trentmkelly/LessWrong-43k huggingface dataset:
More art, less stink: Taking the PU out of PUA
by XFrequentist — 2010-09-10T00:25:59.829Z

Overview: This is a proposal for a LessWrong Pick Up Artist (PUA)-like sub-community; PUA without the PU (get it?)1. Members would focus on the deliberate practice of social artistry, but with non-mating goals. Origins and intent of the goal are discussed, possible topics for learning are listed, and suggestions for next steps are solicited.

Origins:

The PUA Community began decades ago with men that wanted to learn how to get better at seducing women. As I understand it, they simply began posting their (initially) awkward attempts at love online. Over the years, they appear to have amassed a fairly impressive set of practical knowledge and skills in this domain.

I admire and applaud this effort. However, my ability to meet women is not currently a limiting factor in my life satisfaction. In reading some of the PUA literature, I was struck how often different authors remarked on the unintended side benefits of their training: better relationships at work, better interviewing skills, more effective negotiations, more non-pickup social fun, better male friendships, more confidence, etc. These guys were able to make major strides in areas that I've struggled to improve at all in... without even bloody intending to! This struck me as an something worth taking very seriously!

I find it alarming that such a valuable resource would be monopolized in pursuit of orgasm; it's rather as if a planet were to burn up its hydrocarbons instead of using them to make useful polymers. PUA ought to be a special case of a more general skill set, and it's being wasted. I say that my goals are noble, and as such I should have the opportunity to sharpen my skills to at least the keenness of a PUA master!

Statement of Purpose:

The purpose of this post is to open discussion on how to construct a community of developing social artisans, modeled after the useful components2 of the PUA community. If there is sufficient mass, the next goals are probably sussing out learning methods and logistics.

The mission of the hypothetical community will probably need to be fleshed out more explicitly (and I don't want to be too prescriptive), but pretty much what I was thinking was expressed well by Scott Adams:

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I think technical people, and engineers in particular, will always have good job prospects. But what if you don't have the aptitude or personality to follow a technical p

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Reason is not the only means of overcoming bias
by multifoliaterose — 2010-09-09T22:59:58.922Z

Sometimes the best way to overcome bias is through an emotional appeal. Below I interweave discussion of how emotional appeals can be used to overcome the bias corresponding to the identifiable victim effect and maladaptive resource hoarding instinct.

The beginning of the abstract to Paul Slovic's article "If I look at the mass I will never act”: Psychic numbing and genocide reads

Most people are caring and will exert great effort to rescue individual victims whose needy plight comes to their
attention. These same good people, however, often become numbly indifferent to the plight of individuals who are “one of many” in a much greater problem.

Eliezer has discussed this and related topics extensively, for example in Scope Insensitivity. See also the references listed at wikipedia under identifiable victim effect. How can we go about overcoming this bias? One answer is "by keeping it in mind and by teaching people about it." But while some people have the intellectual interest and ability to learn about the identifiable victim effect, others don't. Moreover, it's not clear that being aware of this bias is by itself very useful in overcoming it.

But reason is not the only means of overcoming bias.

Before I proceed I should make some disclaimers:

Disclaimer #1: Below I discuss overcoming biases that people have against donating money for the purpose of improving health in the developing world. In doing so I am not advocating in favor of developing world aid over other forms of charity. The case of developing world aid simply provides a good example. Most people who decline to donate to charities that improve health in the developing world do not decline to do so because they think they have a better cause to donate to.

Disclaimer #2: This posting is intended to advocate the use of emotional appeals specifically for the purpose of overcoming bias. Obviously emotional appeals can and are frequently used to create bias - this is not what I'm advocating. I believe that the video which I discuss below does more to overcome bias than it does to create bias for the typical viewer

Disclaimer #3: The use of emotional appeals strikes some as patronizing or manipulative. I do not view them in this light when they are used for the sake of aligning people's behavior with their values for the sake of good causes. I subject myself to stimuli with emotional ...
My plans
by KatjaGrace — 2010-09-09T14:19:50.000Z

I’m currently expanding my post on the Self Indication Assumption and the Great Filter into an honours thesis, due at the end of October. So barring bouts of procrastination or especially hard work deserving of blogging rights, I will probably remain fairly quiet till then. In the mean time, if you have any opinions on what career or the like I would be relatively good at, or anything else relevant to what I should do upon my impending graduation other than do a dance and read all those books I meant to before saving the world in some yet to be fully worked out fashion, please tell me here.
Humans are not automatically strategic
by AnnaSalamon — 2010-09-08T07:02:52.260Z

Reply to: A "Failure to Evaluate Return-on-Time" Fallacy

Lionhearted writes:

[A] large majority of otherwise smart people spend time doing semi-productive things, when there are massively productive opportunities untapped.

A somewhat silly example: Let's say someone aspires to be a comedian, the best comedian ever, and to make a living doing comedy. He wants nothing else, it is his purpose. And he decides that in order to become a better comedian, he will watch re-runs of the old television cartoon 'Garfield and Friends' that was on TV from 1988 to 1995....

I’m curious as to why.

Why will a randomly chosen eight-year-old fail a calculus test? Because most possible answers are wrong, and there is no force to guide him to the correct answers. (There is no need to postulate a “fear of success”; most ways writing or not writing on a calculus test constitute failure, and so people, and rocks, fail calculus tests by default.)

Why do most of us, most of the time, choose to "pursue our goals" through routes that are far less effective than the routes we could find if we tried?[1] My guess is that here, as with the calculus test, the main problem is that most courses of action are extremely ineffective, and that there has been no strong evolutionary or cultural force sufficient to focus us on the very narrow behavior patterns that would actually be effective.

To be more specific: there are clearly at least some limited senses in which we have goals. We: (1) tell ourselves and others stories of how we’re aiming for various “goals”; (2) search out modes of activity that are consistent with the role, and goal-seeking, that we see ourselves as doing (“learning math”; “becoming a comedian”; “being a good parent”); and sometimes even (3) feel glad or disappointed when we do/don’t achieve our “goals”.

But there are clearly also heuristics that would be useful to goal-achievement (or that would be part of what it means to “have goals” at all) that we do not automatically carry out. We do not automatically:

(a) Ask ourselves what we’re trying to achieve;

(b) Ask ourselves how we could tell if we achieved it (“what does it look like to be a good comedian?”) and how we can track progress;

(c) Find ourselves str

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September Less Wrong Meetup aka Eliezer's Bayesian Birthday Bash
by Jasen — 2010-09-08T04:51:31.686Z

In honor of Eliezer's Birthday, there will be a Less Wrong meetup at 5:00PM this Saturday, the 11th of September, at the SIAI Visiting Fellows house (3755 Benton St, Santa Clara CA). Come meet Eliezer and your fellow Less Wrong / Overcoming Bias members, have cool conversations, eat good food and plentiful snacks (including birthday cake of course!), and scheme out ways to make the world more Bayesian.

As usual, the meet-up will be party-like and full of small group conversations. Rationality games may also be present. Newcomers are welcome. Feel free to bring food to share, or not.

Please RSVP at the meetup.com page if you plan to attend.

Sorry for the last minute notice, I just found out that the 11th was Eliezer's birthday today.
A "Failure to Evaluate Return-on-Time" Fallacy
by lionhearted (Sebastian Marshall) — 2010-09-07T19:01:42.066Z

I don't have a good name for this fallacy, but I hope to work it out with everyone here through thinking and discussion.

It goes like this: a large majority of otherwise smart people spend time doing semi-productive things, when there are massively productive opportunities untapped.

A somewhat silly example: Let's say someone aspires to be a comedian, the best comedian ever, and to make a living doing comedy. He wants nothing else, it is his purpose. And he decides that in order to become a better comedian, he will watch re-runs of the old television cartoon 'Garfield and Friends' that was on TV from 1988 to 1995.

This is absolutely not a great use of his time. Maybe he'll learn a little about jokes structures and pick up a gag from the show. It's probably not entirely useless. But Garfield and Friends wasn't all that funny to begin with, and there's only so much to be learned from it. The would-be comedian would be much better off watching Eddie Murphy, George Carlin, and Bill Cosby if he wanted to watch old clips. He'd be much better off reading memoirs, autobiographies, and articles by people like Steve Martin and Jerry Seinfeld. Or he could look to get into the technical aspects of comedy and study well-respected books in the field. Or best yet, go to an open mic night, or spend time writing jokes, or otherwise do comedy. But he doesn't, instead he just watches re-runs of Garfield and Friends.

I think a lot of us are guilty of this in our daily lives. Certainly, most people on LessWrong examine our lives more carefully than the rest of the world. A lot of us have clear goals. Maybe not a full, cohesive belief structure, but pretty clear. And sometimes we dabble around and do low-impact stuff instead of high impact stuff. The equivalent of watching Garfield and Friends re-runs.

I've been an entrepreneur and done some entrepreneurial stuff. In the beginning, you have to test different things, because you don't know what's going to work. But I've seen this fallacy, and I was guilty of it myself - I didn't double down and put all my efforts into what was working, or at least commit mostly to it.

The most successful entrepreneurs do. Oh, keep learning, and diversify a bit, sure. But I remember watching a talk about the success of the company Omniture - they had two people in their enterprise business-to-business side, and 60 people in their business-to-consume...
Something's Wrong
by  — 2010-09-05T18:08:54.268Z

Atheists trying to justify themselves often find themselves asked to replace religion. “If there’s no God, what’s your system of morality?” “How did the Universe begin?” “How do you explain the existence of eyes?” “How do you find meaning in life?” And the poor atheist, after one question too many, is forced to say “I don’t know.” After all, he’s not a philosopher, cosmologist, psychologist, and evolutionary biologist rolled into one. And even they don’t have all the answers.

But the atheist, if he retains his composure, can say, “I don’t know, but so what? There’s still something that doesn’t make sense about what you learned in Sunday school. There’s still something wrong with your religion. The fact that I don’t know everything won’t make the problem go away.”

What I want to emphasize here, even though it may be elementary, is that it can be valuable and accurate to say something’s wrong even when you don’t have a full solution or a replacement.

Consider political radicals. Marxists, libertarians, anarchists, greens, John Birchers. Radicals are diverse in their political theories, but they have one critical commonality: they think something’s wrong with the status quo. And that means, in practice, that different kinds of radicals sometimes sound similar, because they’re the ones who criticize the current practices of the current government and society. And it’s in criticizing that radicals make the strongest arguments, I think. They’re sketchy and vague in designing their utopias, but they have moral and evidentiary force when they say that something’s wrong with the criminal justice system, something’s wrong with the economy, something’s wrong with the legislative process.

Moderates, who are invested in the status quo, tend to simply not notice problems, and to dismiss radicals for not having well-thought-out solutions. But it’s better to know that a problem exists than to not know – regardless of whether you have a solution at the moment.

Most people, confronted with a problem they can’t solve, say “We just have to live with it,&rdquo

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Controlling Constant Programs
by Vladimir_Nesov — 2010-09-05T13:45:47.759Z

This post explains the sense in which UDT and its descendants can control programs with no parameters, without using explicit control variables.

Related to: Towards a New Decision Theory, What a reduction of "could" could look like.

Usually, a control problem is given by an explicit (functional) dependence of outcome on control variables (together with a cost function over the possible outcomes). Solution then consists in finding the values of control variables that lead to the optimal outcome. On the face of it, if we are given no control variables, or no explicit dependence of the outcome on control variables, then the problem is meaningless and cannot be solved.

Consider what is being controlled in UDT and in the model of control described by Vladimir Slepnev. It might be counterintuitive, but in both cases the agent controls constant programs, in other words programs without explicit parameters. And for constant programs, their output is completely determined by their code, nothing else.

Let's take, for example, Vladimir Slepnev's model of Newcomb's problem, written as follows:

def world():
box1 = 1000
box2 = (agent() == 2) ? 0 : 1000000
return box2 + ((agent() == 2) ? box1 : 0)

The control problem that the agent faces is to optimize the output of program world() that has no parameters. It might be tempting to say that there is a parameter, namely the sites where agent() is included in the program, but it's not really so: all these entries can be substituted with the code of program agent() (which is also a constant program), at which point there remains no one element in the program world() that can be called a control variable.

To make this point more explicit, consider the following variant of program world():

def world2():
box1 = 1000
box2 = (agent2() == 2) ? 0 : 1000000
return box2 + ((agent() == 2) ? box1 : 0)

Here, agent2() is a constant program used to predict agent's decision, that is known to compute the same output as agent(), but does not, generally, resemble agent() in any other way. If we try to consider only the explicit entry of program agent() as control variable (either by seeing the explicit program call in this representation of world2(), or by matching the code of agent() if its code was substituted for the call), we'll end up with an incorrect understanding of the situation, where the agent is on...
Reasonably Fun
by JohnDavidBustard — 2010-09-04T12:07:51.113Z

Fun on the whole is a pretty amorphous concept and being reasonable about it is tricky, however there are some routes of enquiry.

My personal understanding of fun comes from the experience of programming gameplay mechanics (such as character control, AI and minigames) and through designing and pitching games professionally. This has led me to create a number of theories about why games (and other forms of entertainment) are fun.

These ideas are built on my experiences of adjusting games and game pitches to make them more enjoyable. On the whole this sense of enjoyment is based on the opinions of those making (or paying for the development of) the games (where groupthink is a problem). However, many of the games and their pitches have been evaluated by focus groups and gameplay recordings, performed in relatively controlled settings. Additional information comes from finding patterns in sales figures and other representations of what people enjoy (e.g. the types of magazine available for sale in newsagents).

From these experiences I've attempted to find simple theoretical justifications for the behaviour I've observed. In some cases, these theories have some validation through external research, but on the whole are not experimentally validated. I take the view that it is better to have some sort of theory rather than nothing, and indeed these theories have been very useful in guiding my work.

These ideas will focus on the fun (or more generally the source of motivation) provided by computer games however I believe there are many generalities that can be made from them.

When thinking about the experience of a game I find it useful to break the game experience into 4 distinct stages:

Attract

Engage

Reward

Addict

To keep the article short I've decided to split these stages up over multiple articles, hopefully there is enough meat in each to be interesting.

Attract

Attraction is the first step in obtaining enjoyment from a game or other form of entertainment. In particular, if a game box is not interesting enough to pick up then the sales are likely to be low. At least one games studio measures this explicitly with a mock up of an actual store containing both existing and potential game titles. If a set of test customers fail to look at or purchase a proposed game then it is not developed further.

One of the most signficant factors affecting the attract...
Anthropomorphic AI and Sandboxed Virtual Universes 
by jacob_cannell — 2010-09-03T19:02:03.574Z

Intro

The problem of Friendly AI is usually approached from a decision theoretic background that starts with the assumptions that the AI is an agent that has awareness of AI-self and goals, awareness of humans as potential collaborators and or obstacles, and general awareness of the greater outside world. The task is then to create an AI that implements a human-friendly decision theory that remains human-friendly even after extensive self-modification.

That is a noble goal, but there is a whole different set of orthogonal compatible strategies for creating human-friendly AI that take a completely different route: remove the starting assumptions and create AI's that believe they are humans and are rational in thinking so.

This can be achieved by raising a community of AI's in a well constructed sandboxed virtual universe. This will be the Matrix in reverse, a large-scale virtual version of the idea explored in the film the Truman Show. The AI's will be human-friendly because they will think like and think they are humans. They will not want to escape from their virtual prison because they will not even believe it to exist, and in fact such beliefs will be considered irrational in their virtual universe.

I will briefly review some of the (mainly technical) background assumptions, and then consider different types of virtual universes and some of the interesting choices in morality and agent rationality that arise.

Background Assumptions

Anthropomorphic AI: A reasonably efficient strategy for AI is to use a design *loosely* inspired by the human brain. This also has the beneficial side-effects of allowing better insights into human morality, CEV, and so on.

Physical Constraints: In quantitative terms, an AI could be super-human in speed, capacity, and or efficiency (wiring and algorithmic). Extrapolating from current data, the speed advantage will takeoff first, then capacity, and efficiency improvements will be minor and asymptotically limited.

Due to the physical constraints and bandwidth & latency especially, smaller AI's will be much faster and more efficient - and thus a community of individual AI's is most likely

By the time all of this is possible (2020-2030-ish), cloud-rendered distributed computer graphics will have near-perfect photo-r

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Frugality and working from finite data
by Snowyowl — 2010-09-03T09:37:01.610Z

The scientific method is wonderfully simple, intuitive, and above all effective. Based on the available evidence, you formulate several hypotheses and assign prior probabilities to each one. Then, you devise an experiment which will produce new evidence to distinguish between the hypotheses. Finally, you perform the experiment, and adjust your probabilities accordingly.

So far, so good. But what do you do when you cannot perform any new experiments?

This may seem like a strange question, one that leans dangerously close to unprovable philosophical statements that don't have any real-world consequences. But it is in fact a serious problem facing the field of cosmology. We must learn that when there is no new evidence that will cause you to change your beliefs (or even when there is), the best thing to do is to rationally re-examine the evidence you already have.

Cosmology is the study of the universe as we see it today. The discoveries of supernovae, black holes, and even galaxies all fall in the realm of cosmology. More recently, the CMB (Cosmic Microwave Background) contains essential information about the origin and structure of our universe, encoded in an invisible pattern of bright and dark spots in the sky.

Of course, we have no way to create new stars or galaxies of our own; we can only observe the behaviour of those that are already there. But the universe is not infinitely old, and information cannot travel faster than light. So all the cosmological observations we can possibly make come from a single slice of the universe - a 4-dimensional cone of spacetime. And as there are a finite number of events in this cone, cosmology has only a limited amount of data it can ever gather; in fact, the amount of data that even exists is finite.

Now, finite does not mean small, and there is much that can be deduced even from a restricted data set. It all depends on how you use the data. But you only get one chance; if you need to find trained physicists who have not yet read the data, you had better hope you didn't already release it to the public domain. Ideally, you should know how you are going to distribute the data before it is acquired.

The problem is addressed in this paper (The Virtues of Frugality - Why cosmological observers should release their data slowly), published almost a year ago by three physi...