I’m pretty quiet on here currently. That’s because I have a different experiment going on instead: spamming out lots of short posts in one sitting on a notebook blog, Notebucket. I just realised I never linked to it from here, so… now I have.
The quality level is often low and it’s really not worth wading through all of those. But I’m pleased with some of them. Here are some of the more coherent and interesting ones:
Other than that, there’s a whole load of fragmented notes about some cluster of thoughts to do with Husserl, Derrida, mathematical notation as a technology… not sure exactly where I’m going with it, but I want to start combining it into more coherent blog posts soon, and posting them here again.
(Edit: AARGH!!! The WordPress editor gets more broken every time I try it, today it’s not even letting me preview my own post. I’m considering moving to Ghost eventually, which is where I host the notebook, but I need to sort out the commenting situation first. This is getting ridiculous though.)
I’ve recently been reading Drawing Theories Apart: The Dispersion of Feynman Diagrams in Postwar Physics, by David Kaiser. Feynman diagrams combine my longstanding interest in physics with my current weird-interest-of-the-moment, text as a technology (this was also the background inspiration for my recent visual programming post). They aren’t exactly text, but they’re a formalised, repeatable type of diagram that follow a certain set of rules, so they’re definitely text-adjacent. I ended up getting more interested in the details of the physics than in the text-as-technology angle, so that’s going to be the main focus of this somewhat rambling review, but a few other topics will come up too.
Feynman diagrams turn out to be an interesting lens for looking at the history of physics. One obvious way to think of physics is as a set of theories, like ‘thermodynamics’, ‘electromagnetism’, ‘quantum mechanics’, and so on, each with a sort of axiomatic core that various consequences can be developed from. This fits certain parts of physics rather well – special relativity is a particularly good fit, for instance, with its neat conceptual core of a few simple postulates.
At the other end of the scale is something like fluid dynamics. In theory I suppose most people in fluid dynamics are looking at the consequences of one theory, the Navier-Stokes equations, but that’s a horribly complicated set of nonlinear equations that nobody can solve in general. So in reality fluid dynamics is splintered into a bunch of subdisciplines studying various regimes where different approximations can be made – I’m not an expert here but stuff like supersonic flow, boundary layers, high viscosity – and each one has its bag of techniques and set of canonical examples. Knowing about Navier-Stokes is pretty useless on its own, you’re also going to need the bag of techniques for your subfield to make any progress. So a history of fluid dynamics needs to largely be a history of these techniques.
Quantum field theory, where Feynman diagrams were first developed, is also heavy on bags of techniques. These are harder than postulates to transmit clearly through a textbook, you really have to see a lot of examples and work exercises and so on, so tacit knowledge transmitted by experts is especially important. Kaiser makes this point early on (my bolds):
Once we shift from a view of theoretical work as selecting between preformed theories, however, to theoretical work as the crafting and use of paper tools, tacit knowledge and craft skill need not seem so foreign. Thomas Kuhn raised a similar problem with his discussion of “exemplars”. Kuhn wrote that science students must work to master exemplars, or model problems, before they can tackle research problems on their own. The rules for solving such model problems and generalizing their application are almost never adequately conveyed via appeals to overarching general principles and rarely appear in sufficient form within published textbooks.
This focus on ‘paper tools’ is in the tradition of Bruno Latour’s work on ‘inscriptions’, and in fact the title of Kaiser’s book comes from Latour’s paper, Visualisation and Cognition: Drawing Things Together [pdf]. Latour talks about the way that complicated laboratory procedures need to be condensed down into marks on paper in order to communicate with other scientists:
Like these scholars, I was struck, in a study of a biology laboratory, by the way in which many aspects of laboratory practice could be ordered by looking not at the scientists’ brains (I was forbidden access!), at the cognitive structures (nothing special), nor at the paradigms (the same for thirty years), but at the transformation of rats and chemicals into paper… Instruments, for instance, were of various types, ages, and degrees of sophistication. Some were pieces of furniture, others filled large rooms, employed many technicians and took many weeks to run. But their end result, no matter the field, was always a small window through which one could read a very few signs from a rather poor repertoire (diagrams, blots, bands, columns). All these inscriptions, as I called them, were combinable, superimposable and could, with only a minimum of cleaning up, be integrated as figures in the text of the articles people were writing. Many of the intellectual feats I was asked to admire could be rephrased as soon as this activity of paper writing and inscription became the focus for analysis.
These inscriptions are transportable and recombinable by scientists in different locations (‘immutable mobiles’):
If you wish to go out of your way and come back heavily equipped so as to force others to go out of *their* ways, the main problem to solve is that of *mobilization*. You have to go and to come back *with* the “things” if your moves are not to be wasted. But the “things” have to be able to withstand the return trip without withering away. Further requirements: the “things” you gathered and displaced have to be presentable all at once to those you want to convince and who did not go there. In sum, you have to invent objects which have the properties of being *mobile* but also *immutable*, *presentable*, *readable* and *combinable* with one another.
Kaiser’s focus is instead on the ways that diagrams elude this easy transmissibility, and the background of tacit knowledge that they rely on: ‘drawing theories apart’ rather than ‘drawing things together’. Here’s a representative anecdote:
… in the summer of 1949, Enrico Fermi had complained that he was unable to make sense of one of Bethe’s own recent papers, and hence could not reproduce and extend Bethe’s calculations. Fermi and Bethe were both experts in the field in question, and they had worked closely together throughout the war years; they knew the territory and they knew each other quite well.
Also, of course, they were Fermi and Bethe! If they can’t do it, there isn’t much hope for the rest of us.
What Feynman diagrams are…
Before I go any further, it might be useful to give a rough indication of what Feynman diagrams are, and what it’s like to calculate with them. (Disclaimer before I attempt to do this: I only have a basic knowledge of this myself!) The idea is that they’re a notational device used to translate big ugly equations into something easier to manipulate. Unlike most popular science explanations, I’m going to risk putting some of these big ugly equations on the screen, but the details of them are not important. I just want to give an idea of how they’re translated into diagrams.
The examples I’m using come from some excellent notes on Solving Classical Field Equations, by Robert Helling. These notes make the point that Feynman diagrams can be used in many contexts, including in classical physics – they’re not a quantum-only thing. It makes more sense to think of them as applying to a particular kind of mathematical method, rather than to a type of physical theory as such. This method is a specific kind of perturbation theory, a general class of techniques where you make a rough (‘zeroth-order’) approximation to a calculation and then add on successive (‘first-order’, ‘second-order’, ‘third-order’…) correction terms. If all goes well, each correction term is smaller enough than the last that the whole thing converges, and you get a better and better approximation the more terms you include.
Now let’s see how the correction terms map to diagrams. Here’s the first order correction for Helling’s example, in standard equation form:
And here’s the corresponding diagram:
I’m not going to go into the details of the exact rules for translating from equation to diagram, but hopefully you can see some correspondences – the cubed term translates into three branches, for example. The full rules are in Helling’s paper.
At this point there isn’t a big difference between the equation and the diagram in terms of total effort to write down. But in perturbation theory, the higher the order you go to, the more hairy looking the correction terms get – they’re built up in a kind of recursive way from pieces of the lower-level correction terms, and this gets fiddly quickly. For example, here’s the third order correction term:
Ugh. At this point, you can probably see why you want to avoid having to write this thing down. In diagram form this term becomes:
This is a lot less mistake-prone than writing down the big pile of integrals, and the rules tell you exactly what diagrams need to be included, what number to put in front of each one, etc. This is a big improvement. And that becomes even more important in quantum electrodynamics, where the calculations are much more complicated than these example ones.
… sort of
Well, that’s one view of what Feynman diagrams are, at least. As the subtitle indicates, this book is about the dispersion of Feynman diagrams through physics. A large part of this is about geographical dispersion, as physicists taught the new techniques to colleagues around the world, and another part is about the dispersion of the methods through different fields, but the most interesting parts for me were about the dispersion of the meaning of diagrams.
These differences in meaning were there from the start. In the section above I described Feynman diagrams as a notational device for making a certain kind of calculation easier. This mirrors the view of Freeman Dyson, who was the first person to understand Feynman’s diagrammatic method and show its equivalence to the existing mathematical version. Dyson was apparently always very careful to start with the standard mathematics, and then show how the diagrams could replicate this.
None of this fits with how Feynman himself viewed the diagrams. For Feynman, the diagrams were a continuation of an idiosyncratic path he’d been pursuing for some time already, where he tried to remove fields from his models of physics and replace them with direct particle interactions. He saw the diagrams themselves as describing actual particle interactions occurring in spacetime, and considered them to take precedence over the mathematical description:
… Feynman believed fervently that the diagrams were more primary and more important than any derivation that they might be given. In fact, Feynman continued to avoid the question of derivation in his articles, lecture courses and correspondence… Nowhere in Feynman’s 1949 article on the diagrams, for example, were the diagrams’ specific features or their strict one-to-one correlations with specific mathematical expressions derived or justified from first principles. Instead, Feynman avowed unapologetically that “Since the result was easier to understand than the derivation, it was thought best to publish the results first in this paper.”
This split persisted as methods were taught more widely and eventually condensed into textbooks. Some physicists stuck with the mathematical-formalism-first approach, while others took Feynman’s view to an extreme:
James Bjorken and Sidney Drell began their twin textbooks on relativistic quantum mechanics and quantum field theory from 1964 and 1965 with the strong statement that “one may go so far as to adopt the extreme view that the full set of all Feynman graphs is the theory.” Though they quickly backed off this stance, they firmly stated their “conviction” that the diagrams and rules for calculating directly from them “may well outlive the elaborate mathematical structure” of canonical quantum field theory, which, they further opined, might “in time come to be viewed more as a superstructure than as a foundation.”
I’d never thought about this before, but this line of argument makes a fair bit of sense to me. This was a new field and the mathematical formalism was not actually very much older than Feynman’s diagrams. So everything was still in flux, and if the diagrams looked simpler than the formalism then maybe that looked like an indication to start there instead? I’d be interested now to learn a bit more of the history.
A third motivation also appeared at this point. The immediate postwar years were a time of enormous expansion in physics funding, especially in the US, and huge numbers of new students were entering the field. These students mostly needed to calculate practical things quickly, and conceptual niceties were not important. Feynman diagrams were relatively straightforward to learn compared to the underlying formalism, so a diagram-first route that got students calculating quickly became popular.
This pragmatic motivation is one reason that Kaiser’s focus on diagrams works so well, compared to a theory-first approach. Most practitioners were not even trying to teach and apply consistent theories:
… textbooks during the 1950s and 1960s routinely threw together techniques of mixed conceptual heritage, encouraging students to apply an approximation based on nonrelativistic potential scattering here, a lowest-order Feynman diagram there.
There wasn’t any need to, when the pragmatic approach was working so well. New experimental results were coming out all the time, and theorists were running to keep up, finding ways of adapting their techniques to solve new problems. There was more than enough work to keep everyone busy without needing to worry about the conceptual foundations.
There’s something kind of melancholy about reading about this period now. This was the golden age of a particular type of physics, which worked astonishingly well right up until it didn’t. Eventually the new experimental results ran dry, theory caught up, and it was no longer obvious how to proceed further with current techniques. Other fields continued to flourish – astronomy, condensed matter – but particle physics lost its distinctive cultural position at the leading edge of knowledge, and hasn’t regained it.
Still, I enjoyed the book, and I’m hoping it might end up helping me make some more sense of the physics, as well as the history. Since reading Helling’s notes on Feynman diagrams in classical physics, I’ve been curious about how they connect to the quantum versions. There’s a big difference between the classical and quantum diagrams – the quantum ones have loops and the classical ones don’t – and I’d like to understand why this happens at a deeper level, but it’s kind of hard to compare them properly when the formalisms used are so different. Knowing more about the historical development of the theory has given me some clues for where to to start from. I’m looking forward to exploring this more.
Everybody hates neoliberalism, it’s the law. But what is it?
This is probably the topic I’m most ignorant about and ill-prepared-for on the whole list, and I wasn’t going to do it. But it’s good prep for the bullshit jobs post, which was a popular choice, so I’m going to try. I’m going to be trying to articulate my current thoughts, rather than attempting to say anything original. And also I’m not really talking about neoliberalism as a coherent ideology or movement. (I think I’d have to do another speedrun just to have a chance of saying something sensible.) More like “neoliberalism”, scarequoted, as a sort of diffuse cloud of associations that the term brings to mind. Here’s my cloud (very UK-centric):
Big amorphous companies with bland generic names like Serco or Interserve, providing an incoherent mix of services to the public sector, with no obvious specialism beyond winning government contracts
Public private partnerships
Metrics! Lots of metrics!
Incuriosity about specifics. E.g. management by pushing to make a number go up, rather than any deep engagement with the particulars of the specific problem
Food got really good over this period. I think this actually might be relevant and not just something that happened at the same time
Low cost short-haul airlines becoming a big thing (in Europe anyway – don’t really understand how widespread this is)
Thinking you’re on a public right of way but actually it’s a private street owned by some shopping centre or w/e. With private security and lots of CCTV
Post-industrial harbourside developments with old warehouses converted into a Giraffe and a Slug and Lettuce
A caricatured version of Tony Blair’s disembodied head is floating over the top of this whole scene like a barrage balloon. I don’t think this is important but I thought you’d like to know
I’ve had this topic vaguely in mind since I read a blog post by Timothy Burke, a professor of modern history, a while back. The post itself has a standard offhand ‘boo neoliberalism’ side remark, but then when challenged in the comments he backs it up with an excellent, insightful sketch of what he means. (Maybe this post should just have been a copy of this comment, instead of my ramblings.)
I’m sensitive to the complaint that “neoliberalism” is a buzz word that can mean almost everything (usually something the speaker disapproves of).
A full fleshing out is more than I can provide, though. But here’s some sketches of what I have in mind:
1) The Reagan-Thatcher assault on “government” and aligned conceptions of “the public”–these were not merely attempts to produce new efficiencies in government, but a broad, sustained philosophical rejection of the idea that government can be a major way to align values and outcomes, to tackle social problems, to restrain or dampen the power of the market to damage existing communities. “The public” is not the same, but it was an additional target: the notion that citizens have shared or collective responsibilities, that there are resources and domains which should not be owned privately but instead open to and shared by all, etc. That’s led to a conception of citizenship or social identity that is entirely individualized, privatized, self-centered, self-affirming, and which accepts no responsibility to shared truths, facts, or mechanisms of dispute and deliberation.
2) The idea of comprehensively measuring, assessing, quantifying performance in numerous domains; insisting that values which cannot be measured or quantified are of no worth or usefulness; and constantly demanding incremental improvements from all individuals and organizations within these created metrics. This really began to take off in the 1990s and is now widespread through numerous private and public institutions.
3) The simultaneous stripping bare of ordinary people to numerous systems of surveillance, measurement, disclosure, monitoring, maintenance (by both the state and private entities) while building more and more barriers to transparency protecting the powerful and their most important private and public activities. I think especially notable since the late 1990s and the rise of digital culture. A loss of workplace and civil protections for most people (especially through de-unionization) at the same time that the powerful have become increasingly untouchable and unaccountable for a variety of reasons.
4) Nearly unrestrained global mobility for capital coupled with strong restrictions on labor (both in terms of mobility and in terms of protection). Dramatically increased income inequality. Massive “shadow economies” involving illegal or unsanctioned but nevertheless highly structured movements of money, people, and commodities. Really became visible by the early 1990s.
A lot of the features in my association cloud match pretty well: metrics, surveillance, privatisation. Didn’t really pick up much from point 4. I think 2 is the one which interests me most. My read on the metric stuff is that there’s a genuinely useful tool here that really does work within its domain of application but is disastrous when applied widely to everything. The tool goes something like:
let go of a need for top-down control
fragment the system into lots of little bits, connected over an interface of numbers (money, performance metrics, whatever)
try to improve the system by hammering on the little bits in ways such that the numbers go in the direction you want. This could be through market forces, or through metrics-driven performance improvements.
If your problem is amenable to this kind of breakdown, I think it actually works pretty well. This is why I think ‘food got good’ is actually relevant and not a coincidence. It fits this playbook quite nicely:
It’s a known problem. People have been selling food for a long time and have some well-tested ideas about how to cook, prep, order supplies, etc. Theres’s innovation on top of that, but it’s not some esoteric new research field.
Each individual purchase (of a meal, cake, w/e) is small and low-value. So the domain is naturally fragmented into lots of tiny bits.
This also means that lots of people can afford to be customers, increasing the number of tiny bits
Fast feedback. People know whether they like a croissant after minutes, not years.
Relevant feedback. People just tell you whether they like your croissants, which is the thing you care about. You don’t need to go search for some convoluted proxy measure of whether they like your croissants.
Lowish barriers to entry. Not especially capital-intensive to start a cafe or market stall compared with most businesses.
Lowish regulations. There’s rules for food safety, but it’s not like building planes or someting.
No lock-in for customers. You can go to the donburi stall today and the pie and mash stall tomorrow.
All of this means that the interface layer of numbers can be an actual market, rather than some faked-up internal market of metrics to optimise. And it’s a pretty open market that most people can access in some form. People don’t go out and buy trains, but they do go out and buy sandwiches.
There’s another very important, less wonky factor that breaks you out of the dry break-it-into-numbers method I listed above. You ‘get to cheat’ by bringing in emotional energy that ‘comes along for free’. People actually like food! They start cafes because they want to, even when it’s a terrible business idea. They already intrinsically give a shit about the problem, and markets are a thin interface layer over the top rather than most of the thing. This isn’t going to carry over to, say, airport security or detergent manufacturing.
As you get further away from an idealised row of spherical burger vans things get more complicated and ambiguous. Low cost airlines are a good example. These actually did a good job of fragmenting the domain into lots of bits that were lumped together by the older incumbents. And it’s worked pretty well, by bringing down prices to the point where far more people can afford to travel. (Of course there’s also the climate change considerations. If you ignore those it seems like a very obvious Good Thing, once you include them it’s somewhat murkier I suppose.)
The price you pay is that the experience gets subtly degraded at many points by the optimisation, and in aggregate these tend to produce a very unsubtle crappiness. For a start there’s the simple overhead of buying the fragmented bits separately. You have to click through many screens of a clunky web application and decide individually about whether you want food, whether you want to choose your own seat, whether you want priority queuing, etc. All the things you’d just have got as default on the old, expensive package deal. You also have to say no to the annoying ads trying to upsell you on various deals on hotels, car rentals and travel insurance.
Then there are the all the ways the flight itself becomes crappier. It’s at a crap airport a long way from the city you want to get to, with crappy transport links. The flight is a cheap slot at some crappy time of the early morning. The plane is old and crappily fitted out. You’re having a crappy time lugging around the absolute maximum amount of hand luggage possible to avoid the extra hold luggage fee. (You’ve got pretty good at optimising numbers yourself.)
This is often still worth it, but can easily tip into just being plain Too Crappy. I’ve definitely over-optimised flight booking for cheapness and regretted it (normally when my alarm goes off at three in the morning).
Low cost airlines seem basically like a good idea, on balance. But then there are the true disasters, the domains that have none of the natural features that the neoliberal playbook works on. A good example is early-stage, exploratory academic research. I’ve spent too long on this post already. You can fill in the depressing details yourself.
I’ve got some half-written drafts for topics on the original list which I want to finish soon, but for now I seem to be doing better by going off-list and rambling about whatever’s in my head. Today it’s visual imagery.
I’ve ended up reading a bunch of things vaguely connected with mnemonics in the last couple of weeks. I’m currently very bad at concentrating on books properly, but I’m still reading at a similar rate, so everything is in this weird quarter-read state. Anyway here’s the list of things I’ve started:
Moonwalking with Einstein by Joshua Foer. Pop book about learning to compete in memory championships. This is good and an easy read, so there is some chance I’ll actually finish it.
Orality and Literacy by Walter Ong. One of the references I followed up. About oral cultures in general but there is stuff on memorisation (e.g. repetitive passages in Homer being designed for easy memorisation when writing it down is not an option)
Thesetwo interesting posts by AllAmericanBreakfast on Less Wrong this week about experimenting with memory palaces to learn information for a chemistry exam.
Those last two posts are interesting to me because they’re written by someone in the very early stages of fiddling around with this stuff who doesn’t consider themself to naturally have a good visual imagination. I’d put myself in the same category, but probably worse. Actually I’m really confused about what ‘visual imagery’ even is. I have some sort of – stuff? – that has a sort of visual component, maybe mixed in with some spatial/proprioceptive/tactile stuff. Is that what people mean by ‘visual imagery’? I guess so? It’s very transitory and hard to pin down in my case, though, and I don’t feel like I make a lot of use out of it. The idea of using these crappy materials to make something elaborate like a memory palace sounds like a lot of work. But maybe it would work better if I spent more time on it.
The thing that jumped out of the first post for me was this bit:
I close my eyes and allow myself to picture nothing, or whatever random nonsense comes to mind. No attempt to control.
Then I invite the concept of a room into mind. I don’t picture it clearly. There’s a vague sense, though, of imagining a space of some kind. I can vaguely see fleeting shadowy walls. I don’t need to get everything crystal clear, though.
This sounded a lot more fun and approachable to me than crafting a specific memory palace to memorise specific things. I didn’t even get to the point of ‘inviting the concept of a room in’, just allowed any old stuff to come up, and that worked ok for me. I’m not sure how much of this ‘imagery’ was particularly visual, but I did find lots of detailed things floating into my head. It seems to work better if I keep a light touch and only allow some very gentle curiosity-based steering of the scene.
Here’s the one I found really surprising and cool. I was imagining an intricately carved little jade tortoise for some reason, and put some mild curiosity into what its eyes were made of. And I discovered that they were tiny yellow plastic fake gemstones that were weirdly familiar. So I asked where I recognised them from (this was quite heavy-handed questioning that dragged me out of the imagery). And it turns out that they were from a broken fish brooch I had as a kid. I prised all the fake stones off with a knife at some point to use for some project I don’t remember.
I haven’t thought about that brooch in, what, 20 years? But I remember an impressive amount of detail about it! I’ve tried to draw it above. Some details like the fins are a best guess, but the blue, green and yellow stones in diagonal stripes are definitely right. It’s interesting that this memory is still sitting there and can be brought up by the right prompt.
I think I’ll play with this exercise a bit more and see what other rubbish I can dredge up.
I was inspired by John Nerst’s recent post to make a list of my own fundamental background assumptions. What I ended up producing was a bit of a odd mixed bag of disparate stuff. Some are something like factual beliefs, some of them are more like underlying emotional attitudes and dispositions to act in various ways.
I’m not trying to ‘hit bedrock’ in any sense, I realise that’s not a sensible goal. I’m just trying to fish out a few things that are fundamental enough to cause obvious differences in background with other people. John Nerst put it well on Twitter:
It’s not true that beliefs are derived from fundamental axioms, but nor is it true that they’re a bean bag where nothing is downstream from everything else.
I’ve mainly gone for assumptions where I tend to differ with the people I to hang around with online and in person, which skews heavily towards the physics/maths/programming crowd. This means there’s a pretty strong ‘narcissism of small differences’ effect going on here, and if I actually had to spend a lot of time with normal people I’d probably run screaming back to to STEM nerd land pretty fast and stop caring about these minor nitpicks.
Also I only came up with twenty, not thirty, because I am lazy.
I’m really resistant to having to ‘actually think about things’, in the sense of applying any sort of mental effort that feels temporarily unpleasant. The more I introspect as I go about problem solving, the more I notice this. For example, I was mucking around in Inkscape recently and wanted to check that a square was 16 units long, and I caught myself producing the following image:
Apparently counting to 16 was an unacceptable level of cognitive strain, so to avoid it I made the two 4 by 4 squares (small enough to immediately see their size) and then arranged them in a pattern that made the length of the big square obvious. This was slower but didn’t feel like work at any point. No thinking required!
This must have a whole bunch of downstream effects, but an obvious one is a weakness for ‘intuitive’, flash-of-insight-based demonstrations, mixed with a corresponding laziness about actually doing the work to get them. (Slowly improving this.)
I picked up some Bad Ideas From Dead Germans at an impressionable age (mostly from Kant). I think this was mostly a good thing, as it saved me from some Bad Ideas From Dead Positivists that physics people often succumb to.
I didn’t read much phenomenology as such, but there’s some mood in the spirit of this Whitehead quote that always came naturally to me:
For natural philosophy everything perceived is in nature. We may not pick and choose. For us the red glow of the sunset should be as much part of nature as are the molecules and electric waves by which men of science would explain the phenomenon.
By this I mean some kind of vague understanding that we need to think about perceptual questions as well as ‘physics stuff’. Lots of hours as an undergrad on Wikipedia spent reading about human colour perception and lifeworlds and mantis shrimp eyes and so on.
One weird place where this came out: in my first year of university maths I had those intro analysis classes where you prove a lot of boring facts about open sets and closed sets. I just got frustrated, because it seemed to be taught in the same ‘here are some facts about the world’ style that, say, classical mechanics was taught in, but I never managed to convince myself that the difference related to something ‘out in the world’ rather than some deficiency of our cognitive apparatus. ‘I’m sure this would make a good course in the psychology department, but why do I have to learn it?’
This isn’t just Bad Ideas From Dead Germans, because I had it before I read Kant.
Same thing for the interminable arguments in physics about whether reality is ‘really’ continuous or discrete at a fundamental level. I still don’t see the value in putting that distinction out in the physical world – surely that’s some sort of weird cognitive bug, right?
I think after hashingthisout for a while people have settled on ‘decoupling’ vs ‘contextualising’ as the two labels. Anyway it’s probably apparent that I have more time for the contextualising side than a lot of STEM people.
Outside of dead Germans, my biggest unusual pervasive influence is probably the New Critics: Eliot, Empson and I.A. Richards especially, and a bit of Leavis. They occupy an area of intellectual territory that mostly seems to be empty now (that or I don’t know where to find it). They’re strong contextualisers with a focus on what they would call ‘developing a refined sensibility’, by deepening sensitivity to tiny subtle nuances in expression. But at the same time, they’re operating in a pre-pomo world with a fairly stable objective ladder of ‘good’ and ‘bad’ art. (Eliot’s version of this is one of my favourite ever wrong ideas, where poetic images map to specific internal emotional states which are consistent between people, creating some sort of objective shared world.)
This leads to a lot of snottiness and narrow focus on a defined canon of ‘great authors’ and ‘minor authors’. But also the belief in reliable intersubjective understanding gives them the confidence for detailed close reading and really carefully picking apart what works and what doesn’t, and the time they’ve spent developing their ear for fine nuance gives them the ability to actually do this.
The continuation of this is probably somewhere on the other side of the ‘fake pomo blocks path’ wall in David Chapman’s diagram, but I haven’t got there yet, and I really feel like I’m missing something important.
I don’t understand what the appeal of competitive games is supposed to be. Like basically all of them – sports, video games, board games, whatever. Not sure exactly what effects this has on the rest of my thinking, but this seems to be a pretty fundamental normal-human thing that I’m missing, so it must have plenty.
I always get interested in specific examples first, and then work outwards to theory.
My most characteristic type of confusion is not understanding how the thing I’m supposed to be learning about ‘grounds out’ in any sort of experience. ‘That’s a nice chain of symbols you’ve written out there. What does it relate to in the world again?’
I have never in my life expected moral philosophy to have some formal foundation and after a lot of trying I still don’t understand why this is appealing to other people. Humans are an evolved mess and I don’t see why you’d expect a clean abstract framework to ever drop out from that.
Philosophy of mathematics is another subject where I mostly just think ‘um, you what?’ when I try to read it. In fact it has exactly the same subjective flavour to me as moral philosophy. Platonism feels bad the same way virtue ethics feels bad. Formalism feels bad the same way deontology feels bad. Logicism feels bad the same way consequentialism feels bad. (Is this just me?)
I’ve never made any sense out of the idea of an objective flow of time and have thought in terms of a ‘block universe’ picture for as long as I’ve bothered to think about it.
If I don’t much like any of the options available for a given open philosophical or scientific question, I tend to just mentally tag it with ‘none of the above, can I have something better please’. I don’t have the consistency obsession thing where you decide to bite one unappealing bullet or another from the existing options, so that at least you have an opinion.
This probably comes out of my deeper conviction that I’m missing a whole lot of important and fundamental ideas on the level of calculus and evolution, simply on account of nobody having thought of them yet. My default orientation seems to be ‘we don’t know anything about anything’ rather than ‘we’re mostly there but missing a few of the pieces’. This produces a kind of cheerful crackpot optimism, as there is so much to learn.
This list is noticeably lacking in any real opinions on politics and ethics and society and other people stuff. I just don’t have many opinions and don’t like thinking about people stuff very much. That probably doesn’t say anything good about me, but there we are.
I’m also really weak on economics and finance. I especially don’t know how to do that economist/game theoretic thing where you think in terms of what incentives people have. (Maybe this is one place where ‘I don’t understand competitive games’ comes in.)
I’m OK with vagueness. I’m happy to make a vague sloppy statement that should at least cover the target, and maybe try and sharpen it later. I prefer this to the ‘strong opinions, weakly held’ alternative where you chuck a load of precise-but-wrong statements at the target and keep missing. A lot of people will only play this second game, and dismiss the vague-sloppy-statement one as ‘just being bad at thinking’, and I get frustrated.
Not happy about this one, but over time this frustration led me to seriously go off styles of writing that put a strong emphasis on rigour and precision, especially the distinctive dialects you find in pure maths and analytic philosophy. I remember when I was 18 or so and encountered both of these for the first time I was fascinated, because I’d never seen anyone write so clearly before. Later on I got sick of the way that this style tips so easily into pedantry over contextless trivialities (from my perspective anyway). It actually has a lot of good points, though, and it would be nice to be able to appreciate it again.
I enjoyed alkjash’s recent Babble and Prune posts on Less Wrong, and it reminded me of a favourite quote of mine, Feynman’s description of science in The Character of Physical Law:
What we need is imagination, but imagination in a terrible strait-jacket. We have to find a new view of the world that has to agree with everything that is known, but disagree in its predictions somewhere, otherwise it is not interesting.
Imagination here corresponds quite well to Babbling, and the strait-jacket is the Pruning you do afterwards to see if it actually makes any sense.
For my tastes at least, early Less Wrong was generally too focussed on building out the strait-jacket to remember to put the imagination in it. An unfair stereotype would be something like this:
‘I’ve been working on being better calibrated, and I put error bars on all my time estimates to take the planning fallacy into account, and I’ve rearranged my desk more logically, and I’ve developed a really good system to keep track of all the tasks I do and rank them in terms of priority… hang on, why haven’t I had any good ideas??’
I’m poking fun here, but I really shouldn’t, because I have the opposite problem. I tend to go wrong in this sort of way:
‘I’ve cleared out my schedule so I can Think Important Thoughts, and I’ve got that vague idea about that toy model that it would be good to flesh out some time, and I can sort of see how Topic X and Topic Y might be connected if you kind of squint the right way, and it might be worth developing that a bit further, but like I wouldn’t want to force anything, Inspiration Is Mysterious And Shouldn’t Be Rushed… hang on, why have I been reading crap on the internet for the last five days??’
I think this trap is more common among noob writers and artists than noob scientists and programmers, but I managed to fall into it anyway despite studying maths and physics. (I’ve always relied heavily on intuition in both, and that takes you in a very different direction to someone who leans more on formal reasoning.) I’m quite a late convert to systems and planning and organisation, and now I finally get the point I’m fascinated by them and find them extremely useful.
One particular way I tend to fail is that my over-reliance on intuition leads me to think too highly of any old random thoughts that come into my head. And I’ve now come to the (in retrospect obvious) conclusion that a lot of them are transitory and really just plain stupid, and not worth listening to.
As a simple example, I’ve trained myself to get up straight away when the alarm goes off, and every morning my brain fabricates a bullshit explanation for why today is special and actually I can stay in bed, and it’s quite compelling for half a minute or so. I’ve got things set up so I can ignore it and keep doing things, though, and pretty quickly it just goes away and I never wish that I’d listened to it.
On the other hand, I wouldn’t want to tighten things up so much that I completely stopped having the random stream of bullshit thoughts, because that’s where the good ideas bubble up from too. For now I’m going with the following rule of thumb for resolving the tension:
Thoughts can be herded and corralled by systems, and fed and dammed and diverted by them, but don’t take well to being manipulated individually by systems.
So when I get up, for example, I don’t have a system in place where I try to directly engage with the bullshit explanation du jour and come up with clever countertheories for why I actually shouldn’t go back to bed. I just follow a series of habitual getting-up steps, and then after a few minutes my thoughts are diverted to a more useful track, and then I get on with my day.
A more interesting example is the common writers’ strategy of having a set routine (there’s a whole website devoted to these). Maybe they work at the same time each day, or always work in the same place. This is a system, but it’s not a system that dictates the actual content of the writing directly. You just sit and write, and sometimes it’s good, and sometimes it’s awful, and on rare occasions it’s genuinely inspired, and if you keep plugging on those rare occasions hopefully become more frequent. I do something similar with making time to learn physics now and it works nicely.
This post is also a small application of the rule itself! I was on an internet diet for a couple of months, and was expecting to generate a few blog post drafts in that time, and was surprised that basically nothing came out in the absence of my usual internet immersion. I thought writing had finally become a pretty freestanding habit for me, but actually it’s still more fragile and tied to a social context that I expected. So this is a deliberate attempt to get the writing flywheel spun up again with something short and straightforward.
It’s probably not surprising that we reach for a visual metaphor, as sight is so important to us. It’s common to describe improved understanding in terms of seeing further. Galileo named his scientific society the Academy of Lynxes because the lynx was thought to have unparalleled eyesight, though unfortunately that finding seems not to have replicated. (That was the high point of naming scientific institutions, and after that we just got boring stuff like ‘The Royal Society’.)
I’m more attached to smell as a metaphor, though. We do use this one pretty often, talking about having a ‘good nose’ for a problem or ‘sniffing out’ the answer. Or even more commonly when we talk about good or bad taste, given that taste is basically smell.
I’m probably biased because I have atrocious eyesight, and a good sense of smell. I’d rather join an Academy of Trufflehogs. I do think smell fits really well, though, for several reasons:
It’s unmapped. Visual images map into a neat three-dimensional field; smell is a mess.
The vocabulary for smells is bad. There’s a lot more we can detect than we know how to articulate.
It’s deeply integrated into the old brain, strongly plugged into all sorts of odd emotions.
It’s real nonetheless. You can navigate through this mess anyway! Trufflehogs actually find truffles.
3. An even better metaphor, though, is this beautiful one I saw last week from M. John Harrison on Twitter. ‘You became a detector, but you don’t know what it detects’:
every so often something heaves itself around in your imagination
This mental sea change is one of my weird repetitive fascinations that I keep going on about, here and on the old tumblr. Seymour Papert’s ‘falling in love with the gears’, or the ‘positive affective tone’ that started attaching itself to boring geology captions on Wikipedia. The long process of becoming a sensitive antenna, and the longer process of finding out what it’s an antenna for. There is so absolutely NO BETTER STATE THAN THIS.
These are responses to other people’s posts. They’re all a bit short for an individual post but a bit long/tangential/self-absorbed for a reply, so I batched them together here.
1. Easy Mode/Hard Mode inversions
I spend a lot of time being kind of confused and nitpicky about the rationalist community, but there’s one thing they do well that I really really value, which is having a clear understanding of the distinction between doing the thing and doing the things you need to do to look like you’re doing the thing.
Yudkowsky was always clear on this (I’m thinking about the bit on cutting the enemy), and people in the community get it.
I appreciate a lot this having done a PhD. In academia a lot of people seem to have spent so long chasing after the things you need to do to look like you’re doing the thing that they’ve forgotten how to do the thing, or even sometimes that there’s a thing there to do. In parts, the cargo cults have taken over completely.
Zvi Mowshowitz gives doing the thing and doing the things you need to do to look like you’re doing the thing the less unwieldy names of Hard Mode and Easy Mode (at least, I think that’s the key component of what he’s pointing at).
It got me thinking about cases where Easy Mode and Hard Mode could invert completely. In academia, Easy Mode involves keeping up with the state of the art in a rapidly moving narrow subfield, enough to get out a decent number of papers on a popular topic in highly ranked journals during your two year postdoc. You need to make sure you’re in a good position to switch to the new trendy subfield if this one appears to run out of steam, though, because you need to make sure you get that next two year postdoc on the other side of the world, so that …
… wait a minute. Something’s gone wrong here. That sounds really hard!
Hard Mode is pretty ill-defined right now, but I’m not convinced that it necessarily has to be any harder than Easy Mode. I have a really shitty plan and it’s still not obviously worse than the Easy Mode plan.
If there was a risk of a horrible, life-ruining failure in Hard Mode, I’d understand, but there isn’t. The floor, for a STEM PhD student with basic programming skills in a developed economy, is that you get a boring but reasonably paid middle class job and think about what you’re interested in in your spare time. I’m walking along this floor right now and it’s really not bad here. It’s also exactly the same floor you end up on if you fail out of Easy Mode, except you have a few extra years to get acquainted with it.
If there is a genuine inversion here, then probably it’s unstable to perturbations. I’m happy to join in with the kicking.
2. ~The Great Conversation~
Sarah Constantin had the following to say in a recent post:
… John’s motivation for disagreeing with my post was that he didn’t think I should be devaluing the intellectual side of the “rationality community”. My post divided projects into into community-building (mostly things like socializing and mutual aid) versus outward-facing (business, research, activism, etc.); John thought I was neglecting the importance of a community of people who support and take an interest in intellectual inquiry.
I agreed with him on that point — intellectual activity is important to me — but doubted that we had any intellectual community worth preserving. I was skeptical that rationalist-led intellectual projects were making much progress, so I thought the reasonable thing to do was to start fresh.
‘Doubted that we had any intellectual community worth preserving’ is strong stuff! Apparently today is Say Nice Things About The Rationalists Day for me, because I really wanted to argue with it a bit.
I may be completely missing the point on what the ‘rationality community’ is supposed to be in this argument. I’m only arguing for the public-facing, internet community here, because that’s all I really know about. I have no idea about the in-person Berkeley one. Even if I have missed the point, though, I think the following makes sense anyway.
Most subcultures and communities of practice have a bunch of questions people get really exercised about and like to debate. I often internally think of this as ~The Great Conversation~, with satiric tumblr punctuation to indicate it’s not actually always all that great.
I’ve only been in this part of the internet for a few years. Before that I lurked on science blogs (which have some overlap). On science blogs ~The Great Conversation~ includes the replication crisis, alternatives to the current academic publishing system, endless identical complaints about the postdoc system (see part 1 of this post), and ranting about pseudoscience and dodgy alternative therapies.
Sometimes ~The Great Conversation~ involves the big names in the field, but most of the time it’s basically whoever turns up. People who enjoy writing, people who enjoy the sound of their own voice, people with weird new ideas they’re excited about, people on a moral quest to fix things, grumpy postdocs with an axe to grind, bored people, depressed people, lonely people, the usual people on the internet.
If you go to the department common room instead, the academics probably aren’t talking about the things on the science blogs. They’re talking about their current research, or the weird gossip from that other research group, or what the university administration has gone and done this time, or how shit the new coffee machine is. ~The Great Conversation~ is mostly happening elsewhere.
This means that the weirdos on the internet have a surprisingly large amount of control over the big structural questions in the field. This often extends to having control over what those questions are in the first place.
The rationalist community seems to be trying to have ~The Great Conversation~ for as much of human intellectual enquiry as it can manage (or at least as much as it takes seriously). People discuss the replication crisis, but they also discuss theories of cognition, and moral philosophy, and polarisation in politics, and the future of work, and whether Bayesian methods explain absolutely everything in the world or just some things.
The results are pretty mixed, but is there any reasonably sized group out there doing noticeably better, out on the public internet where anyone can join the conversation? If there is I’d love to know about it.
This is a pretty influential position, as lots of interesting people with wide-ranging interests are likely to find it and get sucked in, even if they’re mostly there to argue at the start. Scott Aaronson is one good example. He’s been talking about these funny Singularity people for years, but over time he’s got more and more involved in the community itself.
The rationalist community is some sort of a beacon for something, and to me that ought to count for ‘an intellectual community worth preserving’.
More importantly, the author approaches the game like an art critic in perhaps the best possible sense of that phrase (and with M:TG, there are a lot of bad senses). He treats card design as an art form unto itself (which it clearly is!), and talks about it like a poetic form, with various approaches to creativity within constraints, a historical trajectory with several periods, later work exhibiting a self-consciousness about that history (in Time Spiral, and very differently in Magic 2010), etc.
That is, he’s taking a relatively formal, “internal,” New Criticism-like approach, rather than a historicist approach (relate the work to contemporary extra-artistic phenomena) or an esoteric/Freudian/high-Theory-like approach (take a few elements of the work, link them to some complex of big ideas, uncover an iceberg of ostensibly hidden structure). I don’t think the former approach is strictly better than the latter, but it’s always refreshing because so much existing games criticism takes the latter two approaches.
I know absolutely nothing about M:TG beyond what the acronym stands for, but reading this I realised I’m also really craving sources of this sort of criticism. I recently read Steve Yegge’s giant review of the endgame of Borderlands, a first person shooter that I would personally hate and immediately forgot the name of. Despite this I was completely transfixed by the review, temporarily fascinated by tiny details of gun design, enjoying the detailed explorations of exactly what made the mechanics of the game work so well. This is exactly what I’m looking for! I’d rather have it for fiction or music than games, but I’ll take what I can get.
I kind of imprinted on the New Critics as my ideal of what criticism should be, and although I can see the limitations now (snotty obsession with narrow Western canon, tone deaf to wider societal influences) I still really enjoy the ‘internal’ style. But it’s much easier now to find situated criticism, that wants to relate a piece of art to, say, Marxism or the current political climate. And even easier to find lists of all the ways that that piece of art is problematic and you’re problematic for liking it.
Cynically I’d say that this is because the internal style is harder to do. Works of art are good or bad for vivid and specific internal reasons that require a lot of sensitivity to pinpoint, whereas they’re generally problematic for the same handful of reasons that everything else is problematic. But probably it’s mostly just that the internal style is out of fashion. I’d really enjoy a new New Criticism without the snotty high culture focus.
I find most STEM-vs-the-humanities fight club stuff sort of depressing, because the arguments from the humanities side seem to me to be too weak. (This doesn’t necessarily apply this time – I haven’t tried to catch up on everyone’s posts.) Either people argue that the humanities teach exactly the same skills in systematic thinking that the sciences do, or else you get the really dire ‘the arts teach you to be a real human being‘ arguments.
I think there’s another distinction that often gets lost. There are two types of understanding I’d like to distinguish, that I’m going to call explicit and tacit understanding in this post. I don’t know if those are the best words, so let me know if you think I should be calling them something different. Both are rigorous and reliable paths to new knowledge, and both are important in both the arts and sciences. I would argue, however, that explicit understanding is generally more important in science, and tacit understanding is more important in the arts.
(I’m interested in this because my own weirdo learning style could be described as something like ‘doing maths and physics, but navigating by tacit understanding’. I’ve been saying for years that ‘I’m trying to do maths like an arts student’, and I’m just starting to understand what I mean by that. Also I feel like it’s been a bad, well, century for tacit understanding, and I want to defend it where I can.)
Anyway, let’s explain what I mean by this. Explicit understanding is the kind you come to by following formal logical rules. Scott Alexander gives an example of ‘people who do computer analyses of Shakespeare texts to see if they contain the word “the” more often than other Shakespeare texts with enough statistical significance to conclude that maybe they were written by different people’. This is explicit understanding as applied to the humanities. It produces interesting results there, just as it does in science. Also, if this was all people did in the humanities they would be horribly impoverished, whereas science might (debatably) just about survive.
Tacit understanding is more like the kind you ‘develop a nose for’, or learn to ‘just see’. That’s vague, so here are some examples:
Taking a piece of anonymised writing and trying to guess the date and author. This is a really rigorous and difficult thing my dad had to do in university (before pomo trashed the curriculum, [insert rant here]). It requires very wide-ranging historical reading, obviously, but also on-the-fly sensitivity to delicate tonal differences. You’re not combing through the passage saying ‘this specific sentence construction indicates that this passage is definitely from the late seventeenth century’. There might be some formal rules like this that you can extract, but it will take ages, and while you’re doing the thing you’re more relying on gestalt feelings of ‘this just looks like Dryden’. You don’t especially need to formalise it, because you can get it right anyway.
Parody. This is basically the same thing, except this time it’s you generating the writing to fit the author. Scott is excellent at this himself! Freddie DeBoer uses this technique to teach prose style, which sounds like a great way to develop a better ear for it.
Translation. I can’t say too much about this one, because I’ve never learned a foreign language :(. But you have the problem of matching the meaning of the source, except that every word has complex harmonic overtones of different meanings and associations, and you have to try and do justice to those as well as best as you can. Again, it’s a very skilled task that you can absolutely do a better or worse job at, but not a task that’s achieved purely through rule following.
I wish these kinds of tacit skills were appreciated more. If the only sort of understanding you value is explicit understanding, then the arts are going to look bad by comparison. This is not the fault of the arts!
I’m going to start reintroducing a few tumblr-style posts without much editing, as this thing is starting to develop a stodgy Real Blog atmosphere where I feel like I need to post Proper Serious Writing.
This is supposed to be more of a workbook, and I think I’ll learn faster if I up the percentage of experimental/embarrassing/badly-thought-out posts.
There’s this mindset I sometimes kick myself into, which is roughly ‘I’m going to work hard at this thing, and I’m going to like it.‘
It’s got a very specific emotional tone and a specific range of application. I wouldn’t bother trying to use it for utterly dull stuff like the washing up where I do not care at all. On the other hand, there’s a definite theatrical aspect (the ‘and I’m going to like it’ bit) where I’m kind of faking up the enthusiasm in the hope that some genuine enthusiasm will follow. Getting up early in the winter and working when it’s still dark outside is the right sort of situation for it.
I’d never really thought consciously about this before, but I noticed the other morning that it’s got three different images attached to it in my head. By ‘image’ I don’t mean a vivid mental picture (I don’t have much of a visual imagination at all, oddly for someone who loves geometry), just vague sort-of-images or bits of phrases that cluster round the thing.
The first one is a half-remembered line from The Waste Land, something about ‘the boat responded gaily to the slightest touch’. The real version turns out to be ‘Damyata: The boat responds / Gaily, to the hand expert with sail and oar’.
This is highly relevant. It contains the right sort of things: precision and responsiveness and genuine enjoyment. I’m actually impressed with whatever part of my brain came up with that, apparently without much conscious supervision.
After that the images go downhill fast. The second is something to do with oxen yoked to a plough. Which is not imaginative at all, and also a pretty miserable vision of the potential rewards of hard work. I guess there’s a kind of stoic, stubborn element that’s useful here.
Also, I have never in my life thought clearly about what oxen yoked to a plough actually look like (though of course I’m googling it now). The words in my head are something about oxen yoked to a plough, but the image is more like an old-fashioned heavy leather horse harness.
The third part, ludicrously, is something like one of those glaucoma testing machines you get at the opticians. I can’t quickly find a public domain image, just google it if you don’t know what I’m talking about. I’m not imagining the bit that puffs an unpleasant jet of air into your eye, but the bar bit you push your forehead against in order to keep your face aligned properly.
Apparently this is how I’m taking the image of the harness, which is attached to the ox, and applying it to myself. Sticking my forehead against this machine is how I’m yoking myself to the badly-imagined plough – it’s the crucial image that makes the other two apply to me specifically.
I had no idea I was imagining something so specific and weird. Imagine trying to consciously think up this crap! But somehow it kind of hangs together as something inspiring, if you don’t look at the component parts: fluid delicacy mixed with stolid determination, joined (of course) at the forehead. By a glaucoma machine!
It’s hopeless to try and write about this sort of thing accurately, because so much of what’s going on is not language-based. (And there’s a mess of other associations when I start thinking about this. I’m not sure the process stops, there’s just more and more of this nonsense.) But it’s also fun to try, because it’s all so entertainingly stupid!