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Investing Is More Luck Than Talent - Issue 44: Luck

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Depending on which economist you ask, big inequalities in wealth are either an essential engine for growth—the reward that motivates people to work hard, innovate, and prosper—or a ticking time bomb capable of unleashing mass misery, social upheaval, or even violent revolution.

The academic researchers who study inequality are forever arguing about where that tipping point lies, and how much inequality is too much. Many observers wonder if we’ve begun to tip already, pointing to the surprisingly strong support enjoyed by the avowed socialist Bernie Sanders in the recent United States presidential election.

But what no one can deny is that in many countries around the globe, inequality has reached eye-popping extremes. In the U.S., for example, the top 1 percent of the population holds 42 percent of the national wealth. And the top 100 individuals now have an average wealth roughly 45,000 times the national average.

Where do such massive differences in wealth come from? The positive narrative surrounding inequality might chalk them up to the talent and effort of high earners. Social critics will also cite the many ways that talent and effort can be frustrated by prejudices based on class, race, or gender. Both sets of factors…
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nikolap
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The Secret of Buckminister Fuller’s World-Changing Ideas Was Serendipity - Facts So Romantic

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In his 2016 book, You Belong to the Universe, Jonathon Keats sets out to release Buckminister Fuller from “the zany sci-fi designs that made him notorious, and rescue him from the groupies who have impounded him as a cultish prophet.”

Keats, a writer and artist who whips up his own world-changing ideas through trickster gallery and museum exhibitions, comes to Fuller’s rescue by venturing beneath the veneer of his infamous inventions—the geodesic dome, flying car, world peace games, and dome over Manhattan—to expose their broader significance. 

That significance can be summed up in the unwieldy title that Fuller gave himself: “comprehensive anticipatory design scientist.” The most succinct definition of the title is Fuller’s determination, he said, “to make the world work for 100 percent of humanity, in the shortest possible time, through spontaneous cooperation, without ecological offense or the disadvantage of anyone.”

The reason he wanted to make a flying car was because his first daughter died of meningitis.

As Keats points out, Fuller’s 100 percent ethos was prophetic “and only becomes more resonant in a society where half the world’s wealth is held by the wealthiest 1 percent.”

One of the qualities Keats most admires in…
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nikolap
5 days ago
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Did Media Literacy Backfire?

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Anxious about the widespread consumption and spread of propaganda and fake news during this year’s election cycle, many progressives are calling for an increased commitment to media literacy programs. Others are clamoring for solutions that focus on expert fact-checking and labeling. Both of these approaches are likely to fail — not because they are bad ideas, but because they fail to take into consideration the cultural context of information consumption that we’ve created over the last thirty years. The problem on our hands is a lot bigger than most folks appreciate.

CC BY 2.0-licensed photo by CEA+ | Artist: Nam June Paik, “Electronic Superhighway. Continental US, Alaska & Hawaii” (1995).

What Are Your Sources?

I remember a casual conversation that I had with a teen girl in the midwest while I was doing research. I knew her school approached sex ed through an abstinence-only education approach, but I don’t remember how the topic of pregnancy came up. What I do remember is her telling me that she and her friends talked a lot about pregnancy and “diseases” she could get through sex. As I probed further, she matter-of-factly explained a variety of “facts” she had heard that were completely inaccurate. You couldn’t get pregnant until you were 16. AIDS spreads through kissing. Etc. I asked her if she’d talked to her doctor about any of this, and she looked me as though I had horns. She explained that she and her friends had done the research themselves, by which she meant that they’d identified websites online that “proved” their beliefs.

For years, that casual conversation has stuck with me as one of the reasons that we needed better Internet-based media literacy. As I detailed in my book It’s Complicated: The Social Lives of Networked Teens, too many students I met were being told that Wikipedia was untrustworthy and were, instead, being encouraged to do research. As a result, the message that many had taken home was to turn to Google and use whatever came up first. They heard that Google was trustworthy and Wikipedia was not.

Understanding what sources to trust is a basic tenet of media literacy education. When educators encourage students to focus on sourcing quality information, they encourage them to critically ask who is publishing the content. Is the venue a respected outlet? What biases might the author have? The underlying assumption in all of this is that there’s universal agreement that major news outlets like the New York Times, scientific journal publications, and experts with advanced degrees are all highly trustworthy.

Think about how this might play out in communities where the “liberal media” is viewed with disdain as an untrustworthy source of information…or in those where science is seen as contradicting the knowledge of religious people…or where degrees are viewed as a weapon of the elite to justify oppression of working people. Needless to say, not everyone agrees on what makes a trusted source.

Students are also encouraged to reflect on economic and political incentives that might bias reporting. Follow the money, they are told. Now watch what happens when they are given a list of names of major power players in the East Coast news media whose names are all clearly Jewish. Welcome to an opening for anti-Semitic ideology.

Empowered Individuals…with Guns

We’ve been telling young people that they are the smartest snowflakes in the world. From the self-esteem movement in the 1980s to the normative logic of contemporary parenting, young people are told that they are lovable and capable and that they should trust their gut to make wise decisions. This sets them up for another great American ideal: personal responsibility.

In the United States, we believe that worthy people lift themselves up by their bootstraps. This is our idea of freedom. What it means in practice is that every individual is supposed to understand finance so well that they can effectively manage their own retirement funds. And every individual is expected to understand their health risks well enough to make their own decisions about insurance. To take away the power of individuals to control their own destiny is viewed as anti-American by so much of this country. You are your own master.

Children are indoctrinated into this cultural logic early, even as their parents restrict their mobility and limit their access to social situations. But when it comes to information, they are taught that they are the sole proprietors of knowledge. All they have to do is “do the research” for themselves and they will know better than anyone what is real.

Combine this with a deep distrust of media sources. If the media is reporting on something, and you don’t trust the media, then it is your responsibility to question their authority, to doubt the information you are being given. If they expend tremendous effort bringing on “experts” to argue that something is false, there must be something there to investigate.

Now think about what this means for #Pizzagate. Across this country, major news outlets went to great effort to challenge conspiracy reports that linked John Podesta and Hillary Clinton to a child trafficking ring supposedly run out of a pizza shop in Washington, DC. Most people never heard the conspiracy stories, but their ears perked up when the mainstream press went nuts trying to debunk these stories. For many people who distrust “liberal” media and were already primed not to trust Clinton, the abundant reporting suggested that there was something to investigate.

Most people who showed up to the Comet Ping Pong pizzeria to see for their own eyes went undetected. But then a guy with a gun decided he “wanted to do some good” and “rescue the children.” He was the first to admit that “the intel wasn’t 100%,” but what he was doing was something that we’ve taught people to do — question the information they’re receiving and find out the truth for themselves.

Experience Over Expertise

Many marginalized groups are justifiably angry about the ways in which their stories have been dismissed by mainstream media for decades. This is most acutely felt in communities of color. And this isn’t just about the past. It took five days for major news outlets to cover Ferguson. It took months and a lot of celebrities for journalists to start discussing the Dakota Pipeline. But feeling marginalized from news media isn’t just about people of color. For many Americans who have watched their local newspaper disappear, major urban news reporting appears disconnected from reality. The issues and topics that they feel affect their lives are often ignored.

For decades, civil rights leaders have been arguing for the importance of respecting experience over expertise, highlighting the need to hear the voices of people of color who are so often ignored by experts. This message has taken hold more broadly, particularly among lower and middle class whites who feel as though they are ignored by the establishment. Whites also want their experiences to be recognized, and they too have been pushing for the need to understand and respect the experiences of “the common man.” They see “liberal” “urban” “coastal” news outlets as antithetical to their interests because they quote from experts, use cleaned-up pundits to debate issues, and turn everyday people (e.g., “red sweater guy”) into spectacles for mass enjoyment.

Consider what’s happening in medicine. Many people used to have a family doctor whom they knew for decades and trusted as individuals even more than as experts. Today, many people see doctors as arrogant and condescending, overly expensive and inattentive to their needs. Doctors lack the time to spend more than a few minutes with patients, and many people doubt that the treatment they’re getting is in their best interest. People feel duped into paying obscene costs for procedures that they don’t understand. Many economists can’t understand why so many people would be against the Affordable Care Act because they don’t recognize that this “socialized” medicine is perceived as experts over experience by people who don’t trust politicians who tell them what’s in their best interest any more than they trust doctors. And public trust in doctors is declining sharply.

Why should we be surprised that most people are getting medical information from their personal social network and the Internet? It’s a lot cheaper than seeing a doctor, and both friends and strangers on the Internet are willing to listen, empathize, and compare notes. Why trust experts when you have at your fingertips a crowd of knowledgeable people who may have had the same experience as you and can help you out?

Consider this dynamic in light of discussions around autism and vaccinations. First, an expert-produced journal article was published linking autism to vaccinations. This resonated with many parents’ experience. Then, other experts debunked the first report, challenged the motivations of the researcher, and engaged in a mainstream media campaign to “prove” that there was no link. What unfolded felt like a war on experience, and a network of parents coordinated to counter this new batch of experts who were widely seen as ignorant, moneyed, and condescending. The more that the media focused on waving away these networks of parents through scientific language, the more the public felt sympathetic to the arguments being made by anti-vaxxers.

Keep in mind that anti-vaxxers aren’t arguing that vaccinations definitively cause autism. They are arguing that we don’t know. They are arguing that experts are forcing children to be vaccinated against their will, which sounds like oppression. What they want is choice — the choice to not vaccinate. And they want information about the risks of vaccination, which they feel are not being given to them. In essence, they are doing what we taught them to do: questioning information sources and raising doubts about the incentives of those who are pushing a single message. Doubt has become tool.

Grappling with “Fake News”

Since the election, everyone has been obsessed with fake news, as experts blame “stupid” people for not understanding what is “real.” The solutionism around this has been condescending at best. More experts are needed to label fake content. More media literacy is needed to teach people how not to be duped. And if we just push Facebook to curb the spread of fake news, all will be solved.

I can’t help but laugh at the irony of folks screaming up and down about fake news and pointing to the story about how the Pope backs Trump. The reason so many progressives know this story is because it was spread wildly among liberal circles who were citing it as appalling and fake. From what I can gather, it seems as though liberals were far more likely to spread this story than conservatives. What more could you want if you ran a fake news site whose goal was to make money by getting people to spread misinformation? Getting doubters to click on clickbait is far more profitable than getting believers because they’re far more likely to spread the content in an effort to dispel the content. Win!

CC BY 2.0-licensed photo by Denis Dervisevic.

People believe in information that confirms their priors. In fact, if you present them with data that contradicts their beliefs, they will double down on their beliefs rather than integrate the new knowledge into their understanding. This is why first impressions matter. It’s also why asking Facebook to show content that contradicts people’s views will not only increase their hatred of Facebook but increase polarization among the network. And it’s precisely why so many liberals spread “fake news” stories in ways that reinforce their belief that Trump supporters are stupid and backwards.

Labeling the Pope story as fake wouldn’t have stopped people from believing that story if they were conditioned to believe it. Let’s not forget that the public may find Facebook valuable, but it doesn’t necessarily trust the company. So their “expertise” doesn’t mean squat to most people. Of course, it would be an interesting experiment to run; I do wonder how many liberals wouldn’t have forwarded it along if it had been clearly identified as fake. Would they have not felt the need to warn everyone in their network that conservatives were insane? Would they have not helped fuel a money-making fake news machine? Maybe.

But I think labeling would reinforce polarization — but it would feel like something was done. Nonbelievers would use the label to reinforce their view that the information is fake (and minimize the spread, which is probably a good thing), while believers would simply ignore the label. But does that really get us to where we want to go?

Addressing so-called fake news is going to require a lot more than labeling.It’s going to require a cultural change about how we make sense of information, whom we trust, and how we understand our own role in grappling with information. Quick and easy solutions may make the controversy go away, but they won’t address the underlying problems.

What Is Truth?

As a huge proponent for media literacy for over a decade, I’m struggling with the ways in which I missed the mark. The reality is that my assumptions and beliefs do not align with most Americans. Because of my privilege as a scholar, I get to see how expert knowledge and information is produced and have a deep respect for the strengths and limitations of scientific inquiry. Surrounded by journalists and people working to distribute information, I get to see how incentives shape information production and dissemination and the fault lines of that process. I believe that information intermediaries are important, that honed expertise matters, and that no one can ever be fully informed. As a result, I have long believed that we have to outsource certain matters and to trust others to do right by us as individuals and society as a whole. This is what it means to live in a democracy, but, more importantly, it’s what it means to live in a society.

In the United States, we’re moving towards tribalism, and we’re undoing the social fabric of our country through polarization, distrust, and self-segregation. And whether we like it or not, our culture of doubt and critique, experience over expertise, and personal responsibility is pushing us further down this path.

Media literacy asks people to raise questions and be wary of information that they’re receiving. People are. Unfortunately, that’s exactly why we’re talking past one another.

The path forward is hazy. We need to enable people to hear different perspectives and make sense of a very complicated — and in many ways, overwhelming — information landscape. We cannot fall back on standard educational approaches because the societal context has shifted. We also cannot simply assume that information intermediaries can fix the problem for us, whether they be traditional news media or social media. We need to get creative and build the social infrastructure necessary for people to meaningfully and substantively engage across existing structural lines. This won’t be easy or quick, but if we want to address issues like propaganda, hate speech, fake news, and biased content, we need to focus on the underlying issues at play. No simple band-aid will work.


Special thanks to Amanda Lenhart, Claire Fontaine, Mary Madden, and Monica Bulger for their feedback!

This post was first published as part of a series on media, accountability, and the public sphere. See also:

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nikolap
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tante
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"Did Media Literacy backfire"? (On tribalism and news contexts)
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The Candle Burned - Issue 43: Heroes

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 Andrey Petrovich had given up all hope when the videophone rang.

“Hello, I saw your ad. You give private literature lessons?”

Andrey Petrovich peered at the man on the screen. He was about thirty, with an open smile and serious eyes, dressed in a suit and tie. Andrey Petrovich’s heart skipped a beat. Posting the ad on the Net had become but a hapless habit. In the past ten years he had received six responses. Three callers had dialed the wrong number, two others were old-fashioned insurance salesmen who still made phone calls, and the last one had confused literature with legislature.

“Y-yes, I d-do,” Andrey Petrovich stuttered anxiously. “In my apartment. You are interested in literature?”

“I am,” the man nodded from the screen, and introduced himself. “My name is Maksim. How much do you charge?”

Andrey Petrovich almost blurted, “it’s free,” but caught himself. “Rates are per hour. And negotiable.” He took a deep breath. “When would you like to start?”

“Well, I… you see,” Maksim started.

“First lesson is free,” Andrey Petrovich said quickly. “If you don’t like it, there’s no obligation.”

“Let’s start tomorrow then,” Maksim said definitively. “Are you free at ten in the morning?…
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Is the Chinese Language a Superstition Machine? - Issue 44: Luck

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Every year, more than a billion people around the world celebrate Chinese New Year and engage in a subtle linguistic dance with luck. You can think of it as a set of holiday rituals that resemble a courtship. To lure good fortune into their lives, they may decorate their homes and doors with paper cutouts of lucky words or phrases. Those who need a haircut make sure to get one before the New Year, as the word for “hair” (fa) sounds like the word for “prosperity”—and who wants to snip away prosperity, even if it’s just a trim? The menu of food served at festive meals often includes fish, because its name (yu) sounds the same as the word for “surplus”; a type of algae known as fat choy because in Cantonese it sounds like “get rich”; and oranges, because in certain regions their name sounds like the word for “luck.”

English speakers can relish a good pun, and messing around with homophones (words that sound the same but have different meanings) is a staple of many a clever ad. But Chinese practices take punning to a whole new level—one that reaches deep into a culture where good fortune is…
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SSC Journal Club: Mental Disorders As Networks

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I.

Suppose you have sniffles, fatigue, muscle aches, and headache. You go to the doctor, who diagnoses you with influenza and gives you some Tamiflu.

There’s some complicated statistics going on here. Your doctor has noticed some observable variables (sniffles, fatigue, etc) – and inferred the presence of an invisible latent variable (influenza). Then, instead of treating the symptoms with eg aspirin for the headache, she treats the latent variable itself, expecting its effects to disappear along with it.

Psychiatry tries to use the same model. You get some symptoms – depressed mood, insomnia, fatigue, feelings of worthlessness, suicidality. You go to the psychiatrist, who diagnoses you with depression and gives you an antidepressant.

The psychiatrist is implicitly assuming that the causal structure of her field matches the causal structure of better-understood diseases like influenza. Generations of psychiatrists have noticed that different symptoms all tend to show up together and follow a similar pattern, suggesting some kind of deep connection between them. So psychiatrists follow the influenza model and attribute this collection of linked symptoms to a latent variable called “depression”.

This gets complicated really fast. Psychiatric disorders are diagnosed through clusters of symptoms, but we don’t expect every person to have every symptom in the cluster. For example, we diagnose depression when a patient has five out of nine symptoms on a list including fatigue, guilt, sleep disturbance, suicidality, et cetera. Each of these symptoms is often but not always present in a patient who has most of the others – for example, 75% of depressed patients have sleep disturbances, but 25% don’t.

But all psychiatric disorders are hopelessly comorbid with each other. If someone meets criteria for one DSM disorder, there’s a 50% chance they’ll have another one too. 60% of people with major depression also have an anxiety disorder. This is awkward when compared to eg the 75% sleep disturbance rate. Why are we calling sleep disturbance a “symptom” of depression, but anxiety a “comorbid condition” with depression? If we’re trying to cluster symptoms together to identify conditions, how come “sleep” is grouped with a bunch of other symptoms in the depression cluster, but “anxiety” gets to be a cluster of its own? Are there really two conditions called “depression” and “anxiety”, or just one big condition that has various symptoms including low mood, sleep disturbance, and anxiety, and some people get some of the symptoms and other people get others? I’m told that the people who write the DSM have really conversations about this using rigorous methods, but to the rest of us it seems kind of arbitrary.

The problem isn’t that nothing ever clusters together – depression, for example, is a very natural category. But so are various subtypes of depression. And so are various supertypes of depression, like depression + anxiety, or depression + psychosis, or depression + anxiety + psychosis. Choosing to draw the borders around depression and say “Yup, this is the Actual Disease” isn’t a bad choice, but it doesn’t jump out of the data either. When people try to use sophisticated clustering algorithms on psychiatric disorders, they usually come up with something like this, where there are only three supercategories instead of the 297 different diagnoses in the DSM. And even three supercategories are pushing it – people with psychosis are far more likely to have depression too! Having any number of categories starts seeming arbitrary and fuzzy.

So Nuijten, Deserno, Cramer, and Borsboom (from here on: NDCB) ask: what if that’s wrong? What if there isn’t a latent variable like “influenza”? What if it’s symptoms all the way down?

Consider a network in which each symptom is a node, connected to all the others by pathways with certain weights on each direction. So for example, “sleep disturbance” might be connected to “fatigue” by a strong path – people with disturbed sleep are much more likely to be tired. These might both be connected to “low mood” – people who don’t sleep well, or who are tired all the time, start feeling down about themselves. And this path might go the other way too: people who feel down about themselves might have more trouble getting to sleep on time. And maybe all of these are connected to suicidality, because if you feel bad about yourself you’re more likely to commit suicide, and if you’re suicidal you might feel bad about it, and if you’re tired all the time then maybe you can’t accomplish anything useful with your life and so death might seem like a good way out, and so on.

A sample image from the paper, showing two possible simple networks of depression symptoms

Also from the paper. This shows a more complicated (and apparently empirically validated) network of symptoms. MD is major depression. GAD is generalized anxiety disorder. The nodes are all different symptoms – for example, “inte” is “loss of interest in activities” and “musc” is “muscle tension”.

Not from the paper. But if you figure out a good way to calculate weights on this one, email me.

Each node might affect the others with a certain delay. Being suicidal might make you feel guilty, but even if your last suicidal thought was fifteen minutes ago, you might still feel guilty now. Maybe it would take months or even years before you no longer felt guilty about your suicidal thoughts. So there could be loops: in a simple model, your low mood makes you feel suicidal, your suicidality makes you feel guilty, and your guilt makes you have low mood. This type of loopy network might be stable and self-reinforcing. Maybe your boss yells at you at work, which makes you have a bad mood. Then even if the direct effect of your boss would go away quickly, if it causes suicidal thoughts which cause guilt which cause more low mood, then the cycle can stick around forever.

In NDCB’s model, all possible psychiatric symptoms are connected like this in a loose network. Particularly tight-knit symptom clusters that often active together and reinforce each other correspond to the well-known and well-delineated psychiatric diseases, like depression and schizophrenia. But there are no natural boundaries in the network; low mood and poor sleep may be closely connected to each other, but they’ll also be more distantly connected to anxiety, and even more distantly connected to psychosis. This corresponds to the fact that some depressed people will develop psychotic symptoms, even though psychosis isn’t usually associated with depression. The paths aren’t usually as strong as those between low mood and poor sleep, but they’re there, and in some people with a predisposition to psychosis or some idiosyncratic factor strengthening those paths beyond their usual level in the population, that will be enough.

There are lots of good things about thinking about psychiatric problems this way:

1. It helps explain how life stressors can cause depression. Some people who have a bad breakup will get depressed. This should be mysterious if we think of depression as a biological illness – and we have to at least a little; some people who take the drug interferon-alpha will get depressed afterwards too. But if depression is a symptom network, it becomes easier to explain. The bad breakup causes low mood, which under the right conditions and genetic predispositions can activate all of the other depression symptoms and create a stable, self-reinforcing depression. Likewise, poor sleep is a risk factor for the development of subsequent depression, which is hard to explain if we just think of it as a symptom of some latent-variable-style condition.

2. It explains how treating depression symptoms can treat the depression. I’ve heard a lot of different perspectives on this, but at least one of my attendings (and some studies) believes that treating poor sleep with a sleeping pill like Ambien can help dispel an underlying depression, including symptoms seemingly unrelated to sleep like “feelings of worthlessness and guilt”.

3. It explains how therapy can treat depression. If eg cognitive behavioral therapy helps you stop thinking of yourself as worthless, then you’ve de-activated the “feelings of worthlessness and guilt” node and made it a lot harder for all the other nodes to coalesce into a stable self-reinforcing pattern.

4. It explains the polygenic structure of mental illnesses. If a mental illness were one specific thing, we would expect it to have one specific cause, or at least be limited to genes active in one specific area or process. In fact, it’s hard to come up with anything that genes involved in these illnesses have in common other than “they’re mostly expressed in the brain” – and sometimes not even that. In NDBC’s model, genes might be involved in any of the symptoms, or in the paths between the symptoms. A gene involved in poor sleep could predispose to depression. So could a gene involved in low energy levels. Even a gene involved in anxiety or psychosis could have some effect. And so would any gene that influenced the probability that, given poor sleep, a person would have low energy levels; or that given anxiety, a person will have psychosis. The end result would be everyone having a slightly different network, with different amounts of work needed to activate each node and different weights on each of the inter-nodal paths.

5. It helps explain why so many brilliant people searching for The One True Cause Of Depression have come up empty.

II.

Actually, this last one deserves more explanation. NDCB think of these symptoms as visible patient complaints (“poor sleep”, “feelings of worthlessness”), and treat the connections between them as common sense (“if you don’t sleep, you’ll probably be fatigued”, “if you feel very guilty, you might attempt suicide because you think you deserve to die”). But their theory also works for networks of biological dysfunctions, or networks that combine biological dysfunctions with common-sense observed symptoms.

For example, we know that there’s a link between depression and inflammation. But it’s not a very good link; not all depressed people have increased inflammation, not all people with increased inflammation get depressed, and drugs that decrease inflammation don’t always cure depression. There’s similarly good evidence linking depression to folate metabolism, serotonergic neurotransmission, BDNF levels, and so on. Suppose we made a graph like the ones above, except that instead of putting things like “poor sleep” and “feelings of guilt” on it, we used “inflammatory dysfunction”, “folate metabolism dysfunction”, “serotonin dysfunction”, and “BDNF dysfunction”. There are a lot of reasons to expect these things to interconnect – for example, folate helps produce a cofactor necessary for serotonin synthesis, so any dysfunction in folate metabolism could make a problem with serotonergic neurotransmission more likely.

In a best case scenario we could merge the biological and psychological perspective, replacing “disturbed sleep” with “disturbance in the orexin and histamine systems that regulate sleep” and “tiredness” with “disturbance in the dopamine system that regulates goal-directed action”, and so “poor sleep makes you tired” with “disturbance in the orexin system causes a disturbance in the dopamine system”. In practice I expect this would be a terrible idea and that common-sense concepts mostly don’t have simple well-delineated biological equivalents. But what I’m saying is that the model where all of these things are observable symptoms, and the model where they’re all disturbances in brain chemicals and metabolism, aren’t necessarily in conflict.

So we can expand point (5) to say not only that it explains why nobody has found the One True Depression Cause, but why they have found so many promising leads that never quite pan out. Just like depression has a bunch of different symptoms, each of which is often-but-not-always involved, and each of which reinforces the others — so it has a bunch of different disturbances in biological systems, each of which is often-but-not-always involved, and each of which reinforces the others. Maybe there’s a nice correspondence between one disrupted biological system and one symptom, or maybe they sit uneasily together as different nodes on the same big graph.

III.

Are there any problems with this theory?

There are a couple of disorders that really don’t fit this model. Bipolar disorder, for example, doesn’t quite work as a collection of self-reinforcing symptoms. It’s marked by depressive episodes that can give way to years of stable mood before the person has a manic episode months or years later. I can’t think of any way to model this except as some underlying unified tendency toward bipolar disorder – although the ability for this tendency to cause a depression that looks just like normal unipolar depression is a point in NDCB’s favor, since it suggests there can be many different causes for the same syndrome.

The impressive success of ketamine also counts as a point against. NDCB imagine psychiatric disorders like depression as gradually fading out on a symptom-by-symptom basis, eventually reaching a point where enough symptoms are gone that the rest of them aren’t self-reinforcing and just sputter out. This matches the course of eg SSRI treatment, where the medications will gradually improve a few symptoms at at time over the space of a month or so and maybe cause a full remission if you’re lucky. It doesn’t really match ketamine, where every aspect of depression vanishes instantly, then returns after a week or so without treatment. There are a couple of other equally impressive things – staying awake for thirty hours straight, for example, can have an immediate and near-miraculous antidepressant effect, which unfortunately vanishes as soon as you go to sleep. Both of these treatments seem like direct strikes against the One True Cause Of Depression, and both suggest that an underlying tendency toward depression can exist separate from any symptoms (or else why would the depression come back after the effects of the ketamine wore off?)

I don’t think it’s possible to cure depression by blasting every symptom simultaneously. That is, suppose somebody is depressed with symptoms of poor sleep, poor appetite, low energy, suicidality, and low mood. Ambien can make them sleep. Pot can make them eat. Adderall can give them energy. Clozaril can make them stop wanting to kill themselves. And heroin can perk up mood. So if you gave someone Ambien, pot, Adderall, Clozaril, and heroin at the same time, would that cure their depression? I’m pretty sure no one has ever tried this, but I don’t think anyone’s reported exceptional results from less extreme cocktails like Adderall + trazodone + pot, which I’m sure a bunch of people end up taking. This along with the stuff from the last paragraph suggests that if we want to go with this model, maybe we should think less in terms of actual poor sleep and more in terms of dysfunction in the biological system of which sleep is a visible correlate. In that case we could say that Ambien helps the sleep itself but not the underlying dysfunction. But that takes some of the elegance out of the theory.

Despite these issues, I feel like something along these lines has to be true. There are too many things that sort of kind of cause psychiatric problems, and too few things that look like One True Causes. Things that look a lot like schizophrenia can be caused by viral infections in utero, by genetic factors, by hitting your head really hard as a child, by hypoxia during the birthing process, by something something something intestinal tract, by something relating to immigration which seems like it might involve psychosocial stress, and so on. Studies of the immune system, the dopamine system, the glutamate system, and the kynurenine system have all found disruptions. There have been so many really brilliant attempts to reduce all of these to a single brain region, or the levels of one specific chemical, or something that’s simple in the same way that lack-of-insulin-causes-diabetes is simple. But nobody’s ever succeeded. Maybe we should just give up.

I guess I’ve felt for a long time that some kind of weird change in attractor states of biological systems is the best way to explain these kinds of things, but I was never able to express what I meant coherently besides “weird change in attractor states of biological systems”. NDCB offer a clear model that suggests good avenues for future research.

(And I wasn’t joking when I said that little diagram with the two pentagons was the solution to 25% of extant philosophical problems.)

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nikolap
39 days ago
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Zagreb, Croatia
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gradualepiphany
38 days ago
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Interesting.
Los Angeles, California, USA
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