Should you try to do good work on LW?

I've been avoiding this thread so far because I'm kind of uncomfortable with compliments, but luckily it's descended into insults and I'm pretty okay with those.

Yes, I have a blog. I write blog posts much more often than I write Less Wrong posts (although they're much lower quality and scatterbrained in all senses of the word). Sometimes I want to say something about rationality, and since I happen to know of this site that's totally all about rationality with a readership hundreds of times greater than my blog, I post it here instead of (or in addition to) my blog. I promise you I didn't just add the PUA reference for "a Less Wrong audience"; in fact, knowing what I know all these months later, I would have specifically avoided even mentioning it for exactly the reason that's happening right now.

I have written about 150 posts for Less Wrong, and about 1200 in my blog. Of those, I can think of three that tangentially reference pick-up artistry as an example of something, and zero that are entirely about PUA or which express explicit support for it. According to my blog tagging system, three posts is slightly more than "cartography" or "fishmen" (two posts each), but still well below "demons" (fourteen posts). I don't think it's unreasonable to mention a movement with some really interesting psychology behind it about 50% more than I mention hypothetical half-man half-fish entities, or a quarter as often as I mention malevolent disembodied spirits.

More importantly, now that I'm talking to you...why is your username "private_messaging"?

Downvoted.

I hope I would downvote any comment containing the judgement-words "nonsense", "sociopathic" and "trash" (referring to a subset of the LW readership) regardless of the position being advocated. The book Non-violent Communication advises making observations and expressing feelings, but avoiding rendering judgments. A "judgement" can be defined as a phrase or statement that can be expected to diminish the status or moral standing of a person or group.

Parenthetically, it has been proposed that one of the ways online forums unravel over time is that a few people who like making strong judgments show up and get into long conversations with each other, which tends to discourage participants for whom the strong judgments distract from their reasons for participating.

What ever data on physiology nazis collected correctly, we are relying on today. Even when very bad guys collect data properly the data is usable. When it's on-line bragging by people fascinated with 'negs'... not so much. It is a required condition that data is badly collected; the guys trying to be sociopaths does not suffice.

It is very plausible [...] that we value internal states on the model, and we also receive negative reinforcement for model-world inconsistencies [...], resulting in learned preference not to lose correspondence between model and world

Generally correct; we learn to value good models, because they are more useful than bad models. We want rewards, therefore we want to have good models, therefore we are interested in the world out there. (For a reductionist, there must be a mechanism explaining why and how we care about the world.)

Technically, sometimes the most correct model is not the most rewarded model. For example it may be better to believe a lie and be socially rewarded by members of my tribe who share the belief, than to have a true belief that gets me killed by them. There may be other situations, not necessarily social, where the perfect knowledge is out of reach, and a better approximation may be in the "valley of bad rationality".

it is unnecessary to define the values over real world (the alternatives work fine for e.g. finding imaginary cures for imaginary diseases which we make match real diseases) [...] there's precisely the bit of AI architecture that has to be avoided.

In other words, make an AI that only cares about what is inside the box, and it will not try to get out of the box.

That assumes that you will feed the AI all the necessary data, and verify that the data is correct and complete, because the AI will be just as happy with any kind of data. If you give an incorrect information to AI, the AI will not care about it, because it has no definition of "incorrect"; even in situations where AI is smarter than you and could have noticed an error that you didn't notice. In other words, you are responsible for giving AI the correct model, and the AI will not help you with this, because AI does not care about correctness of the model.