Status 451

Sometimes it seems like the cold war never ended.

The western world is ostensibly a free-market democracy, and yet you could be forgiven for thinking otherwise. Corporations are universally reviled, sometimes with hilarious results. The socialist running for US president is widely beloved, while the business owner is a public joke. Academia and the more elite publications will, behind closed doors, admit they thought the former СССР had some good ideas. Despite what it says in our history books, this memetic conflict is still ongoing.

I don’t care so much about what name we give to Moloch. I’m much more interested in the things people say, the ways they behave when engaging in this cosmic struggle. It’s quite curious.

Despite our political squabbles, most people generally hold the same object-level beliefs. Our ideas regarding morality are largely the same. Murder is bad. Love is good. Don’t hurt other people. That sort of thing. At the end of the day, this is why we all do the things we do. Further, it’s not too difficult to judge whether something achieves these goals or not. While it’s hard to really predict the long term effects a given policy will have on society, we can all generally agree on which systems work and which systems fail. So why do we disagree so viciously on politics when we agree on the goals and have objective ways to measure them?

The big clue to me was when I started to notice, in the US anyway, that someone’s professed party often doesn’t do the things you would expect it to do from first principles. Republican ‘pro-business’ policies often give preferential treatment to certain businesses at the expense of others. Democrat social policies have a strange tendency to backfire on the poor and reward the upper-middle class. It’s almost as if people value Being A Democrat (Republican) more than they value actually achieving Democrat (Republican) goals.

When you see an obvious contradiction, and nobody else seems bothered by it, that’s a clue to look deeper. Many people are better at understanding than communicating. Perhaps something illegible is going on. Maybe a deeper cause drives this difference, and all we see is the bad explanation.

For all people’s opinions on social policy, they’re shockingly bad at systems thinking. People think, “X will solve our problems,” and go about trying to do X. What they fail to realize is that systems are dynamic and chaotic. If you do X to a system, the system will react. If your path to X is “do X until it’s done”, the system will push back, and you’ll never get anywhere. You can’t do X directly. You have to figure out something else, something that leads to X. If you aim where X is, you will miss. You have to aim at where X will be.

The key to all of this is incentives. Incentives matter. Anything you do to society will only change it today. But if you change the incentives, you will forevermore change what society will do in the future. There are implicit incentives in all our decisions. It seems people rarely give them the attention they deserve. But it’s interesting to look at the incentives that fall out of different policies, and ponder what they might mean.

As I said before, communism, capitalism, I don’t find this argument interesting. But the incentives that fall out of communism and capitalism in practice, these are fascinating. We have all these ideas in our heads, from society, from the media, about what these mean, but the incentives tell a different story. Following the incentives, the fundamental difference between the two is central planning. The naïve intuition might frame this as redistribution, but that’s not quite correct. There are ways to redistribute wealth in a decentralized fashion, but communism never implements itself that way.

Communism is fundamentally central planning. The core idea of communism is that we can identify coordination failures in systems, and if we could avoid them it would be better. Avoiding them necessitates an overseer, who can supervise and step in when necessary. This overseer is necessarily centralized.

Capitalism (or, more precisely, free markets) is fundamentally decentralization. The core idea of free markets is that by empowering a million people to make a million decisions for themselves, their incentives for success and against failure are stronger, and the diversity of experimentation will generate more and better solutions over time. This system does not work when a single director ultimately makes decisions.

As an illustration, consider the medical industry. Well, the medical industry in the US is a horrendously bad example of a free market, so consider the relatively free case of nonessential surgeries at private clinics.

I’ve lived in the US for many years, and I am a Canadian citizen. I have ample experience with both medical systems. The difference is a useful illustration of my point.

Consider knee replacement surgery. This surgery is nonessential, nobody will die without knee replacements, but it is significant for quality of life. In the US, if I need a knee replacement, I will go to a clinic, make an appointment, have the surgery next week, and a month later receive a bill for fifty thousand dollars. In Canada, I will go to my doctor, get on a waiting list, wait at least six months, have my surgery, and pay fifty bucks for some painkillers. The reason why medical care is astronomical in the US is well documented, but what’s up with Canada? Why does it take so long? The difference is in the incentives created by the US’s markets and Canada’s socialism.

In the US, a million people who need knee replacement are each able to weigh the costs and benefits of surgery, and make the right decision for themselves on whether or not to go under the knife. In Canada, this decision is ultimately delegated down to a central agency. Instead of a million people making a million decisions, one person (or committee) is making one million decisions on behalf of one million people.

This is an unmanageable burden. One person can’t do the work of a million people. That’s why most modern communistic proposals imagine massive computer systems to take on this burden. Failing that, the only way to manage this burden is to turn a million illegible decision processes into one simple, scalable bureaucratic policy.

A result of this is that the policy necessarily must be one-size-fits-all. Sure, it can be complicated, with exceptions carved out for this, that, or the other group. But the exceptions are still based on relatively simple factors such as demographic group membership. The process can’t mold itself to fit an individual’s needs. And it can’t react in real-time to shifting conditions in the environment. It’s restricted to a predefined set of procedures to be used in different contingencies

Additionally, the central authority’s ability to make the correct policies is limited. A central authority can’t possibly know what a million people want better than they do. It must accept trade-offs. The most common one is legibility. Earlier I mentioned that people often understand better than they communicate. The central planner’s policies can only be based on what people can communicate. They must engage in some streetlight sociology.

The end result is that communistic policies treat the systems they apply to as static systems, out of necessity. In the socialized healthcare of Canada, the central health agency is given a budget and told to optimize given that budget. The amount of resources they can bring to bear on the problem is ultimately fixed; all they can do is use them wisely. If a million people want knee replacements, and we can only afford 200,000 a year, a hell of a lot of people are going to be on wait lists.

In the free, decentralized system of the US, this doesn’t happen. The system is dynamic and open. It readily exchanges resources with the outside world. More people wanting knee replacements doesn’t stretch a fixed budget; it makes more resources available! Alternatively, as the price rises, more people are able to decide for themselves that it’s not worth the cost, and drop out of the pool of waiting patients. Nobody needs to preemptively put themselves on a wait list.

The tradeoff is cost. It sounds optimistic when I say “more resources available to provide more knee replacements,” but remember, resources means money. More knee replacements means that more money gets spent, in total. It is more expensive, in total. The budgetary mindset of the central planner allows them to aggressively drive down the price of the surgery, at the expense of other, non-monetary factors (opportunity cost, time, quality of service). In the US, no such compromise on service quality takes place; you simply spend more money instead.

It’s this difference in mindset, I think, that is at the heart of the deep political differences between socialists and free marketeers. If you’ll let me engage in a bit of armchair evolutionary psychology for a moment, consider the following. In situations where the pool of resources is fixed, the budgetary mindset makes sense. There is no chance the pool of resources will grow, so having a central authority allocate the resource makes sense. The alternative would be waste and instability in the service of a goal that we’ve already hypothesized is impossible.

On the other hand, very few resources are truly fixed, and rarely are they permanently so. In many cases, taking the central allocation approach is unnecessary, and retards the experimentation and diversity the leads to growing the resources you have.

It’s plausible that both types of situations were common throughout human history. In times of famine, where no more food would be available until after winter, the strict central management of resources is critical. At the confluence of two rivers, a trading post represents a place where you can grow the pool of a critical resource, at the expense of a less important one.

Perhaps, over time, evolution thought it valuable to fixate genes that bias people towards both mindsets, with the optimal one for any given situation ultimately dominating the memetic landscape.

Perhaps we all agree on what our goals should be. Perhaps we all are good at judging when we’ve succeeded or failed. But perhaps we’re all afflicted with genetic blindspots, and coming together to solve society’s problems involves overcoming the bug-ridden software that evolution has armed us with. Capitalism, communism, the flavour of the system doesn’t matter. What matters is that the incentives are aligned to best achieve the goals we all agree we should reach.

This is my favorite joke of all time.

Transcript of a US naval ship with Canadian authorities off the coast of Newfoundland:

Americans: “Please divert your course 15 degrees to the North to avoid a collision.”

Canadians: “Recommend you divert YOUR course 15 degrees to the South to avoid a collision.”

Americans: “This is the captain of a US Navy ship. I say again, divert YOUR course.”

Canadians: “No, I say again, you divert YOUR course.”

Americans: “THIS IS THE AIRCRAFT CARRIER USS ABRAHAM LINCOLN, THE SECOND LARGEST SHIP IN THE UNITED STATES’ ATLANTIC FLEET. WE ARE ACCOMPANIED BY THREE DESTROYERS, THREE CRUISERS AND NUMEROUS SUPPORT VESSELS. I DEMAND THAT YOU CHANGE YOUR COURSE 15 DEGREES NORTH, THAT’S ONE-FIVE DEGREES NORTH, OR COUNTER MEASURES WILL BE UNDERTAKEN TO ENSURE THE SAFETY OF THIS SHIP.”

Canadians: “This is a lighthouse. Your call.”

This never really happened. Both Snopes and the US Navy have pages debunking it. But the joke is funny because it’s easy to conceive of a possible world in which it were true — everyone’s either met someone who’s tried to move an immovable object, or been that person themselves. Usually the immovable object doesn’t tell you “We’re a lighthouse, your call” quite so bluntly, which is why it’s a punchline. But it’s a form of ha ha only serious humor — true of a concept, whether or not the event actually took place.

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The other day my friend came to me for advice. She’s going to start a PhD, but she’s worried she can’t handle it. Thing is, her concern is something I hear only too often, from too many people.

“I just don’t think I’m cut out to be a scientist. You hear all these stories of all these people who are passionate, driven. Who want more than anything to learn, to understand. But me? Sure, I like what I do, but it’s not all I want to do. I’m just not that passionate. I’m interested in too many things. I don’t think I can do this all day, every day, my whole life.”

You hear this all the time. “Do what you love.” “Follow your passions.” This advice sounds great, but is it really?

The activist giving their all at a non-profit, living in poverty. The soldier who wants to serve their country, sacrificing their youth and health for their squad. The college grad at a startup, burning out to build the next Facebook. The artist, slaving away in obscurity. All of these people are following their passion, doing what they love, but are they happy? Most of them are nowhere near. They’re just burning themselves out, while others take advantage of their naivete.

I told my friend: “do what you love” is terrible advice. If you do what you love, you’ll stop loving it some day, and on that day, you’ll have nothing to go on. A better idea is to do something you can tolerate. Something you like. And then, make it lovely.

As much as we like to believe in grand narratives, they aren’t what make us happy. The things that make us happy are smaller, more mundane. Happiness is good quality of life. You want a job that makes you happy? Find something you can tolerate. Then make it great. Live close to work, enjoy a walking commute. Work with happy, friendly people who you enjoy seeing every day. Optimize the little things. At the end of it all, a lifetime of contentment is worth more than constant striving towards an unrealistic passion.

“Neoreaction” has been much discussed recently, but what is it?

Neoreaction defines itself more in in terms of what it is opposed to than in terms of what it is in favor of.

Fine. So what is neoreaction against?

Democracy.

Neoreaction is the political philosophy that says that democracy is not merely the well-meaning god that happened to fail, but that our current wreckage was predetermined, because democracy fatally intertwined with progressivism since its birth, that it is a tool of progressivism, and that therefore, for a society to accept democracy is for a society to accept its inevitable doom at the hands of progressivism.

What is democracy?

To modern American ears, the phrase “democracy sucks” is an insane statement. To be against democracy is to be against motherhood, apple pie, puppies, and breathing oxygen.

The fact that our reaction (heh) to hearing democracy spoken ill of is visceral, deep, and immediate, is, I suggest, cause to examine that reaction. We humans only react viscerally to things that are coded into our DNA (dangerous heights, smells of rotting — and therefore disease-causing — meat, and so forth) and to triggers that are beaten into us by culture (the idea of stepping into traffic, the bad dream of showing up at the office without pants, etc.).

We in the West have been told that Democracy is wonderful. But what is this democracy that we love?

It’s a little tricky to answer, because “democracy” is a motte-and-bailey term. The motte (the core defensible meaning of the term) is that democracy is a system of selecting leaders by casting ballots.

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Polus. And is that not a great power?
Socrates. Polus has already said the reverse.

If you’ve ever taken a course that touched on the Platonic dialogues — intro philosophy, intro classics, even some rhetoric courses still — you’ve probably heard them described as a genre. (If you haven’t, well, now you’ve heard them described that way.)

Bust of Socrates. By Sphinx, CC-BY-SA 2.5.

A genre is in fact exactly what they are: a way of telling a story. Folks with swords and magic overcome monsters and armies? That’s a fantasy story. A clever rogue hoodwinks everyone and gets away scot-free? That’s a caper story. Some jerk shows up all the other thinkers (or folks who think they’re thinkers) just by asking a bunch of questions? That’s a Platonic dialogue, and the jerk’s name is usually Socrates.

Dialogues, as their prefix implies, consist of two roles, two “sides” to a stream of logos, of words. (We see the same pattern in discourse and dialectic.) (Edit: I’m wrong! dia here means through, not two. Thanks, LapsedPacifist.) In the Platonic dialogues, usually there are several speakers, but just two roles: Socrates and Socrates’ foils. Socrates’ role is to ask questions, draw his foils out, highlight the inconsistencies in their thinking and lead them to verbalize the answers to the questions they needed his help to ask. Socrates is the Smart Guy, and the foils are the Dumb Guys. (It’s classical Greek philosophy. They’re all guys.)

The Socratic method can be a great mode of intellectual exploration when people avoid using it as a weapon. Unfortunately, our role models here are not that great, because Socrates was in fact kind of a jerk, and ultimately he got himself executed for trolling the polis too hard. Indeed, one of the failure modes of the Socratic method is when the questioner uses their role more to show off how great they are (which Socrates did model) than to open new perspectives in the minds of those in the responder role. When this happens, it teaches people to be cautious of open-ended questions, to wonder where the trap is; in groups, no one wants to be the first to open their mouth and say something stupid. If you answer, you’re automatically a Dumb Guy.

It’s worth looking more closely at the Dumb Guys, though, because they aren’t homogeneous. Broadly, they fall into two classes: hubristic dumb guys and epistemically humble dumb guys. Hubristic dumb guys think they know all the answers, and by definition don’t, because nobody does. Epistemically humble dumb guys know they don’t know most of the answers, and don’t mind, apart from the whole not-knowing part, and would like to know more.

You’d think that for your self-image it would be better to be Socrates, but I honestly kinda like being the second kind of dumb guy.

If nothing else, it gets the conversation moving. I see it as giving other people the chance to be the smart guy, or at least smarter than that fuckup — sometimes that’s the kick in the ass people need to break the bystander effect and express their opinion. They’re not sure whether their take on a situation is any smarter than Socrates’, and Socrates is being all cagey keeping his cards to his chest, but at least they look smart compared to that rube.

Applying this strategy to social media has been interesting. Nothing on Twitter brings out the randos who don’t read replies faster than an open-ended question. “What if?” questions, in particular, get a lot of what I’ve come to think of as “short-circuit” responses: point out the most obvious obstacle to the question as constructed and move on. Usually the obstacle in question is one I’ve already thought of and decided to ask anyway, so this doesn’t bother me apart from wishing there were a way to signpost that within the 140-character limit. (Maybe 10k characters will fix this problem, if Twitter lives that long.) The distribution of responses has given me a lot to think about with regard to the distribution of problem-solving strategies; “X is unlikely/really hard/&c” is something I hear a lot in what-iffing, and while I don’t particularly find it discouraging (it’s a really useful attitude to have when you’re on the clock), I can understand how other people might.

However, the distribution has other points on it, like randos who reframe dumb questions in less-dumb ways. Here’s one recent example:

Which, reductio, makes the interesting point that Apple has (even if it probably won’t exercise) the option to defect in an extremely high-stakes Prisoner’s Dilemma — and maybe even get away with it. Software being what it is, and considering that they have exactly one shot to get any firmware replacement they’re ordered to write correct, it’s also a trembling-hand Prisoner’s Dilemma. So, a dumb question and a less-dumb follow-on question lead to a useful lens for considering the structure of the Apple-vs-DoJ problem — and, perhaps, for finding less nuclear solutions by exploring the tree of that signaling game. Score one for good-faith inquiry.

Not, mind, that I think short-circuit responders are responding in bad faith. I think they’re not interested in that avenue of inquiry, which is entirely their right — it’s their attention to expend. I will, however, continue asking dumb questions, in every situation looking for the point of view that gives me +80 IQ points. If I have to lower myself a bit to do it, I don’t mind; you find all kinds of useful things when you look under stuff.

The internet has been abuzz over the last few days about a preprint in PeerJ Preprints, “Gender bias in open source: Pull request acceptance of women vs. men.” Scott Alexander delivers a summary of popular-media responses to this, among other good discussion, none of which I’ll recapitulate here. I’m more interested in opening a window on how the peer review process works — one that you don’t really get from viral reporting on science. This is something I can shed at least a little light on, because coincidentally, two years ago I coauthored a paper, “More ties than we thought,” that went viral not once but twice — first the preprint on arXiv, then the peer-reviewed version in, also coincidentally, PeerJ.

Just to make things even more interesting, in the preprint version, our result was wrong.

Briefly, we revisited Thomas Fink and Yong Mao’s The 85 Ways to Tie a Tie in light of YouTube sartorialist Alex Krasny’s reverse-engineering of the “Eldredge” knot that the Merovingian wears in the movie The Matrix Reloaded. Fink and Mao use a formal grammar to describe their 85 possible tie knots, but they included an extra, implicit constraint — all their knots start from the wide end of the tie. We relaxed this constraint and came up with a formal grammar for the process of tying a tie knot from either end of the tie, which includes the Eldredge, the Trinity, and other modern knots. It also turns out to include thousands and thousands of really derpy-looking knots. This in itself is interesting, because that suggests that there’s more math to explore about what makes a knot look nifty — and about processes in general. Many processes produce results, but not all steps to an end produce an end you want, even for completely deterministic processes. The “generating functions” parts of our work are about exploring that process space and its outcomes, which has all kinds of interesting implications for machining, robotics, textiles (we’ve got some work in progress on braiding and knitting), and other areas of materials science. (Though mostly it is because Mikael Vejdemo-Johansson noticed there was something we didn’t have a mathematical understanding of, and now we have corrected that oversight.)

And in the preprint, we had a boneheaded off-by-one error.

68 venues reported on the preprint, not counting NPR affiliates separately. Nobody caught the error. Frankly, most of the preprint coverage was of the “Ha ha, look at the goofy things that university boffins get paid to study” variety, which means they either didn’t read closely enough to notice that two of the authors have no university affiliation or didn’t think it worth pointing out. Yes, our motivation was trivial, indeed silly, but that jives with a paper where half the authors worked on it in their Copious Free Time. It was “slow news day” coverage, but hey, there’s no such thing as bad publicity, right?

Anyway, we pushed on, because clearly we’d struck some kind of nerve and we figured it was worth publishing “for real” in academic terms, so we started shopping it around. Or, to be more specific, Mikael started shopping it around — credit where credit is due.

It got rejected a lot. After about a year of rejections, Mikael heard that PeerJ was starting up a computer science journal, we submitted it, and then one of the peer reviewers found our off-by-one error. After correcting this, we found that we had about ten times fewer ties than we’d claimed in the preprint, and we corrected our in-progress draft. There was some additional back-and-forth, in large part because we lucked into one of the intellectual powerhouses of generating functions as a reviewer and got feedback that helped us improve our analysis significantly. As an author I was really pleased with PeerJ’s reviewing process; it’s far closer to the “shepherding” process that some academic workshops use with accepted papers that could still use some work than the “three anonymous reviews and not much of a feedback loop” process that is typical of top-tier conferences. The final revision was accepted for the first issue of PeerJ CS last May, and the paper went viral again.

56 venues covered the peer-reviewed paper. There is exactly one element in common between the sets of venues that covered it online before and after peer review: the KTH press office. The Swedish newspaper Dagens Nyheter (“Daily News”) was the only paper to report both figures: the preprint version in the light-entertainment-and-silliness section, the updated figure in a print-only Father’s Day factoid bubble. Other than that, exactly zero of the outlets that reported the incorrect figure also reported on the peer-reviewed paper or the correction. I can understand their reasoning, because for most of these venues, the paper is a curiosity, and a curiosity about a curiosity doesn’t really rise to the level of reporting in their view.

The thing is, though, nobody makes serious decisions that affect other people based on what they know about tie knots. People do make serious decisions that affect other people based on what they know about gender bias — or, more importantly, what they think they know. How Vice, CNN, and other venues that are reporting on this preprint as if it’s already scientific consensus report will affect some of those decisions, and after looking at the data on my own experience of viral science reporting, “are they going to follow up when the paper is actually complete?” is a question readers deserve an answer to from reporters who are treating this paper like a genie that’s been let out of its bottle.

Because that’s the thing: a preprint is a completed draft, but it is not a completed journal article until it passes peer review. A preprint is for eliciting early feedback from a peer community, like getting beta readers for your fanfic. arXiv, where we published our preprint, has been the physics and mathematics communities’ preprint archive of choice for years, and in recent years computer scientists have started using it too; PeerJ is now providing this service for the domains in which it publishes. The media are not drawing this distinction.

The gender bias article isn’t a completed journal article until Emerson Murphy-Hill and the rest of his team finish discussing the preprint with those PeerJ reviewers who decide to provide feedback, do whatever editing, additional data gathering/processing, and re-analysis they need to do in light of that feedback, resubmit the paper for peer review (to PeerJ, or to some other venue — remember, they’re using PeerJ’s preprint service, which is basically the equivalent of arXiv except operated by PeerJ, but this doesn’t necessarily mean they even intend to submit it to PeerJ, or that PeerJ will give it any special consideration if they do), handle any feedback from peer reviewers, and submit a camera-ready version that the editors sign off on. Then it’s a matter of waiting until the issue their paper will be in comes out. This process takes a couple of months, minimum, which is forever in Internet time, so it’s likely that we’ll see another round of viral coverage when the peer-reviewed paper eventually comes out. How will that coverage compare with the preprint coverage?

To be clear: From what I’ve seen on PeerJ Preprints, I think that Murphy-Hill and colleagues are engaging with their scientific peers in the spirit of genuine inquiry and communication. One of those peers happens to be none other than Mikael Vejdemo-Johansson, who is a stickler for both rigor and good presentation. The peer review process is behaving like it is supposed to. I believe that a useful paper will come out of this process. Unfortunately, the popular press does not have a particularly good understanding of the peer review process, and is treating the data gathering and preliminary hypothesis testing that are the early steps of science as if they were already-established science. I am at a loss as to how to solve this problem in reporting.