trentmkelly/LessWrong-43k huggingface dataset:
Map and territory: Natural structures
by casebash — 2017-08-01T13:53:29.532Z

This will be a very short post which simply defines one term which I find useful when discussing the map and the territory.

I find it very useful to have a term that helps clarify that the map is not completely arbitrary and that there are things in the territory that are natural candidates for appearing in the map. For example, for the Ship of Thesus, one natural candidate is the pure, original, unmodified ship; another are the fixed percentages (ie. 50% original); another would be a continuity based measure. If you are asked to create a definition of what counts as the Ship of Thesus, these are some of the first ideas that you would come up with, although you would of course need to define it in much, much more detail to get all the way down to the level of the territory.
Or suppose you are trying to define what is meant by table. Again, the definition is purely arbitrary and whatever you choose, but there are certain natural structures in reality that pop out at you. One might be all four-legged, non-living objects with a flat top, another might relax the four-legged requirement so that it only required four legs at one particular time, ect.

When I'm explaining that a particular concept has been reified, it greatly clarifies my position to explain that I don't believe that the concept is empty, but there is *something* behind it that leads us to want that word. That something is really not a single thing (or else it would be real, not reified), but a collection of closely related 'natural structures'. Each of the definitions provided for the Ship of Thesus or a table corresponds to a different natural structure, while the term itself appears in the map. I hope you find this word useful too, but if you have any suggestions for a better term, please mention it in the comments.
August 2017 Media Thread
by ArisKatsaris — 2017-08-01T08:16:26.369Z

This is the monthly thread for posting media of various types that you've found that you enjoy. Post what you're reading, listening to, watching, and your opinion of it. Post recommendations to blogs. Post whatever media you feel like discussing! To see previous recommendations, check out the older threads.

Rules:

Please avoid downvoting recommendations just because you don't personally like the recommended material; remember that liking is a two-place word. If you can point out a specific flaw in a person's recommendation, consider posting a comment to that effect.

If you want to post something that (you know) has been recommended before, but have another recommendation to add, please link to the original, so that the reader has both recommendations.

Please post only under one of the already created subthreads, and never directly under the parent media thread.

Use the "Other Media" thread if you believe the piece of media you want to discuss doesn't fit under any of the established categories.

Use the "Meta" thread if you want to discuss about the monthly media thread itself (e.g. to propose adding/removing/splitting/merging subthreads, or to discuss the type of content properly belonging to each subthread) or for any other question or issue you may have about the thread or the rules.
Open thread, July 31 - August 6, 2017
by Thomas — 2017-07-31T14:41:09.485Z

If it's worth saying, but not worth its own post, then it goes here.

Notes for future OT posters:

1. Please add the 'open_thread' tag.

2. Check if there is an active Open Thread before posting a new one. (Immediately before; refresh the list-of-threads page before posting.)

3. Open Threads should start on Monday, and end on Sunday.

4. Unflag the two options "Notify me of new top level comments on this article" and "Make this post available under..." before submitting
Models of human relationships - tools to understand people
by Elo — 2017-07-29T03:31:25.612Z

This post will not teach you the models here. This post is a summary of the models that I carry in my head. I have written most of the descriptions without looking them up (See Feynman notebook method). If you have read a book on every one of these points they will make sense, as if you were shaking hands with an old acquaintance. If you are seeing them for the first time, they won't make very much sense or they will feel like a surface trivial truth.

I can't make you read all the books but maybe I can offer you that the answer to social problems is surprisingly simple. After reading enough books you start to see the overlap and realise they often are trying to talk about the same thing. (i.e. NVC + Gottman go together well).

In fact if you were several independent dragon hunters trying to model an invisible beast and all of various people's homemade sensors kept going "ping" at similar events you would probably start to agree you were chasing the same monster. Models should start to agree when they are talking about the same thing. The variety of models should make it easier for different minds to connect to different parts of the answer.

All models are wrong, some models are useful. Try to look at where the models converge. That's where I find the truth.

1. The book Crucial Confrontations - Kerry Patterson

http://www.wikisummaries.org/wiki/Crucial_Conversations:_Tools_for_Talking_When_Stakes_are_High
(without explaining how) If you can navigate to a place of safety in a conversation you can say pretty much anything. Which is not to say "here is how to be a jerk" but if you know something is going to come across negative you can first make sure to be in a positive/agreeable/supportive conversation before raising the hard thing.

In the middle of a yelling match is maybe not the best time to bring up something that has bugged you for years. However a few sentences about growth mindset, supporting people being a better person and trying to help (and getting a feel that the person is ready to hear the thing) and you could tell anyone they are a lazy bum who needs to shape up or ship out.

The conversation needs to be safe. For example - "I want to help you as a person and I know how hard it can be to get feedback from other people and I want to make you into a better person. I have a...
Sleeping Beauty Problem Can Be Explained by Perspective Disagreement (IV)
by Xianda_GAO_duplicate0.5321505782395719 — 2017-07-26T01:01:17.679Z

This is the final part of my argument. Previous parts can be found here: I, II, III. To understand the following part I should be read at least. Here I would argue against SSA, argue why double-halving is correct, and touch on the implication of perspective disagreement on related topics such as the Doomsday Argument, the Presumptuous Philosopher and the Simulation Argument.

ARGUMENTS AGAINST SELF-SAMPLING ASSUMPTION

I think the most convincing argument against SSA was presented by Elga in 2000 （although he intended it as an counter to halving in general). He purpose the coin toss could happen after the first awakening. Beauty’s answer ought to remain the same regardless the timing of the toss. As SSA states, an observer should reason as if she is randomly selected from the set of all actual observers (past, present and future ones). If an imaginary selector randomly choose a day among all waking day(s) he is guaranteed to pick Monday if the coin landed on H but only has half the chance if T. From the selector’s perspective clearly a bayesian updating should be performed upon learning it is Monday. A simple calculation tells us his credence of H must be 2/3. As SSA dictates this is also beauty’s answer once she knows it is Monday. However the coin toss could potential happen after this awakening. Now beauty is predicting a fair coin toss yet to happen would most likely land on H. This supernatural predicting power is a conclusive evidence against SSA.

However, if we recognize the importance of perspective disagreement then beauty is not bound to give the same answer as the Selector. In fact I would argue she should not perform a bayesian update base on the new information. This can be explained in two ways.

One way is to put the new information into the frequentist approach mentioned in part I. In Duplicating Beauties, when a beauty wakes up and remembering 1000 repetitions she shall reason there are about 500 of H and T each among those 1000 tosses. The same conclusion would be reached by all beauties without knowing if she is physically the original or created somewhere along the way. Now suppose a beauty learns she is indeed the original. She would simply reason as the original beauty who wakes up remembering 1000 tosses. These 1000 tosses would still contain about 500 of H and T each. Meaning her answer shall remain at 1/2.&nb...
What Are The Chances of Actually Achieving FAI?
by Bound_up — 2017-07-25T20:57:19.395Z

I get that the shut up and multiply calculation will make it worth trying even if the odds are really low, but my emotions don't respond very well to low odds.

I can override that to some degree, but, at the end of the day, it'd be easier if the odds were actually pretty decent.

Comment or PM me, it's not something I've heard much about.
People don't have beliefs any more than they have goals: Beliefs As Body Language
by Bound_up — 2017-07-25T17:41:21.764Z

Many people, anyway.

There is a common mistake in modeling humans, to think that they have actual goals, and that they deduce their actions from those goals. First there is a goal, then there is an action which is born from the goal. This is wrong.

More accurately, humans have a series of adaptations they execute. A series of behaviors which, under certain circumstances, kinda-sorta-maybe aim at the same-ish thing (like inclusive genetic fitness), but which will be executed regardless of whether or not they actually hit that thing.

Actions are not deduced from goals. The closest thing we have to "goals" are inferred from a messy conglomerate of actions, and are only an approximation of the reality that is there: just a group of behaviors.

-

I've come to see beliefs as very much the same way. Maybe some of us have real beliefs, real models. Some of us may in fact choose our statements about the world by deducing them from a foundational set of beliefs.

The mistake is repeated when we model most humans as having actual beliefs (nerds might be an exception). To suppose that their statements about reality, their propositions about the world, or their answers to questions are deduced from some foundational belief. First there is a belief, then there is a report on that belief, provided if anyone inquires about the belief they're carrying around. This is wrong.

More accurately, humans have a set of social moves/responses that they execute. Some of those moves APPEAR (to the naive nerd such as I) to be statements about how and what reality is. Each of these "statements" was probably vetted and accepted individually, without any consideration for the utterly foreign notion that the moves should be consistent or avoid contradiction. This sounds as tiresome to them as suggesting that their body language, or dance moves should be "consistent," for to them, the body language, dance moves, and "statements about reality" all belong to the same group of social moves, and thinking a social move is "consistent" is like thinking a certain posture/gesture is consistent or a color is tasty.

And missing the point like a nerd and taking things "literally" is exactly the kind of thing that reveals low social acuity.

Statements about individual beliefs are not deduced from a model of the world, just like actions are not deduced from goals. You can choose to interpret "I think we shoul...
Bayesian statistics as epistemic advantage
by Dr_Manhattan — 2017-07-25T17:07:49.660Z

Interesting Talking Machines episode quote about Bayesian stats being used at Bletchley and GCHQ (its successor). Seems like they held on to a possibly significant advantage (crypto ppl would be better to comment on this) for years, owing largely to Turing. (The rest of the episode is about AI safety and also interesting.)

Source:

http://www.thetalkingmachines.com/blog/2016/2/26/ai-safety-and-the-legacy-of-bletchley-park

GCHQ in the ’70s, we thought of ourselves as completely Bayesian statisticians. All our data analysis was completely Bayesian, and that was a direct inheritance from Alan Turing. I’m not sure this has ever really been published, but Turing, almost as a sideline during his cryptoanalytic work, reinvented Bayesian statistics for himself. The work against Enigma and other German ciphers was fully Bayesian. …

Bayesian statistics was an extreme minority discipline in the ’70s. In academia, I only really know of two people who were working majorly in the field, Jimmy Savage … in the States and Dennis Lindley in Britain. And they were regarded as fringe figures in the statistics community. It’s extremely different now. The reason is that Bayesian statistics works. So eventually truth win out. There are many, many problems where Bayesian methods are obviously the right thing to do. But in the ’70s we understood that already in Britain in the classified environment.

Transcription Source:

https://www.johndcook.com/blog/2017/07/25/bayesian-methods-at-bletchley-park/
Steelmanning as an alternative to Rationalist Taboo
by cousin_it — 2017-07-25T16:27:11.233Z

The problem with Rationalist Taboo is that it was invented to make others clarify their thoughts, not to clarify your own.

Here's how it usually goes wrong: "You can't explain the color red to me? Hahaha, I've dissolved the idea of qualia! They are just an illusion!" No, silly, your opponent's failure to define X doesn't prove you right about X. You're just turning yourself into a person who declares all hard-to-define ideas illusory in order to stop thinking. Is that what you really want?

Focusing on the meanings behind words is a great idea and I'm happy that we have it in this community. But asserting that a word is useless should only be done with caution! Even misguided words still come from a millennia-long optimization process, like butterflies, and there are secrets to learn from the swirls on their wings. To that end, instead of Rationalist Taboo, I prefer to use good old steelmanning:

Alice: Can you explain what you mean by "surprise"?

Bob and Carol in unison: Observing a low probability event.

Alice: This morning I saw a car whose license plate said 8713, but it didn't surprise me at all!

Bob: Hmm, it looks like my concept of "surprise" was misguided. I won't use the word from now on.

Carol: Hold on. The word "surprise" might lead to some other nontrivial concept that's useful in its own right. Maybe it's about description length? Or logical uncertainty? I'll try to formalize...

Carol wins the exchange, because Bob dissolved a word prematurely and gave up the chance to think an interesting thought. These days I try to be more like Carol, and when I hear a seemingly misguided word like "essence" or "emergence", my first instinct isn't to kick it when it's down, but to steelman it and rescue whatever is worth rescuing.

What Taboo gets right is that words are mere handles, and meanings are the only part worth discussing; but when you try to capture a word, there will always be leftover meanings, often more complex and interesting than the one you caught. That's what Taboo gets wrong.
Complexity Is Bad
by Zvi — 2017-07-25T12:00:14.000Z

Previously: Choices are Bad, Change Is Bad

Meta Note: Early drafts were too complex. Complexity is Bad. I simplified.

Mark Rosewater, head of design at Magic: The Gathering who I recently praised for writing down his process, has a podcast called Drive to Work. Commuting is really bad (citation not needed), so recording a podcast is a great idea. Usually it is a great geek out, but incomprehensible to non-players.

The recent episode on complexity is an exception. No game knowledge is needed and the insights transfer to life in general. He is explaining how to think about complexity. The central point is: Complexity is Bad.

It is known that Complexity is Bad, but it is important that your model of this is made of gears. To help with this, I will summarize his most important points, and add some more of my own.

People can only have so much attention.

People can only store so much information at once, typically seven things.

People can only think about so many things at once, typically three things.

If people have too many things to remember, do or think about, bad things happen.

Often they will have to prioritize, and will often prioritize wrong. They will distill the situation, or your argument, to make it simpler, whether you like it or not, in ways you can’t predict or control.

Often they will throw up their hands and give up, doing nothing or doing something at random.

Other times complexity is a barrier to entry and people won’t understand or engage with you at all.

Complexity often papers over mistakes, preventing you from finding better, more elegant solutions. You are patching bad outputs rather than fixing your underlying process.

More complex systems are harder to analyze and understand. They are more fragile and have more points of failure. They are harder to usefully change, especially without adding more complexity.

Even in the best case, complex things take longer and more concentration to engage with.

The more complex something is, the higher the standards it is judged by, since you had more choices and anyone interacting with it likely has more choices.

In exchange, complexity lets you do more complex things, have whatever you are building or rules you are making achieve more complex outcomes, and to better understand and explain things that are complex, which is most things. Complexity is highly useful.

Albert Einstein summarized this as ...
Epistemological Implications of a Reduction of Theoretical Implausibility to Cognitive Dissonance
by common_law — 2017-07-25T01:29:32.006Z

The Aronsonian re-interpretation of cognitive dissonance as caused by ideas in conflict with self-image forestalled some obvious applications to philosophical issues lying at the border with psychology. As the action-oriented approach suggests, when Festinger's theory is deepened to pertain to the relations between far-mode and near-mode representations, the similarity between cognitive dissonance and theoretical plausibility becomes almost obvious. Implausibility has the same properties and role as cognitive dissonance. It is an aversive state that that can motivate a change in far-mode beliefs, and the change is toward a form of coherence among beliefs. Rival theories can be rated on a single dimension of plausibility in the same way that they evoke different degrees of dissonance.

The reduction of implausibility to cognitive dissonance bears significant philosophical weight. It denies both Bayesian and coherentist theories of knowledge. The fashionable Bayesian interpretation of implausibility is in terms of degrees of rational belief. A theory is implausible according to the Bayesian School when it possesses a low a priori probability. But we don't thereby scale our beliefs for rationality if we scale beliefs by how much dissonance they cause,. Moreover, to scale them by rationality would require that we have some independent reason for thinking, apart from the comparative cognitive dissonance they arouse, that one theory is more rational than is the other. Scaling our beliefs by the cognitive dissonance they arouse cannot itself be justified on a priori grounds, since dissonance reduction often takes us systematically away from the truth, as in fact is the case in most experimental studies of dissonance. (This helps explain why the identity of dissonance and implausibility hasn't previously been noted.)

Regarding the other negative implication of the dissonance account of implausibility - coherentist theories of knowledge haven't arrived at a clear meaning of "coherence," but coherentist theories emphasize logical and explanatory relations among far-mode ideas (although recent versions have included the role of ideas derived directly from perception). The dissonance theory of implausibility holds that dissonance is aroused by pragmatic incompatibility between near-mode and far-mode cognition. However, we don't seem to be immune to conflicts

...
Bi-Weekly Rational Feed
by sapphire — 2017-07-24T21:56:46.003Z

===Highly Recommended Articles:

Superintelligence Risk Project Update II by Jeff Kaufman - Jeff's thoughts and the sources he found most useful. Project is wrapping up in a few day. Topics: Technical Distance to AI. Most plausible scenarios of Superintelligence risk. OpenPhil's notes on how progress was potentially stalled in Cryonics and Nanotech.

Superintelligence Risk Project Update by Jeff Kaufman - Links to the three most informative readings on AI risk. Details on the large number of people Jeff has talked to. Three fundamental points of view on AI-Safety. Three Fundamental points of disagreement. An update on the original questions Jeff was trying to answer.

Podcast The World Needs Ai Researchers Heres How To Become One by 80,000 Hours - "OpenAI’s latest plans and research progress. Concrete Papers in AI Safety, which outlines five specific ways machine learning algorithms can act in dangerous ways their designers don’t intend - something OpenAI has to work to avoid. How listeners can best go about pursuing a career in machine learning and AI development themselves."

Radical Book Club The Decentralized Left by davidzhines (Status 451) - The nature of leftwing organizing and what righties can learn from it. An exposition of multiple books on radical left organization building. Major themes are "doing the work" and "decentralized leadership".

Study Of The Week To Remediate Or Not To Remediate by Freddie deBoer - Should low math proficiency students take remedial algebra or credit bearing statistics. The City University of New York ran an actual randomized study to test this. The study had pretty good controls. For example students were randomly assigned to three groups, participating professors taught one section of each group.

Kenneth Arrow On The Welfare Economics Of Medical Care A Critical Assessment by Artir (Nintil) - "Kenneth Arrow wrote a paper in 1963, Uncertainty and the Welfare Economics of Medical Care. This paper tends to appear in debates regarding whether healthcare can be left to the market (like bread), or if it should feature heavy state involvement. Here I explain what the paper says, and to what extent it is true."

Becoming Stronger Together by b4yes (lesswrong) - "About a year ago, a secret rationalist group was founded. This is a report of what the group did during that year."

The De

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