I am currently a nuclear engineer with a focus in nuclear plant safety and probabilistic risk assessment. I am also an aspiring EA, interested in X-risk mitigation and the intersection of science and policy.

My thoughts on assorted stuff from the web:

ErickBall's Comments

How to Identify an Immoral Maze

One factor is that the military has a pretty consistent policy of moving officers around to different postings every few years. You never work with the same people very long, except maybe at the very top. This might help enable some of the outrunning-your-mistakes phenomenon mentioned above, but it also probably means you can't develop the kind of interpersonal politics you might see in a big corporation.

human psycholinguists: a critical appraisal

Wait, why is it impossible for a fully-connected network trained by backpropagation to generalize across unseen input and output nodes? Is this supposed to be obvious?

human psycholinguists: a critical appraisal
If compositionality is necessary, then this sort of “deep learning” implements compositionality, even if this fact is not superficially obvious from its structure. 

But compositionality mostly isn't necessary for the kind of writing GPT-2 does. Try getting it to tell you how many legs a dog has. One? Three? Five? It doesn't know, because people rarely write things like "a dog has four legs" in its input data. Here's GPT-2:

A dog has the same number of legs as  a man, but has fewer legs than a gorilla.  It has a lot of brains, but they are divided equally between the two front legs. 

It's very good at coming up with sentences that are grammatically and stylistically correct, but it has no concept of whether they're true. Now, maybe that's just a result of interacting exclusively with language--people generally learn how many legs a dog has by looking at one, not by hearing about them. But even when it comes to purely linguistic issues, it basically doesn't make true statements. This is typified by its habit of contradicting itself (or repeating itself) within the same sentence:

A convincing argument requires certain objects to exist. Otherwise it's not really science. For instance, according to Stromberg, all the atoms in a dog's body exist, and the image of the dog, even though it does not exist, exists (p. 120).
Operationalizing Newcomb's Problem

I actually think if you're new to the idea of logical decision theory, Newcomb's problem is not the best place to start. The Twin Prisoner's Dilemma is much more intuitive and makes the same basic point: that there are situations where your choice of thought process can help to determine the world you find yourself in--that making decisions in a dualist framework (one that assumes your thoughts affect the world only through your actions) can sometimes be leaving out important information.

Operationalizing Newcomb's Problem

I guess if you ran this experiment for real, any answer along the lines of "I don't know whether I'll stay" would have to result in getting $10.

Operationalizing Newcomb's Problem

Sorry if that was unclear--I meant that the lie detector has 10% false positives, so those people were telling the truth when they said they would stay, but got the $10 anyway because the lie detector thought they were lying.

Epistemic Spot Check: Fatigue and the Central Governor Module

Levine's comments seem to be a bit of a strawman of Noakes' position... though, based on your second quote, he may also be a strawman of himself.

A subject can elect to simply stop exercising on the treadmill while walking slowly because they don’t want to continue; no mystical ‘central governor’ is required to hypothesize or predict a VO2 below maximal achievable oxygen transport in this case.

Whether sub-maximal oxygen transport ever occurs is entirely beside the point; the implication of the central governor model would be that maximal oxygen transport (or maximal muscle contraction, or whatever) occurs only under extreme circumstances, because the brain subconsciously detects potential for damage to the body and reduces exercise effort. A VO2 max is generally determined by running some exercise test "until exhaustion", with no mechanism in place for knowing how hard the athlete is trying. Presumably the only motivation is "this doctor just told me to keep going until I'm tired" or maybe "I want a good test score for bragging rights". It's definitely not "baby trapped under the car". In this situation the evidence for Noakes' hypothesis would be something like, measure VO2 max again while being chased by a bear (or during some kind of competition, if the IRB doesn't like the bear thing) and it should be higher the second time. If you can improve performance through increased motivation, up to the highest levels of motivation you're willing/able to measure, then common sense would say you still probably haven't reached the actual "maximum". Anecdotally, in at least one instance of extreme motivation I've been able to cycle so hard that in a period of about 30 seconds I gave myself a nasty cough lasting several days; I am unable to repeat this under normal circumstances.

Whether the performance limitation occurs primarily through pain or whether there's also some kind of hard limit is unclear. Limitation of exercise performance by fatigue is familiar to anyone who's tried running a mile in gym class. On the other hand, I've read that major league pitchers are often limited in pitching speed by the stress on their elbow ligaments, rather than by the ability of the muscles to contract harder. If true that means the brain is detecting potentially injurious muscle contractions and putting a damper on them, but without necessarily causing pain.

(Reinventing wheels) Maybe our world has become more people-shaped.

But we have no problem observing causality in nature as well as in man-made environments. It seems like human culture has not so much made the world friendly to human concepts of causality, rather it has built up a standard set of human-friendly abstractions that are selected for their ability to fit causal models onto a complex world. There are lots of parts of the world where causality exists but is not observable through abstractions (e.g. butterfly effects). We generally ignore these.

Can you eliminate memetic scarcity, instead of fighting?

Interesting. I like the idea here of having reusable patterns of problem-solving across diverse engineered physical systems. It reminds of the idea of software patterns. I'm actually kind of disappointed that this was never taught in any of my engineering classes, especially given Wikipedia's big list of organizations that use it (including Samsung, GE, Boeing, NASA, HP, Intel, and a bunch of others). Now I'm excited to read about some case studies!

If you have any examples of how you've used it, I'd love to hear about those too.

Matthew Walker's "Why We Sleep" Is Riddled with Scientific and Factual Errors

Yes, this just-so-story is suspicious, especially because it's not "just so"--if there were such strong selection for variability, wouldn't you expect full coverage of the night? Some people could go to bed at four and others could wake up at three. As far as I know this does not generally happen (in the absence of electric lighting) and hence the dangers of having everybody asleep at once must be manageable.

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