the studies sponsored by the pharmaceutical industry from this list, but I might have missed some, and I am always skeptical of anything that says anything the pharmaceutical industry approves of even I can’t trace the money directly.

One source I do trust is RAND, a think tank which is generally well-respected and pretty objective (despite the name, they are not associated with Ayn Rand or Rand Paul). In Regulating Drug Prices: US Policy Alternatives In A Global Context, they write:

U.S. consumers spend roughly twice as much on drugs as their European counterparts….Pressure is building in U.S. policy circles for the federal government to take action to regulate the cost of drugs. At the same time, there is debate about the pros and cons of doing so…To shed light on this debate, a team of RAND researchers examined the impact of drug price regulation…The results showed that:

— Globally, the regulation of pharmaceutical prices has increased in recent years.

— In most cases, regulation reduces pharmaceutical revenues.

— Regulatory approaches that reduce pharmaceutical revenues may generate modest consumer savings in the best cases, but risk much larger costs as decreased innovation leads to reductions in life expectancy.

In other words, such prices would be good in the short term as we get all the currently-existing drugs for very cheap:

Annual per capita spending in 2010 would fall for Americans age 55–59 by an amount in the range of $9,000 annually and for Europeans of the same age by an amount in the range of $400.

But bad in the long-term as pharmaceutical innovation declines and we have fewer interventions available to protect our health:

Life expectancy would fall by somewhere in the range of 0.2 years for Americans age 55–59 in 2010 and by approximately 0.1 years for Europeans in the same cohort and year. By 2060, this effect would increase for both Americans and Europeans to approximately 0.7 years.

Given the value they place on human life, they argue that this money-for-life-years trade is net negative:

Overall, as shown in Figure 1, the net value of price controls is positive in the short term (2010) for Americans age 55–59, producing approximately $1,100 in per capita savings, but negative for Europeans in the same cohort and year, who face increased costs in the range of $8,000. For both Americans and Europeans, price controls have higher per capita costs over the longer term: By 2060, reductions in life expectancy, after accounting for medical cost savings, would cost the equivalent of $51,000 and $54,000, to age 55–59 Americans and Europeans, respectively.

All of this sounds sort of boring and economics-y when you read it like this, and maybe your eyes are glazing over. So let me put this in context. In 2060 there will probably be 420 million Americans and 523 million Europeans. And suppose that whatever changes we make in drug regulations today last for one human lifespan, so that everybody has a chance to be 55-60. So about a billion people each losing about 0.7 years of their life equals 700 million life-years. Since some people live in countries outside the US and Europe [citation needed] and they also benefit from First-World-invented medications, let’s round this up to about a billion life-years lost.

What was the worst thing that ever happened? One strong contender is Mao’s Great Leap Forward, in which ineffective agricultural reforms and very effective purges killed 45 million people. Most of these people were probably already adults, and lifespan in Mao’s China wasn’t too high, so let’s say that each death from the Great Leap Forward cost what would otherwise be twenty healthy life years. In that case, the worst thing that has ever happened until now cost 45 million * 20 = 900 million life-years.

Once again, RAND’s calculations plus my own Fermi estimate suggest that prescription drug price regulation would cost one billion life-years, which would very slightly edge out Communist China for the title of Worst Thing Ever.

Am I exaggerating or being facetious? I’m actually not sure. Dammit, Jim I’m a doctor, not an economist. I’m not qualified to analyze any of those ten studies above beyond a quick check to see if they’re completely ridiculous. I’m not qualified to say if RAND is right or wrong to estimate a cost of 0.7 life-years, or whether I’m misusing their calculation to try to add up exactly how bad it would be. Maybe a real economist will look at this whole essay and say it’s really stupid. I don’t know.

The only thing I can say in my own defense is that I am acknowledging that the question exists. I am not at all sure that Vox has reached this level yet. They just wrote an article on price regulations for brand-name drugs which, first, mixed them liberally with generic drugs despite the different arguments around each, and second, didn’t mention anything about research or innovation. Call me overly demanding, but when you are proposing a policy which most economists think would decrease the rate of life-saving medical progress, and which by some calculations might edge out Mao’s China for the title of most disastrous and deadly thing in all of human history, then I feel like you should acknowledge, at least in a single sentence, that somebody has claimed, at least once, that the policy might have some slight downside. At least don’t act as if it’s the same issue as a different kind of drug regulation which doesn’t have that downside.

I think it’s an unfortunate omission to talk about the EpiPen cost increase as relating only to lack of price controls, and fail to mention the reason why this happens with EpiPen but never chairs or mugs. And I think it’s a further omission to talk about regulating brand-name medications but fail to mention that some people think it will backfire and impede innovation. While I appreciate the effort to say we’re both on the same team of reducing drug costs, I’m a little concerned about my teammates’ strategy here.

And there’s another way we’re not quite on the same team. I’m on Team Left-Libertarian, which luckily is so confusing and contradictory that I can define it however I want. And today it means that while I’m not opposed to all regulation in principle, I at least get really scared when somebody pushes for regulation today and promises to check whether it will have bad consequences tomorrow. I think that’s how we got in this mess where the generics industry is so regulated that EpiPens cost hundreds of dollars, and even if Vox and I are on the same object-level team of Make Epi-Pens Cost Less, I worry we are not on the same meta-level team of Learn From The Fact That Epi-Pens Cost So Much And Worry That The Same Kind Of Thinking That Caused The Epi-Pen Problem Will Probably Cause Other Problems Too.


So do I have a solution to the high price of brand-name drugs? Well, I have a partial, unsatisfying solution. But first, a digression.

Vox gives the example of Harvoni costing $32,000 in the United States, but only $22,000 in the United Kingdom. This is supposed to be an example of the United Kingdom’s drug price regulation system working. I guess this is good, but you may notice that both numbers are really really high. There’s generic Harvoni available in India for $900. I can’t find how much it costs to manufacture, but reading between the lines and looking at some similar compounds, it’s probably about $100. So good work, Britain. You’re paying $22,000 instead of $32,000 for a $100 pill.

There are a couple of morals to this story. The first is that Vox’s claim that generics made by two competing companies cost 55% of the brand-name price isn’t the right statistic to use here. Look at their source and you find that as number of competing companies gets to 20, generics cost 5% of brand names. As number of competitors approaches infinity, drug cost should approach manufacturing cost, which can be very low – in the cast of Harvoni, less than one percent. This seems true in the case of modafinil, which I’ve talked about before; it costs about $25 per pill in the US and more like $2 per pill in more generic-friendly India.

So the second moral of the story is that almost all gains in prescription drug prices are to be found not in price regulation bringing prices down from $32,000 to $22,000, but in switching from monopoly brand-name drugs that cost $32,000 to heavily-competitive generic drugs that cost $100.

In a lot of cases, this is easier than you would think.

Pristiq is the brand-name of desvenlafaxine, a new antidepressant which is still brand-name only. Desvenlafaxine sounds a lot like venlafaxine – which is Effexor, an old antidepressant which is available in generic. In fact, desvenlafaxine is a tiny change to the venlafaxine molecule which may or may not have any interesting medical benefit over the original, and which was invented solely to have something whose patent hasn’t expired.

Wyeth, the company that makes Pristiq, says that it’s better than Effexor because it doesn’t have as many drug-drug interactions. But Effexor doesn’t really have clinically significant drug-drug interactions, and this seems to be them just saying random stuff and hoping people believe them. There are no good head-to-head studies comparing Pristiq to Effexor, but if you try to piece together a comparison from unrelated studies (not recommended, but we’ll do it anyway) Effexor actually seems better than its newer cousin. Even the data I took from drug rating databases shows patients preferring Effexor to Pristiq by quite a lot. Carlat Psychiatry, which is psychiatrists’ insider news site on pharmacology developments, has a blog post called Top Five Reasons To Forget About Pristiq. Most of the well-informed psychiatrists I know agree that Pristiq is a slightly worse version of an older antidepressant with no proven advantages.

A month’s supply of Effexor costs $20. A month’s supply of Pristiq costs $300. So let me amend the paragraph above. Pristiq is a slightly worse version of an older antidepressant with no proven advantages that also costs fifteen times as much.

It should come as no surprise to anyone familiar with the state of psychiatry that it is the second most-prescribed antidepressant in the USA, with three million prescriptions per month.

Why would this happen? The relevant study is called Pharmaceutical Industry-Sponsored Meals And Physician Prescribing Patterns For Medicare Beneficiaries, so you know it’s going to be good. It shows that doctors who often eat drug-company-sponsored free lunches are more than twice as likely to prescribe Pristiq as doctors who rarely eat such lunches. This matches my observations perfectly. Doctors prescribe Pristiq because they don’t know very much about antidepressants, but they attend free lunches by pharmaceutical companies who tell them that Pristiq is great, and they believe it. If this surprises you, be more cynical.

I’m looking at the price of Pristiq in Canada, and it seems to range around $120 to $250. So if we instituted price regulations like Canada’s, we might lower the cost of Pristiq from $300 to $150. If we convinced doctors to prescribe Effexor instead, it would be $20, plus I really do believe Effexor is genuinely better.

Pristiq is far from alone in this. I don’t have good statistics, but I bet that at least half of brand-name prescriptions in the US are more like Pristiq (attempts to rip people off) than like Harvoni (genuinely wonderful breakthroughs in medical science).

So one of the best ways to deal with expensive brand-name drugs is to stop using expensive brand name drugs for no reason. Since I get to define what left-libertarianism means however I want, I will say that it is provisionally okay with banning pharmaceutical companies from buying doctors lunch, as long as there aren’t any studies concluding that this would kill more people than Communist China. There are probably lots of other ways to improve medical education and medical economics so that doctors are less easily bamboozled into prescribing these, but those can wait for other blog posts.

What about the genuinely novel brand-name drugs, the ones like Harvoni that really are better than anything that came before?

An optimistic answer: maybe after we stop spending our civilizational resources on Pristiq, we’ll have a little more money to afford them, and maybe we’ll be happy to subsdize the genuinely awesome pharmaceutical research that remains.

Another optimistic answer: once FDA regulatory requirements are loosened, there will be a wide selection of different brand-name drugs. For example, even when Prozac was a brand-name, pharma’s ability to inflate its price was limited by the existence of several very similar brand-name drugs, like Paxil and Zoloft. If there are twenty competing brand-name hepatitis wonder drugs – and I don’t think that’s outside the realm of what we can hope for – then I think that will tend to lower prices to cost. This would include the cost of research and licensing, and so still be pretty high, but as long as research is a real unavoidable cost it would probably be the best we can hope for.

(this would be a good time to bring up that chlorcyclizine costs fifty cents per pill and might work as well as Harvoni)

The pessimistic answer is that all we can do is ensure that the generics marketplace is fair and competitive. And then rich people can buy Harvoni now for $30,000, and poor people will have to wait ten years to buy Harvoni when it costs $100. Right now they’ll unfortunately have to figure out how to make do with the set of medications invented in 2006 and before.

And I know this is terrible, especially if someone has a disease with only one cure and it was invented after 2006. But think of it this way. This objection, rephrased, is that 2016 has more drugs available than 2006, and we want to maximize the number of new drugs available to the poorest patients. But if we try to do that by instituting price controls which decreases the rate of drug innovation long-term, then we end up decreasing the number of new drugs available to the poorest patients, exactly the opposite of what we thought we were doing.

Let me give an example. According to study (9) above, price controls would have caused about 200 fewer drugs to be approved over the period from 1980 – 2000. In fact about 600 drugs were approved during that period. So if they’re right, it would have cut the innovation rate by 1/3. That means that in Hypothetical Price Control World’s 2016, after 36 years of price controls, we would only have 24 of our years’ worth of drugs – ie, the drugs that we had in 2004 in our own world. But since drugs usually go off patent about ten years after approval, in fact we’ve genericized the drugs that we had in 2006 in our own world. So we have more drugs available just as generics than Hypothetical Price Control World has as generics and brand-names combined. If poor people can afford only generics or price-controlled brand names, our poor people are better off than Hypothetical Price Control World’s poor people (and our rich people are much better off than Hypothetical Price-Control World’s rich people). And as time goes on, our advantage over their world will only get bigger.

Maybe there are better ways to do this. Some people have talked about funding research via “prizes” rather than through an investment-and-profit model. Some people say we should fund it publicly through the NIH or something, which we already sort of do to a degree. Still other people say that we should abolish the FDA, cut the costs of drug development by an order of magnitude, and, um, see what happens. I don’t know about any of those things. I just feel like until you’re ready to set these up and have some idea that they work, do the thing that probably is going to result in people having the best access to the most life-saving drugs. Which right now looks like no price control.

Or maybe I am completely wrong about all of this. I am not an economist and have to take these studies at face value, and anything that touches pharmaceutical companies ends up being corrupted and full of lies. Maybe I myself am saying something very stupid that will end up killing more people than Communist China. If so I certainly hope that people who know more than I do will tell me why these calculations were wrong and how to look at this situation better.

But this is the level at which I think this discussion needs to be had.

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Terrorists Vs. Chairs: An Outlier Story

The other day I needed to know how many people were killed by chairs, and while searching I came across the Washington Post’s You’re More Likely To Be Fatally Crushed By Furniture Than Killed By A Terrorist. It argues that worrying about terrorism is irrational, because terrorists kill fewer people each year than falling furniture, and nobody cares about that:

Consider, for instance, that since the attacks of Sept. 11, 2001, Americans have been no more likely to die at the hands of terrorists than being crushed to death by unstable televisions and furniture […] What accounts for the fear that terrorism inspires, considering that its actual risk in the United States and other Western countries is so low? The answer lies in basic human psychology.

I once saw the perfect response to this kind of argument on Twitter, but I forgot to screenshot it, so I’ll have to try to draw it from memory here.

One person posted a graph that looked something like this:

And somebody else edited it to look like this:

And whoa I had never realized before how sketchy it is to start your interval for recording the average number of terrorist attacks the day after the last major terrorist attack.

I mean, I know why people do it. It’s because September 11 was an “outlier”, and outliers should not be counted. Problem is, depending on your distribution, sometimes “outliers” are the only thing that matters.

Let me give an example. Suppose I’m trying to make an argument that earthquakes are totally not a problem for Haiti at all, that there’s no need to invest in earthquake preparedness, and that Haitian people who worry about earthquakes are stupid. I make a graph showing that since January 13, 2010, fewer Haitians have died per year from earthquake-related causes than from crazy furniture-related mishaps. This is totally 100% true. Look at those stupid Haitians, worrying about something that on average never hurts anybody!

(the Haitian earthquake of January 12, 2010 killed about 100,000 people)

I’m sure there are a zillion small Richter 1.0 and Richter 2.0 earthquakes in Haiti all the time. I’m sure our monitoring interval of January 13, 2010 to present picked up lots of these and correctly noted that they don’t kill anybody. The only Haitian earthquakes anyone needs to worry about are the outliers.

If you start your monitoring interval on January 13, earthquakes kill 0 people/year. If you start it on January 11, earthquakes kill 20,000 people a year. Neither of these is entirely fair – one is purpose-designed to maximize casualties, the other to minimize it. I don’t think there’s an obvious fair way to do things – the best solution would be extend the interval back to infinity, but then you get into problems like Haiti having fewer people back in the day, or Haiti not having risen out of the sea yet back in 4,000,000,000 BC. Maybe the best solution is to pick an arbitrary block of time like “the last fifty years”, or to do something very complicated like using the remote historical record to produce earthquake numbers and then combine it with modern populations to produce expected casualties.

The same is true of September 11. Start the interval September 12, and you get 5-10 terrorism deaths/year. Start it September 10, and you get 200. I don’t know when the best time to start it would be. If I had to choose something, I would say maybe 1985, when jihadist terrorism got started after the Soviet invasion of Afghanistan. But someone else could choose 1776, or 2000, based on similarly arbitrary criteria. And it would all be irrelevant – September 11 either made terrorists more ambitious, made security forces more watchful, or both, and so probably changed the calculus for good.

Granted, even when you include September 11, terrorism isn’t the worst thing, and people probably do overestimate it. So forget terrorism. On average, the flu kills something like 20,000 people worldwide each year. That’s a lot, but not apocalyptically much. If you go back year after year, the average stays at something like 20,000/year, right up until you get to 1918, when about 100,000,000 people died. So flu deaths over the last century average about 1 million/year. But three years from now, average flu deaths over the last century will average about 20,000 year. A death rate of only 20,000/year might make our current efforts to contain the flu seem excessive compared to other diseases. But a death rate of 1 million/year makes them look if anything the opposite.

Even worse: did you know that giant asteroids kill about a hundred people per year, on average? This is admittedly an odd definition of “kill” and “average” given that no human being has ever been killed by a giant asteroid. But given that giant asteroids strike Earth about every ten million years, and an asteroid strike today might kill about a billion people, on average giant asteroids kill about a hundred people per year.

Actually, un-forget terrorism. I have a friend who is very in favor of the War On Terror, and he argues that the problem with terrorism isn’t the average suicide bomber who kills three people. It isn’t even the 9-11 hijackers who killed three thousand people. It’s the group that steals a nuke and kills three million people. Just as “on average” a hundred people die each year from giant asteroid strikes, maybe “on average” thirty thousand people die each year from nuclear terrorism. All you’d need for this to be true is one nuclear attack per century. And that’s as bad as an average flu season!

The thing about falling furniture is that there’s probably not going to be a furniturepocalypse where suddenly millions of people all perish at once after being struck by a really really big desk. Furniture is constant. Terrorism isn’t. The whole point of black swans is that we pay too much attention to constant risks and ignore the outliers, especially the outliers which outlie so far that they haven’t happened yet. That’s true whether it’s terrorism, earthquakes, pandemics, or AI.

I worry that someday many years from now, terrorists are going to have some improbable victory which is even more destructive than September 11. I worry that uncounted people are going to die. And I worry that ten years later, someone is going to post on Facebook about how “From the day after ISIS nuked London through today, on average fewer people per year have died of terrorism than from hilarious accidents involving bedside dressers!”

Reverse Voxsplaining: Drugs vs. Chairs

[Content note: this is pretty much a rehash of things I’ve said before, and that other people have addressed much more eloquently. My only excuse for wasting your time with it again is that SOMEHOW THE MESSAGE STILL HASN’T SUNK IN. Pitching this as “market” vs. “government” is overly simplistic, but maybe if I am overly simplistic sometimes then it will sink in better.]

EpiPens, useful medical devices which reverse potentially fatal allergic reactions, have recently quadrupled in price, putting pressure on allergy sufferers and those who care for them. Vox writes that this “tells us a lot about what’s wrong with American health care” – namely that we don’t regulate it enough:

The story of Mylan’s giant EpiPen price increase is, more fundamentally, a story about America’s unique drug pricing policies. We are the only developed nation that lets drugmakers set their own prices, maximizing profits the same way sellers of chairs, mugs, shoes, or any other manufactured goods would.

Let me ask Vox a question: when was the last time that America’s chair industry hiked the price of chairs 400% and suddenly nobody in the country could afford to sit down? When was the last time that the mug industry decided to charge $300 per cup, and everyone had to drink coffee straight from the pot or face bankruptcy? When was the last time greedy shoe executives forced most Americans to go barefoot? And why do you think that is?

The problem with the pharmaceutical industry isn’t that they’re unregulated just like chairs and mugs. The problem with the pharmaceutical industry is that they’re part of a highly-regulated cronyist system that works completely differently from chairs and mugs.

If a chair company decided to charge $300 for their chairs, somebody else would set up a woodshop, sell their chairs for $250, and make a killing – and so on until chairs cost normal-chair-prices again. When Mylan decided to sell EpiPens for $300, in any normal system somebody would have made their own EpiPens and sold them for less. It wouldn’t have been hard. Its active ingredient, epinephrine, is off-patent, was being synthesized as early as 1906, and costs about ten cents per EpiPen-load.

Why don’t they? They keep trying, and the FDA keeps refusing to approve them for human use. For example, in 2009, a group called Teva Pharmaceuticals announced a plan to sell their own EpiPens in the US. The makers of the original EpiPen sued them, saying that they had patented the idea epinephrine-injecting devices. Teva successfully fended off the challenge and brought its product to the FDA, which rejected it because of “certain major deficiencies”. As far as I know, nobody has ever publicly said what the problem was – we can only hope they at least told Teva.

In 2010, another group, Sandoz, asked for permission to sell a generic EpiPen. Once again, the original manufacturers sued for patent infringement. According to Wikipedia, “as of July 2016 this litigation was ongoing”.

In 2011, Sanoji asked for permission to sell a generic EpiPen called e-cue. This got held up for a while because the FDA didn’t like the name (really!), but eventually was approved under the name Auvi-Q, (which if I were a giant government agency that rejected things for having dumb names, would be going straight into the wastebasket). But after unconfirmed reports of incorrect dosage delivery, they recalled all their products off the market.

This year, a company called Adamis decided that in order to get around the patent on devices that inject epinephrine, they would just sell pre-filled epinephrine syringes and let patients inject themselves. The FDA rejected it, noting that the company involved had done several studies but demanding that they do some more.

Also, throughout all of this a bunch of companies are merging and getting bought out by other companies and making secret deals with each other to retract their products and it’s all really complicated.

None of this is because EpiPens are just too hard to make correctly. Europe has eight competing versions. But aside from the EpiPen itself, only one competitor has ever made it past the FDA and onto the pharmacy shelf – a system called Adrenaclick.

And of course there’s a catch. With ordinary medications, pharmacists are allowed to interpret prescriptions for a brand name as prescriptions for the generic unless doctors ask them not to. For example, if I write a prescription for “Prozac”, a pharmacist knows that I mean anything containing fluoxetine, the chemical ingredient sold under the Prozac brand. They don’t have to buy it directly from Prozac trademark-holder Eli Lilly. It’s like if someone asks for a Kleenex and you give them a regular tissue, or if you suggest putting something in a Tupperware but actually use a plastic container made by someone other than the Tupperware Corporation.

EpiPens are protected from this substitution. If a doctor writes a prescription for “EpiPen”, the pharmacist must give an EpiPen-brand EpiPen, not an Adrenaclick-brand EpiPen. This is apparently so that children who have learned how to use an EpiPen don’t have to relearn how to use an entirely different device (hint: jam the pointy end into your body).

If you know anything at all about doctors, you know that they have way too much institutional inertia to change from writing one word on a prescription pad to writing a totally different word on a prescription pad, especially if the second word is almost twice as long, and especially especially if it’s just to do something silly like save a patient money. I have an attending who, whenever we are dealing with anything other than a life-or-death matter, just dismisses it with “Nobody ever died from X”, and I can totally hear him saying “Nobody ever died from paying extra for an adrenaline injector”. So Adrenaclick continues to languish in obscurity.

So why is the government having so much trouble permitting a usable form of a common medication?

There are a lot of different factors, but let me focus on the most annoying one. EpiPen manufacturer Mylan Inc spends about a million dollars on lobbying per year. tells us what bills got all that money. They seem to have given the most to defeat S.214, the “Preserve Access to Affordable Generics Act”. The bill would ban pharmaceutical companies from bribing generic companies not to create generic drugs.

Did they win? Yup. In fact, various versions of this bill have apparently failed so many times that FDA Law Blog notes that “insanity is doing the same thing over and over again and expecting different result”.

So let me try to make this easier to understand.

Imagine that the government creates the Furniture and Desk Association, an agency which declares that only IKEA is allowed to sell chairs. IKEA responds by charging $300 per chair. Other companies try to sell stools or sofas, but get bogged down for years in litigation over whether these technically count as “chairs”. When a few of them win their court cases, the FDA shoots them down anyway for vague reasons it refuses to share, or because they haven’t done studies showing that their chairs will not break, or because the studies that showed their chairs will not break didn’t include a high enough number of morbidly obese people so we can’t be sure they won’t break. Finally, Target spends tens of millions of dollars on lawyers and gets the okay to compete with IKEA, but people can only get Target chairs if they have a note signed by a professional interior designer saying that their room needs a “comfort-producing seating implement” and which absolutely definitely does not mention “chairs” anywhere, because otherwise a child who was used to sitting on IKEA chairs might sit down on a Target chair the wrong way, get confused, fall off, and break her head.

(You’re going to say this is an unfair comparison because drugs are potentially dangerous and chairs aren’t – but 50 people die each year from falling off chairs in Britain alone and as far as I know nobody has ever died from an EpiPen malfunction.)

Imagine that this whole system is going on at the same time that IKEA spends millions of dollars lobbying senators about chair-related issues, and that these same senators vote down a bill preventing IKEA from paying off other companies to stay out of the chair industry. Also, suppose that a bunch of people are dying each year of exhaustion from having to stand up all the time because chairs are too expensive unless you’ve got really good furniture insurance, which is totally a thing and which everybody is legally required to have.

And now imagine that a news site responds with an article saying the government doesn’t regulate chairs enough.

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OT57: Chopin Thread

This is the bi-weekly visible open thread. There are hidden threads every few days here. Post about anything you want, ask random questions, whatever. Also:

1. One reason I love you guys is that you always know useful information about random things. Some of the comments on pharmacological tolerance really helped me understand it better; particularly comment-of-the-week-worthy were Erebus, George Dawson, and Raza. Related: r/nootropics recently had a good thread about Adderall tolerance.

2. Important Consumer Warning: I was recently on vacation and tried to get some money out of a Bank of America ATM. The ATM took my card and refused to give it back. When I called the bank’s number, they just told me that this just happened randomly sometimes, they wouldn’t help me, there was nothing anyone could do, and I’d have to get a new card from my bank. While I was on the phone, a passer-by overheard and told me that they’d had the same problem, also with a Bank of America ATM. Needless to say this seriously complicated my vacation. I wish I had known not to use Bank of America ATMs at any point when it would be inconvenient to permanently lose the card involved, so now I am telling you.

3. Worth highlighting: the last open thread’s discussion on people who willed themseves into having their first childhood memory.

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Links 8/16: On My Right Hand Michael; On My Left Hand URL

Have you heard of Desert Bus, the terrible game about driving a bus for eight real-time hours through a monotonous desert landscape? You have? Then did you know it’s part of Penn and Teller’s Smoke and Mirrors, a collection of trick video games mostly useful for trolling your friends?

Continental/postmodernist theorist Jacques Lacan might have been the worst psychiatrist ever (but see here).

Omens and portents, part 5490569910.

Did you know: there are still some practicing Manichaeans around in China.

Yet another study finds evidence that Tylenol use during pregnancy increases ADHD rates (paper, popular article)

During World War II, submariners who were missing their alcohol invented torpedo juice, a cocktail made of pineapple juice and torpedo motor fuel.

Related to recent posts on psychedelics: what happens when you take LSD once a week for a year?

“Earth-like” planet around Proxima Centauri.

The great thing about capitalism is that you can monetize everything, even the crackpots who send physicists mail claiming to have discovered Theories Of Everything: What I Learned As A Hired Consultant For Autodidact Physicists.

Forbes: The Five Biggest Open Economics Questions.

At least one study finds that police use of body cameras causes more fatal shootings, especially among African-Americans. Authors theorize that police in genuinely dangerous situations feel more comfortable shooting knowing that the body camera video will vindicate them. But I think I’ve seen other studies say the opposite, so probably best not to overreact just yet. Study does find that police use of smartphones is associated with decreased fatal shooting rate, which makes sense – if they’re anything like me, they’re probably staying in the police station browsing Facebook all day.

I say bad things about occupational licensing a lot, but I guess I should grudgingly admit that occupational licensing of midwives seems to have seriously decreased infant mortality.

Related: Otto von Bismarck’s universal health insurance for Germany seems to have decreased mortality rates. This paper somehow manages to talk about imperial German health insurance without making any Kaiser puns.

Facebook has too many terrible groups to remove them all manually, so they seem to automatically remove ones that get reported enough times. This goes exactly as well as you would expect; Muslims in the Middle East have started a (successful) campaign to get atheist Facebook groups in their countries shut down.

The FDA has decided to subject e-cigarettes to very onerous regulations, meaning they will probably become much less accessible and convenient, meaning probably thousands of people who would otherwise have successfully switched to tobacco-free products will continue to smoke tobacco. A friend on Tumblr tries a cost-benefit analysis and suggests that the change could cost up to 9360 lives, which seems about par for the course for FDA decisions.

Did you know: Brightline is a company building a high-speed rail network in Florida, in what would be the US’ first new private passenger rail system in a hundred years.

Tyler Cowen makes the case that Denmark’s institutions aren’t that great because Danes in the US do better than Danes in Denmark, suggesting Denmark is a successful country mostly because of Danish culture (Cowen didn’t mention genes, but should have). Discussion on Twitter centered around how it’s very hard to find accurate statistics on US Danes because they’re all confounded by who does or doesn’t remember their ancestry (usually upper-class people keep better geneologies). Somehow this realy neat list of all immigrant groups by average education level attained also came up, which shows that Danes are pretty unremarkable on that front. Cowen’s conclusion – that we should at least have open borders for any country with more generous welfare payments than our own – is also pretty interesting.

On the other hand, here’s a case where institutions do matter – Native American areas under the jurisdiction of US rather than tribal courts tend to have stronger credit markets. I would find this more exciting if I knew how a priori relevant strong credit markets were, versus how likely they just went down a list of things until they could cherry-pick one that courts seemed to affect.

Salon magazine is pivoting to a new format which will have less politics and try to include more conservative voices.

This is not a drill: Uber will be fulfilling ride requests using self-driving cars in Pittsburgh within a month. Okay, fine, it’s sort of a drill – the self-driving cars will still have drivers sitting in them in order to ensure safety and comply with regulations.

Old Tom was a killer whale who made a deal with whalers – he would drive other whales within range, in exchange for a share of the meat once they were killed. I don’t usually support phrases like “race traitor” but I’ll make an exception here.

Justice Department announces it will end the use of private prisons – although remember that this directive applies only to the federal level. Since we are not allowed to have unallayed happiness about a nice thing, here’s Jacob Levy on why we can’t feel good about this. Related: DoJ says poor people cannot be detained for being unable to afford bail. Also related: DoJ says it’s not going to prosecute people who use marijuana in accordance with state laws.

Latest replication failure: forcing someone to smile does not make them happy. And a forest plot for you. Darn, I actually believed that one.

Most recent development in Dubai’s efforts to become an outright dystopia: they can arrest people for fundraising for charity.

Cracked with a surprisingly sophisticated (and scary) look into abuse in psychiatric institutions.

You probably think that there is no reason to read an entire New York Times article on the ankles of Michelangelo’s David, but it’s actually really poignant and well-written and gives you a good feel for the time period.

Finding: kids whose parents divorce seem to do worse. Problem: maybe this is genetically confounded – eg parents have some flaws that lead them to divorce, and which also get transmitted down to their kids. Solution: well, there are a lot of possible solutions, but one I wouldn’t have thought of is to correlate children’s outcomes with number of women at the father’s workplace. The theory is that fathers are more likely to divorce if they have lots of female co-workers – more opportunities for affairs, I guess – and there aren’t a lot of other good ways that your father having many female co-workers could make you do worse in life [citation needed], so this is an “exogenous” cause of divorce and sort of like running a quasi-experiment. Results: children whose fathers have more female co-workers do indeed do worse in life, in the ways we would predict if divorce had lasting effects on children. I am pretty skeptical of this finding – they try to control for things like “richer men might work in more white-collar industries with more women”, but I don’t really trust statistical controls that much. But as one of many studies in this area it mostly accords with what I thought the last time I reviewed the research.

Using the caduceus as a symbol of medicine is mythologically incorrect (h/t Ben Hoffman).

Somebody tell me whether this surprising claim is true or totally made up: Reason claims that no matter what the tax rate, government revenue is always 19% of GDP.

People’s obesity is unrelated to that of their adoptive parents, but strongly related to that of their genetic parents.

FiveThirtyEight has a really interesting analysis of welfare reform (at least the TANF program), which concludes that there’s only been a small decrease in total amount of dollars going to “welfare”, but it’s shifted from cash transfers to poor people, to sponsoring classes/programs/bureaucracies that supposedly help poor people indirectly.

Dublin, California is experimenting with a new mass transit policy in which they subsidize Uber rides for needy travelers in their city. It’s supposed to cost the city about the same amount as bus subsidies, and passengers only slightly more than bus fares, while vastly increasing poor people’s mobility and ability to work to their own schedule. This sounds so amazing that I’m sure somebody is already working to make it illegal.

Contrary to previous belief, places with an excess of men over women are not necessarily prone to social instability.

I thought Steven Pinker was mostly okay, but he’s gone off the deep end lately with his theory that worrying about AI is just some kind of evolutionary psychology thing where men worry about other men being more alpha male than they are. Of course this is getting shared all over the Internet with titles like Ever Wonder Why Only Men Fear An AI Takeover? Of course, as people were quick to point out, multiple surveys show women express more fear of AI than men, plus the whole idea is ridiculous to anyone who has actually studied AI risk in any kind of serious way, and offensive to people who try to do evolutionary psychology responsibly. But I’m sure everyone involved has gotten their clicks and advertising dollars, not to mention their chance to express cheap stereotypes, and with 99% certainty no one will feel the slightest need to apologize for any of it. This reminds me how everybody who covers Silicon Valley has to write articles about how “white” it is, even though it’s one of the least white industries in the country and possibly >50% minority.

You know those sex-ed programs that give teenagers fake babies that really cry so they know how annoying having a baby is and presumably avoid teenage pregnancy? Yeah. They don’t work and may increase teen pregnancy. But I am super suspicious of this. It shows a single short assignment with these fake babies raises pregnancy from 11% to 17%. If this is true it’s the most amazing pro-fertility intervention ever known to mankind and needs to be rolled out in Japan immediately. This is what I mean when I say I am doubtful of studies where tiny interventions seem to produce life-changing results.

“But without government, who would build the roads?!” (h/t Jason Kuznicki)

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