# Cyan

Karma: 5,429
• Of course experimental design is very important in general. But VAuroch and I agree that when two designs give rise to the same likelihood function, the information that comes in from the data are equivalent. We disagree about the weight to give to the information that comes in from what the choice of experimental design tells us about the experimenter’s prior state of knowledge.

• 31 Aug 2015 2:22 UTC
3 points

you’re ignoring critical information

No, it practical terms it’s negligible. There’s a reason that double-blind trials are the gold standard—it’s because doctors are as prone to cognitive biases as anyone else.

Let me put it this way: recently a pair of doctors looked at the available evidence and concluded (foolishly!) that putting fecal bacteria in the brains of brain cancer patients was such a promising experimental treatment that they did an end-run around the ethics review process—and after leaving that job under a cloud, one of them was still considered a “star free agent”. Well, perhaps so—but I think this little episode illustrates very well that a doctor’s unsupported opinion about the efficacy of his or her novel experimental treatment isn’t worth the shit s/​he wants to place inside your skull.

• You’re going to have a hard time convincing me that… vectors are a necessary precursor for regression analysis...

So you’re fitting a straight line. Parameter estimates don’t require linear algebra (that is, vectors and matrices). Super. But the immediate next step in any worthwhile analysis of data is calculating a confidence set (or credible set, if you’re a Bayesian) for the parameter estimates; good luck teaching that if your students don’t know basic linear algebra. In fact, all of regression analysis, from the most basic least squares estimator through multilevel/​hierarchical regression models up to the most advanced sparse “p >> n” method, is built on top of linear algebra.

(Why do I have such strong opinions on the subject? I’m a Bayesian statistician by trade; this is how I make my living.)

• Consciousness is the most recent module, and that does mean [that drawing causal arrows from consciousness to other modules of human mind design is ruled out, evolutionarily speaking.]

The causes of the fixation of a genotype in a population are distinct from the causal structures of the resulting phenotype instantiated in actual organisms.

• I don’t disagree with this. A lot of the kind of math Scott lacks is just rather complicated bookkeeping.

(Apropos of nothing, the work “bookkeeping” has the unusual property of containing three consecutive sets of doubled letters: oo,kk,ee.)

• I have the sort of math skills that Scott claims to lack. I lack his skill at writing, and I stand in awe (and envy) at how far Scott’s variety of intelligence takes him down the path of rationality. I currently believe that the sort of reasoning he does (which does require careful thinking) does not cluster with mathy things in intelligence-space.

• Scott’s technique for shredding papers’ conclusions seem to me to consist mostly of finding alternative stories that account for the data and that the authors have overlooked or downplayed. That’s not really a math thing, and it plays right to his strengths.

• I like it when I can just point folks to something I’ve already written.

The upshot is that there are two things going on here that interact to produce the shattering phenomenon. First, the notion of closeness permits some very pathological models to be considered close to sensible models. Second, the optimization to find the worst-case model close to the assumed model is done in a post-data way, not in prior expectation. So what you get is this: for any possible observed data and any model, there is a model “close” to the assumed one that predicts absolute disaster (or any result) just for that specific data set, and is otherwise well-behaved.

As the authors themselves put it:

The mechanism causing this “brittleness” has its origin in the fact that, in classical Bayesian Sensitivity Analysis, optimal bounds on posterior values are computed after the observation of the specific value of the data, and that the probability of observing the data under some feasible prior may be arbitrarily small… This data dependence of worst priors is inherent to this classical framework and the resulting brittleness under finite-information can be seen as an extreme occurrence of the dilation phenomenon (the fact that optimal bounds on prior values may become less precise after conditioning) observed in classical robust Bayesian inference.

• 31 Dec 2014 21:44 UTC
5 points

It’s a rather confusing way of referring to a “biased point of view”. Saying that “Person A has privilege” wrt. some issue is a claim that A’s overall observations and experiences are unrepresentative, and so she should rely on others’ experiences as much as on her own.

That’s not quite correct; I think it’s best to start with the concept of systematic oppression. Suppose for the sake of argument that some group of people is systematically oppressed, that is, on account of their group identity, the system in which they find themselves denies them access to markets, or subjects them to market power or physical violence, or vilifies them in the public sphere—you can provide your own examples. The privileged group is just the set complement of the oppressed group. An analogy: systematic oppression is the subject and privilege (in the SJ jargon sense) is the negative space.

The “biased point-of-view” thing follows as a near-corollary because it’s human nature to notice one’s oppression and to take one’s absence-of-oppression for granted as a kind of natural status quo, a background assumption.

Next question: in what way did Aaronson’s so-called wealthy white male privilege actually benefit him? To answer this, all we need to do is imagine, say, a similarly terrified poor black trans nerd learning to come out of their shell. Because I’ve chosen an extreme contrast, it’s pretty clear who would have the easier time of it and why. Once you can see it in high contrast, it’s pretty easy to relax the contrast and keep track of the relative benefits that privilege conveys.

• I’m a SSC fan and highly sympathetic to SJ goals and ideals. One of the core LW meetup members in my city can’t stand to read SSC on account of what he perceives to be constant bashing of SJ. (I’ve already checked and verified that his perception of the proportion of SJ bashing in SSC posts is a massive overestimate, probably caused by selection bias.) As a specific example of verbiage that he considers typical of SSC he cited:

And the people who talk about “Nice Guys” – and the people who enable them, praise them, and link to them – are blurring the already rather thin line between “feminism” and “literally Voldemort”.

When I read that line, I didn’t take it literally—in spite of the use of the word “literally”. I just kind of skipped over it. But after it was pointed out to me that I ought to take it literally, well… “frothing” is a pretty good description.

I remain a SSC fan, but I’m less likely to just blank out the meaning of these kinds of things now.

• Embarrassingly, I didn’t have the “who feeds Paris” realization until last year—well after I thought I had achieved a correct understanding of and appreciation for basic microeconomic thought.

• Same special-snowflake level credible limits, but for different reasons. Swimmer963 has an innate drive to seek out and destroy (whatever she judges to be) her personal inadequacies. She wasn’t very strategic about it in teenager-hood, but now she has the tools to wield it like a scalpel in the hands of a skilled surgeon. Since she seems to have decided that a standard NPC job is not for her, I predict she’ll become a PC shortly.

You’re already a PC; your strengths are a refusal to tolerate mediocrity in the long-term (or let us say, in the “indefinite” term, in multiple senses) and your vision for controlling and eradicating disease.