nhaliday + core-rats   87

The Law of Leaky Abstractions – Joel on Software
[TCP/IP example]

All non-trivial abstractions, to some degree, are leaky.


- Something as simple as iterating over a large two-dimensional array can have radically different performance if you do it horizontally rather than vertically, depending on the “grain of the wood” — one direction may result in vastly more page faults than the other direction, and page faults are slow. Even assembly programmers are supposed to be allowed to pretend that they have a big flat address space, but virtual memory means it’s really just an abstraction, which leaks when there’s a page fault and certain memory fetches take way more nanoseconds than other memory fetches.

- The SQL language is meant to abstract away the procedural steps that are needed to query a database, instead allowing you to define merely what you want and let the database figure out the procedural steps to query it. But in some cases, certain SQL queries are thousands of times slower than other logically equivalent queries. A famous example of this is that some SQL servers are dramatically faster if you specify “where a=b and b=c and a=c” than if you only specify “where a=b and b=c” even though the result set is the same. You’re not supposed to have to care about the procedure, only the specification. But sometimes the abstraction leaks and causes horrible performance and you have to break out the query plan analyzer and study what it did wrong, and figure out how to make your query run faster.


- C++ string classes are supposed to let you pretend that strings are first-class data. They try to abstract away the fact that strings are hard and let you act as if they were as easy as integers. Almost all C++ string classes overload the + operator so you can write s + “bar” to concatenate. But you know what? No matter how hard they try, there is no C++ string class on Earth that will let you type “foo” + “bar”, because string literals in C++ are always char*’s, never strings. The abstraction has sprung a leak that the language doesn’t let you plug. (Amusingly, the history of the evolution of C++ over time can be described as a history of trying to plug the leaks in the string abstraction. Why they couldn’t just add a native string class to the language itself eludes me at the moment.)

- And you can’t drive as fast when it’s raining, even though your car has windshield wipers and headlights and a roof and a heater, all of which protect you from caring about the fact that it’s raining (they abstract away the weather), but lo, you have to worry about hydroplaning (or aquaplaning in England) and sometimes the rain is so strong you can’t see very far ahead so you go slower in the rain, because the weather can never be completely abstracted away, because of the law of leaky abstractions.

One reason the law of leaky abstractions is problematic is that it means that abstractions do not really simplify our lives as much as they were meant to. When I’m training someone to be a C++ programmer, it would be nice if I never had to teach them about char*’s and pointer arithmetic. It would be nice if I could go straight to STL strings. But one day they’ll write the code “foo” + “bar”, and truly bizarre things will happen, and then I’ll have to stop and teach them all about char*’s anyway.


The law of leaky abstractions means that whenever somebody comes up with a wizzy new code-generation tool that is supposed to make us all ever-so-efficient, you hear a lot of people saying “learn how to do it manually first, then use the wizzy tool to save time.” Code generation tools which pretend to abstract out something, like all abstractions, leak, and the only way to deal with the leaks competently is to learn about how the abstractions work and what they are abstracting. So the abstractions save us time working, but they don’t save us time learning.

People think a lot about abstractions and how to design them well. Here’s one feature I’ve recently been noticing about well-designed abstractions: they should have simple, flexible and well-integrated escape hatches.
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july 2019 by nhaliday
Why read old philosophy? | Meteuphoric
(This story would suggest that in physics students are maybe missing out on learning the styles of thought that produce progress in physics. My guess is that instead they learn them in grad school when they are doing research themselves, by emulating their supervisors, and that the helpfulness of this might partially explain why Nobel prizewinner advisors beget Nobel prizewinner students.)

The story I hear about philosophy—and I actually don’t know how much it is true—is that as bits of philosophy come to have any methodological tools other than ‘think about it’, they break off and become their own sciences. So this would explain philosophy’s lone status in studying old thinkers rather than impersonal methods—philosophy is the lone ur-discipline without impersonal methods but thinking.

This suggests a research project: try summarizing what Aristotle is doing rather than Aristotle’s views. Then write a nice short textbook about it.
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june 2018 by nhaliday
trees are harlequins, words are harlequins — bayes: a kinda-sorta masterpost
lol, gwern: https://www.reddit.com/r/slatestarcodex/comments/6ghsxf/biweekly_rational_feed/diqr0rq/
> What sort of person thinks “oh yeah, my beliefs about these coefficients correspond to a Gaussian with variance 2.5″? And what if I do cross-validation, like I always do, and find that variance 200 works better for the problem? Was the other person wrong? But how could they have known?
> ...Even ignoring the mode vs. mean issue, I have never met anyone who could tell whether their beliefs were normally distributed vs. Laplace distributed. Have you?
I must have spent too much time in Bayesland because both those strike me as very easy and I often think them! My beliefs usually are Laplace distributed when it comes to things like genetics (it makes me very sad to see GWASes with flat priors), and my Gaussian coefficients are actually a variance of 0.70 (assuming standardized variables w.l.o.g.) as is consistent with field-wide meta-analyses indicating that d>1 is pretty rare.
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august 2017 by nhaliday
Superintelligence Risk Project Update II

For example, I asked him what he thought of the idea that to we could get AGI with current techniques, primarily deep neural nets and reinforcement learning, without learning anything new about how intelligence works or how to implement it ("Prosaic AGI" [1]). He didn't think this was possible, and believes there are deep conceptual issues we still need to get a handle on. He's also less impressed with deep learning than he was before he started working in it: in his experience it's a much more brittle technology than he had been expecting. Specifically, when trying to replicate results, he's often found that they depend on a bunch of parameters being in just the right range, and without that the systems don't perform nearly as well.

The bottom line, to him, was that since we are still many breakthroughs away from getting to AGI, we can't productively work on reducing superintelligence risk now.

He told me that he worries that the AI risk community is not solving real problems: they're making deductions and inferences that are self-consistent but not being tested or verified in the world. Since we can't tell if that's progress, it probably isn't. I asked if he was referring to MIRI's work here, and he said their work was an example of the kind of approach he's skeptical about, though he wasn't trying to single them out. [2]

Earlier this week I had a conversation with an AI researcher [1] at one of the main industry labs as part of my project of assessing superintelligence risk. Here's what I got from them:

They see progress in ML as almost entirely constrained by hardware and data, to the point that if today's hardware and data had existed in the mid 1950s researchers would have gotten to approximately our current state within ten to twenty years. They gave the example of backprop: we saw how to train multi-layer neural nets decades before we had the computing power to actually train these nets to do useful things.

Similarly, people talk about AlphaGo as a big jump, where Go went from being "ten years away" to "done" within a couple years, but they said it wasn't like that. If Go work had stayed in academia, with academia-level budgets and resources, it probably would have taken nearly that long. What changed was a company seeing promising results, realizing what could be done, and putting way more engineers and hardware on the project than anyone had previously done. AlphaGo couldn't have happened earlier because the hardware wasn't there yet, and was only able to be brought forward by massive application of resources.

Summary: I'm not convinced that AI risk should be highly prioritized, but I'm also not convinced that it shouldn't. Highly qualified researchers in a position to have a good sense the field have massively different views on core questions like how capable ML systems are now, how capable they will be soon, and how we can influence their development. I do think these questions are possible to get a better handle on, but I think this would require much deeper ML knowledge than I have.
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july 2017 by nhaliday
Defection – quas lacrimas peperere minoribus nostris!

Kindness Against The Grain: https://srconstantin.wordpress.com/2017/06/08/kindness-against-the-grain/
I’ve heard from a number of secular-ish sources (Carse, Girard, Arendt) that the essential contribution of Christianity to human thought is the concept of forgiveness. (Ribbonfarm also has a recent post on the topic of forgiveness.)

I have never been a Christian and haven’t even read all of the New Testament, so I’ll leave it to commenters to recommend Christian sources on the topic.

What I want to explore is the notion of kindness without a smooth incentive gradient.

The Social Module: https://bloodyshovel.wordpress.com/2015/10/09/the-social-module/
Now one could propose that the basic principle of human behavior is to raise the SP number. Sure there’s survival and reproduction. Most people would forget all their socialization if left hungry and thirsty for days in the jungle. But more often than not, survival and reproduction depend on being high status; having a good name among your peers is the best way to get food, housing and hot mates.

The way to raise one’s SP number depends on thousands of different factors. We could grab most of them and call them “culture”. In China having 20 teenage mistresses as an old man raises your SP; in Western polite society it is social death. In the West making a fuss about disobeying one’s parents raises your SP, everywhere else it lowers it a great deal. People know that; which is why bureaucrats in China go to great lengths to acquire a stash of young women (who they seldom have time to actually enjoy), while teenagers in the West go to great lengths to be annoying to their parents for no good reason.


It thus shouldn’t surprise us that something as completely absurd as Progressivism is the law of the land in most of the world today, even though it denies obvious reality. It is not the case that most people know that progressive points are all bogus, but obey because of fear or cowardice. No, an average human brain has much more neurons being used to scan the social climate and see how SP are allotted, than neurons being used to analyze patterns in reality to ascertain the truth. Surely your brain does care a great deal about truth in some very narrow areas of concern to you. Remember Conquest’s first law: Everybody is Conservative about what he knows best. You have to know the truth about what you do, if you are to do it effectively.

But you don’t really care about truth anywhere else. And why would you? It takes time and effort you can’t really spare, and it’s not really necessary. As long as you have some area of specialization where you can make a living, all the rest you must do to achieve survival and reproduction is to raise your SP so you don’t get killed and your guts sacrificed to the mountain spirits.

SP theory (I accept suggestions for a better name) can also explains the behavior of leftists. Many conservatives of a medium level of enlightenment point out the paradox that leftists historically have held completely different ideas. Leftism used to be about the livelihood of industrial workers, now they agitate about the environment, or feminism, or foreigners. Some people would say that’s just historical change, or pull a No True Scotsman about this or that group not being really leftists. But that’s transparent bullshit; very often we see a single person shifting from agitating about Communism and worker rights, to agitate about global warming or rape culture.


The leftist strategy could be defined as “psychopathic SP maximization”. Leftists attempt to destroy social equilibrium so that they can raise their SP number. If humans are, in a sense, programmed to constantly raise their status, well high status people by definition can’t raise it anymore (though they can squabble against each other for marginal gains), their best strategy is to freeze society in place so that they can enjoy their superiority. High status people by definition have power, and thus social hierarchy during human history tends to be quite stable.

This goes against the interests of many. First of all the lower status people, who, well, want to raise their status, but can’t manage to do so. And it also goes against the interests of the particularly annoying members of the upper class who want to raise their status on the margin. Conservative people can be defined as those who, no matter the absolute level, are in general happy with it. This doesn’t mean they don’t want higher status (by definition all humans do), but the output of other brain modules may conclude that attempts to raise SP might threaten one’s survival and reproduction; or just that the chances of raising one’s individual SP is hopeless, so one might as well stay put.


You can’t blame people for being logically inconsistent; because they can’t possibly know anything about all these issues. Few have any experience or knowledge about evolution and human races, or about the history of black people to make an informed judgment on HBD. Few have time to learn about sex differences, and stuff like the climate is as close to unknowable as there is. Opinions about anything but a very narrow area of expertise are always output of your SP module, not any judgment of fact. People don’t know the facts. And even when they know; I mean most people have enough experience with sex differences and black dysfunction to be quite confident that progressive ideas are false. But you can never be sure. As Hume said, the laws of physics are a judgment of habit; who is to say that a genie isn’t going to change all you know the next morning? At any rate, you’re always better off toeing the line, following the conventional wisdom, and keeping your dear SP. Perhaps you can even raise them a bit. And that is very nice. It is niceness itself.

Leftism is just an easy excuse: https://bloodyshovel.wordpress.com/2015/03/01/leftism-is-just-an-easy-excuse/
Unless you’re not the only defector. You need a way to signal your intention to defect, so that other disloyal fucks such as yourself (and they’re bound to be others) can join up, thus reducing the likely costs of defection. The way to signal your intention to defect is to come up with a good excuse. A good excuse to be disloyal becomes a rallying point through which other defectors can coordinate and cover their asses so that the ruling coalition doesn’t punish them. What is a good excuse?

Leftism is a great excuse. Claiming that the ruling coalition isn’t leftist enough, isn’t holy enough, not inclusive enough of women, of blacks, of gays, or gorillas, of pedophiles, of murderous Salafists, is the perfect way of signalling your disloyalty towards the existing power coalition. By using the existing ideology and pushing its logic just a little bit, you ensure that the powerful can’t punish you. At least not openly. And if you’re lucky, the mass of disloyal fucks in the ruling coalition might join your banner, and use your exact leftist point to jump ship and outflank the powerful.


The same dynamic fuels the flattery inflation one sees in monarchical or dictatorial systems. In Mao China, if you want to defect, you claim to love Mao more than your boss. In Nazi Germany, you proclaim your love for Hitler and the great insight of his plan to take Stalingrad. In the Roman Empire, you claimed that Caesar is a God, son of Hercules, and those who deny it are treacherous bastards. In Ancient Persia you loudly proclaimed your faith in the Shah being the brother of the Sun and the Moon and King of all Kings on Earth. In Reformation Europe you proclaimed that you have discovered something new in the Bible and everybody else is damned to hell. Predestined by God!


And again: the precise content of the ideological point doesn’t matter. Your human brain doesn’t care about ideology. Humans didn’t evolve to care about Marxist theory of class struggle, or about LGBTQWERTY theories of social identity. You just don’t know what it means. It’s all abstract points you’ve been told in a classroom. It doesn’t actually compute. Nothing that anybody ever said in a political debate ever made any actual, concrete sense to a human being.

So why do we care so much about politics? What’s the point of ideology? Ideology is just the water you swim in. It is a structured database of excuses, to be used to signal your allegiance or defection to the existing ruling coalition. Ideology is just the feed of the rationalization Hamster that runs incessantly in that corner of your brain. But it is immaterial, and in most cases actually inaccessible to the logical modules in your brain.

Nobody ever acts on their overt ideological claims if they can get away with it. Liberals proclaim their faith in the potential of black children while clustering in all white suburbs. Communist party members loudly talk about the proletariat while being hedonistic spenders. Al Gore talks about Global Warming while living in a lavish mansion. Cognitive dissonance, you say? No; those cognitive systems are not connected in the first place.


And so, every little step in the way, power-seekers moved the consensus to the left. And open societies, democratic systems are by their decentralized nature, and by the size of their constituencies, much more vulnerable to this sort of signalling attacks. It is but impossible to appraise and enforce the loyalty of every single individual involved in a modern state. There’s too many of them. A Medieval King had a better chance of it; hence the slow movement of ideological innovation in those days. But the bigger the organization, the harder it is to gather accurate information of the loyalty of the whole coalition; and hence the ideological movement accelerates. And there is no stopping it.

Like the Ancients, We Have Gods. They’ll Get Greater: http://www.overcomingbias.com/2018/04/like-the-ancients-we-have-gods-they-may-get… [more]
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june 2017 by nhaliday
In Defense of Individualist Culture | Otium
The salient feature of an individualist environment is that nobody directly tries to make you do anything.


I see a lot of writers these days raising problems with modern individualist culture, and it may be an especially timely topic. The Internet is a novel superstimulus, and it changes more rapidly, and affords people more options, than ever before. We need to think about the actual consequences of a world where many people are in practice being left alone to do what they want, and clearly not all the consequences are positive.

But I do want to suggest some considerations in favor of individualist culture — that often-derided “atomized modern world” that most of us live in.

We Aren’t Clay

interesting: https://slatestarscratchpad.tumblr.com/post/162329749236/httpssrconstantinwordpresscom20170627in-de

Patriarchy is the Problem: https://srconstantin.wordpress.com/2017/09/12/patriarchy-is-the-problem/
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june 2017 by nhaliday
Links 5/17: Rip Van Linkle | Slate Star Codex
More on Low-Trust Russia: Do Russian Who Wants To Be A Millionaire contestants avoid asking the audience because they expect audience members to deliberately mislead them?

Xenocrypt on the math of economic geography: “A party’s voters should get more or less seats based on the shape of the monotonic curve with integral one they can be arranged in” might sound like a very silly belief, but it is equivalent to the common mantra that you deserve to lose if your voters are ‘too clustered’”

Okay, look, I went way too long between writing up links posts this time, so you’re getting completely dated obsolete stuff like Actually, Neil Gorsuch Is A Champion Of The Little Guy. But aside from the Gorsuch reference this is actually pretty timeless – basically an argument for strict constructionism on the grounds that “a flexible, living, bendable law will always tend to be bent in the direction of the powerful.”

Otium: Are Adult Developmental Stages Real? Looks at Kohlberg, Kegan, etc.

I mentioned the debate over 5-HTTLPR, a gene supposedly linked to various mental health outcomes, in my review of pharmacogenomics. Now a very complete meta-analysis finds that a lot of the hype around it isn’t true. This is pretty impressive since there are dozens of papers claiming otherwise, and maybe the most striking example yet of how apparently well-replicated a finding can be and still fail to pan out.

Rootclaim describes itself as a crowd-sourced argument mapper. See for example its page on who launched the chemical attack in Syria.

Apparently if you just kill off all the cells that are growing too old, you can partly reverse organisms’ aging (paper, popular article)

The Politics Of The Gene: “Contrary to expectations, however, we find little evidence that it is more common for whites, the socioeconomically advantaged, or political conservatives to believe that genetics are important for health and social outcomes.”

Siberian Fox linked me to two studies that somewhat contradicted my minimalist interpretation of childhood trauma here: Alemany on psychosis and Turkheimer on harsh punishment.

Lyrebird is an AI project which, if fed samples of a person’s voice, can read off any text you want in the same voice. See their demo with Obama, Trump, and Hillary (I find them instantly recognizable but not at all Turing-passing). They say making this available is ethical because it raises awareness of the potential risk, which a Facebook friend compared to “selling nukes to ISIS in order to raise awareness of the risk of someone selling nukes to ISIS.”

Freddie deBoer gives lots of evidence that there is no shortage of qualified STEM workers relative to other fields and the industry is actually pretty saturated. But Wall Street Journal seems to think they have evidence for the opposite? Curious what all of the tech workers here think.

Scott Sumner: How Can There Be A Shortage Of Construction Workers? That is, is it at all plausible that (as help wanted ads would suggest) there are areas where construction companies can’t find unskilled laborers willing to work for $90,000/year? Sumner splits this question in two – first, an economics question of why an efficient market wouldn’t cause salaries to rise to a level that guarantees all jobs get filled. And second, a political question of how this could happen in a country where we’re constantly told that unskilled men are desperate because there are no job opportunities for them anymore. The answers seem to be “there’s a neat but complicated economics reason for the apparent inefficiency” and “the $90,000 number is really misleading but there may still be okay-paying construction jobs going unfilled and that’s still pretty strange”.

Study which is so delightfully contrarian I choose to reblog it before reading it all the way through: mandatory class attendance policies in college decrease grades by preventing students from making rational decisions about when and how to study.
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may 2017 by nhaliday
Performance Trends in AI | Otium
Deep learning has revolutionized the world of artificial intelligence. But how much does it improve performance? How have computers gotten better at different tasks over time, since the rise of deep learning?

In games, what the data seems to show is that exponential growth in data and computation power yields exponential improvements in raw performance. In other words, you get out what you put in. Deep learning matters, but only because it provides a way to turn Moore’s Law into corresponding performance improvements, for a wide class of problems. It’s not even clear it’s a discontinuous advance in performance over non-deep-learning systems.

In image recognition, deep learning clearly is a discontinuous advance over other algorithms. But the returns to scale and the improvements over time seem to be flattening out as we approach or surpass human accuracy.

In speech recognition, deep learning is again a discontinuous advance. We are still far away from human accuracy, and in this regime, accuracy seems to be improving linearly over time.

In machine translation, neural nets seem to have made progress over conventional techniques, but it’s not yet clear if that’s a real phenomenon, or what the trends are.

In natural language processing, trends are positive, but deep learning doesn’t generally seem to do better than trendline.


The learned agent performs much better than the hard-coded agent, but moves more jerkily and “randomly” and doesn’t know the law of reflection. Similarly, the reports of AlphaGo producing “unusual” Go moves are consistent with an agent that can do pattern-recognition over a broader space than humans can, but which doesn’t find the “laws” or “regularities” that humans do.

Perhaps, contrary to the stereotype that contrasts “mechanical” with “outside-the-box” thinking, reinforcement learners can “think outside the box” but can’t find the box?

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january 2017 by nhaliday
So apparently this is why we have positive psychology but not evidence-based psychological treatment
APA presidents are supposed to have an initiative and… I thought mine could be “evidence-based treatment and prevention.” So I went to my friend, Steve Hyman, the director of [National Institute of Mental Health]. He was thrilled and told me he would chip in $40 million dollars if I could get APA working on evidence-based treatment.

So I told CAPP [which owns the APA] about my plan and about NIMH’s willingness. I felt the room get chillier and chillier. I rattled on. Finally, the chair of CAPP memorably said, “What if the evidence doesn’t come out in our favor?”

…I limped my way to [my friend’s] office for some fatherly advice.

“Marty,” he opined, “you are trying to be a transactional president. But you cannot out-transact these people…”

And so I proposed that Psychology turn its… attention away from pathology and victimology and more toward what makes life worth living: positive emotion, positive character, and positive institutions. I never looked back and this became my mission for the next fifteen years. The endeavor… caught on.
ratty  quotes  stories  psychology  social-psych  replication  social-science  lol  core-rats  evidence-based 
january 2017 by nhaliday
Overcoming Bias : On the goodness of Beeminder
There is a lot of leeway in what indicators you measure, and some I tried didn’t help much. The main things I measure lately are:

- number of 20 minute blocks of time spent working. They have to be continuous, though a tiny bit of interruption is allowed if someone else causes it
- time spent exercising weighted by the type of exercise e.g. running = 2x dancing = 2 x walking
- points accrued for doing tasks on my to-do list. When I think of anything I want to do I put it on the list, whether it’s watching a certain movie or figuring out how to make the to do list system better. Some things stay there permanently, e.g. laundry. I assign each task a number of points, which goes up every Sunday if it’s still on the list. I have to get 15 points per day or I lose.
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january 2017 by nhaliday
Morris on the great divergence
Eighteenth-century intellectuals called this approach kaozheng, “evidential research.” It emphasized facts over speculation, bringing methodical, rigorous approaches to fields as diverse as mathematics, astronomy, geography, linguistics, and history, and consistently developing rules for assessing evidence. Kaozheng paralleled western Europe’s scientific revolution in every way—except one: it did not develop a mechanical model of nature.
history  china  asia  europe  comparison  science  culture  anthropology  industrial-revolution  quotes  ratty  economics  speculation  growth-econ  divergence  core-rats  early-modern  the-great-west-whale  roots  frontier  age-of-discovery  discovery  technology  innovation  analytical-holistic  empirical  🎩  🤖  civilization  sinosphere  s:*  definite-planning  big-picture  🔬  broad-econ  info-dynamics  revolution  chart  lens  zeitgeist  wealth-of-nations  great-powers  enlightenment-renaissance-restoration-reformation  n-factor  orient  occident  modernity  the-trenches  thinking  physics 
december 2016 by nhaliday
Fact Posts: How and Why
The most useful thinking skill I've taught myself, which I think should be more widely practiced, is writing what I call "fact posts." I write a bunch of these on my blog. (I write fact posts about pregnancy and childbirth here.)

To write a fact post, you start with an empirical question, or a general topic. Something like "How common are hate crimes?" or "Are epidurals really dangerous?" or "What causes manufacturing job loss?"

It's okay if this is a topic you know very little about. This is an exercise in original seeing and showing your reasoning, not finding the official last word on a topic or doing the best analysis in the world.

Then you open up a Google doc and start taking notes.

You look for quantitative data from conventionally reliable sources. CDC data for incidences of diseases and other health risks in the US; WHO data for global health issues; Bureau of Labor Statistics data for US employment; and so on. Published scientific journal articles, especially from reputable journals and large randomized studies.

You explicitly do not look for opinion, even expert opinion. You avoid news, and you're wary of think-tank white papers. You're looking for raw information. You are taking a sola scriptura approach, for better and for worse.

And then you start letting the data show you things.

You see things that are surprising or odd, and you note that.

You see facts that seem to be inconsistent with each other, and you look into the data sources and methodology until you clear up the mystery.

You orient towards the random, the unfamiliar, the things that are totally unfamiliar to your experience. One of the major exports of Germany is valves? When was the last time I even thought about valves? Why valves, what do you use valves in? OK, show me a list of all the different kinds of machine parts, by percent of total exports.

And so, you dig in a little bit, to this part of the world that you hadn't looked at before. You cultivate the ability to spin up a lightweight sort of fannish obsessive curiosity when something seems like it might be a big deal.

And you take casual notes and impressions (though keeping track of all the numbers and their sources in your notes).

You do a little bit of arithmetic to compare things to familiar reference points. How does this source of risk compare to the risk of smoking or going horseback riding? How does the effect size of this drug compare to the effect size of psychotherapy?

You don't really want to do statistics. You might take percents, means, standard deviations, maybe a Cohen's d here and there, but nothing fancy. You're just trying to figure out what's going on.

It's often a good idea to rank things by raw scale. What is responsible for the bulk of deaths, the bulk of money moved, etc? What is big? Then pay attention more to things, and ask more questions about things, that are big. (Or disproportionately high-impact.)

You may find that this process gives you contrarian beliefs, but often you won't, you'll just have a strongly fact-based assessment of why you believe the usual thing.
ratty  lesswrong  essay  rhetoric  meta:rhetoric  epistemic  thinking  advice  street-fighting  scholar  checklists  🤖  spock  writing  2016  info-foraging  rat-pack  clarity  systematic-ad-hoc  bounded-cognition  info-dynamics  let-me-see  nitty-gritty  core-rats  evidence-based  truth  grokkability-clarity 
december 2016 by nhaliday
Ra | Otium
Ra = smooth, blank, prestigeful (or maybe just statusful) authority


Vagueness, mental fog, “underconfidence”, avoidance, evasion, blanking out, etc. are hallmarks of Ra. If cornered, a person embodying Ra will abruptly switch from blurry vagueness to anger and nihilism.

Ra is involved in the sense of “everyone but me is in on the joke, there is a Thing that I don’t understand myself but is the most important Thing, and I must approximate or imitate or cargo-cult the Thing, and anybody who doesn’t is bad.”

Ra causes persistent brain fog or confusion, especially around economic thinking or cost-benefit analysis or quantitative estimates.

Ra causes a disinclination to express oneself. An impression that a person who is unknown or mysterious is more attractive or favorably received than a person who is an “open book.”

Ra is fake Horus.
things  thinking  mystic  postrat  status  signaling  essay  civilization  society  power  insight  hmm  metabuch  🦀  hidden-motives  leviathan  models  2016  core-rats  minimalism  frisson  ratty  vague  cost-benefit  schelling  order-disorder  emotion  info-dynamics  elegance  judgement 
october 2016 by nhaliday
Haidt-Love Relationship | Otium
Jonathan Haidt has an ideology. In his academic life, he poses positive questions, but he definitely has a normative position as well. And you can see this most clearly in his speeches to young people, which are sermons on Haidtism.

Here is an example.

In it, he contrasts “Coddle U” with “Strengthen U,” two archetypal colleges. He’s clearly arguing in favor of psychological resilience, and against fragility. Let’s leave aside the question of whether feminists and other activists are actually oversensitive weenies, and whether trigger warnings are actually coddling, and engage with his main point, that it is better not to be an oversensitive weenie.

Haidt seems to see this as self-evident. The emotionally weak are to be mocked; the emotionally strong are to be respected.

I don’t find it as obvious.
haidt  critique  regularizer  society  psychology  stress  core-rats  ratty  ideology  values  serene  emotion 
august 2016 by nhaliday
Chronicles of Harry
seems very active across multiple rationalist-type sites
rationality  blog  people  math  hmm  yvain  stream  🤖  ratty  core-rats  diaspora 
august 2016 by nhaliday
Air Conditioning: Harmful?
As someone who has never lived with AC and is excited about whole house fans, it's easy for me to read things like this and feel virtuously smug. I'm so much better than those selfish people who keep themselves cool at the expense of the planet, go me! But my carbon footprint isn't actually lower than someone's in Orlando, because of heating. Heating emits less CO2 per degree than cooling, but in places where people live it typically requires many fewer degrees of cooling to get into the comfortable range.

There's a large ongoing migration from cold places to warm ones, facilitated by air conditioning, mostly in the form of having the vast majority of new housing construction being in the warm parts of the country. This is very beneficial from a climate perspective, and an anti-AC attitude, where AC is a luxury but heating is an unavoidable necessity, isn't helpful.
street-fighting  environment  data  rationality  essay  insight  len:short  cocktail  ratty  core-rats  infrastructure  energy-resources 
july 2016 by nhaliday
Nootropics | Otium
Bottom Lines

Caffeine, modafinil, amphetamine, methylphenidate, and maybe a discontinued nicotinic-receptor agonist drug called ispronicline, have really big effects on cognitive function in healthy people.

Caffeine and modafinil work significantly better in sleep-deprived than non-sleep-deprived people.

Caffeine, nicotine, and amphetamine, in contrast to methylphenidate and modafinil, do not improve memory performance or accuracy on cognitive tasks in healthy people, but only reaction time. In other words: caffeine, nicotine, and amphetamine make you more alert but not smarter; methylphenidate and modafinil also seem to improve memory.

Amphetamine and modafinil work better on people with the COMT val/val phenotype (who tend to be less intelligent) and may be ineffective or counterproductive on COMT met/met phenotype people.

All of the above (caffeine, nicotine, modafinil, amphetamine, and methylphenidate) cause some tolerance.

Cerebrolysin, a mixture of neural growth factors, apparently works really well on Alzheimer’s patients, though there’s fewer studies of it than more common Alzheimer’s drugs. It might extrapolate to people with other kinds of neurodegenerative problems, or to slow the effects of aging.

Cognitive training (memorization practice including spaced repetition) works moderately well on Alzheimer’s patients and schizophrenics. It’s quite plausible that it’s also good for healthy people.

Healthy people can get small positive effects from nicotine, possibly the herb Bacopa monniera, and from transcranial magnetic stimulation.

Alzheimer’s patients can get small effects from cholinesterase inhibitors (which are standard Alzheimer’s drugs); from a mixture of vitamins, fatty acids, choline, and uridine; from melatonin, the hormone which regulates sleep; and from the amino acid derivative acetyl-l-carnitine. Apart from the cholinesterase inhibitors (which have GI side effects) these are safe for healthy people to take, but it’s not known whether they affect cognitive function in healthy people.
summary  reflection  nootropics  neuro  drugs  list  survey  reference  yvain  hmm  len:long  ssc  ratty  🤖  faq  core-rats  big-picture  iteration-recursion  learning  retention  chart 
june 2016 by nhaliday
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