trentmkelly/LessWrong-43k huggingface dataset:
Question about timeless physics
by XiXiDu — 2011-12-16T13:09:54.128Z

Related to: lesswrong.com/lw/qp/timeless_physics/

Why do I find myself at this point in time, configuration space, rather than another point? In other words, why do I have certain expectations rather than others?

I don't expect the U.S. presidential elections to have happened but to happen next, where "to happen" and "to have happened" internally marks the sequential order of steps indexed by consecutive timestamps. But why do I find myself to have that particular expectation rather than any other, what is it that does privilege this point?

So you seem to remember Time proceeding along a single line. You remember that the particle first went left, and then went right. You ask, "Which way will the particle go this time?"

My question is why I find myself to remember that the particle went left and then right rather than left but not yet right?

But both branches, both future versions of you, just exist. There is no fact of the matter as to "which branch you go down". Different versions of you experience both branches.

Yes, but why does my version experience this point of my branch and not any other point of my branch?

I understand that if this universe was a giant simulation and that if it was to halt and then resume, after some indexical measure of causal steps used by those outside of it, then I wouldn't notice it. Therefore if you remove the notion of an outside world there ceases to be any measure of how many causal steps it took until I continued my relational measure of progression.

But that's not my question. Assume for a moment that my consciousness experience is not a causal continuum but a discrete sequence of causal steps from 1, 2, 3, ... to N where N marks this point. Why do I find myself at N rather than 10 or N+1?
Allen & Wallach on Friendly AI
by lukeprog — 2011-12-16T09:22:39.436Z

Colin Allen and Wendell Wallach, who wrote Moral Machines (MM) for OUP in 2009, address the problem of Friendly AI in their recent chapter for Robot Ethics (MIT Press). Their chapter is a precis of MM and a response to objections, one of which is:

The work of researchers focused on ensuring that a technological singularity will be friendly to humans (friendly AI) was not given its due in MM.

Their brief response to this objection is:

The project of building AMAs [artificial moral agents] is bracketed by the more conservative expectations of computer scientists, engaged with the basic challenges and thresholds yet to be crossed, and the more radical expectations of those who believe that human-like and superhuman systems will be built in the near future. There are a wide variety of theories and opinions about how sophisticated computers and robotic systems will become in the next twenty to fifty years. Two separate groups focused on ensuring the safety of (ro)bots have emerged around these differing expectations: the machine ethics community and the singularitarians (friendly AI), exemplified by the Singularity Institute for Artificial Intelligence (SIAI). Those affiliated with SIAI are specifically concerned with the existential dangers to humanity posed by AI systems that are smarter than humans. MM has been criticized for failing to give fuller attention to the projects of those dedicated to a singularity in which AI systems friendly to humans prevail.

SIAI has been expressly committed to the development of general mathematical models that can, for example, yield probabilistic predictions about future possibilities in the development of AI. One of Eliezer Yudkowsky’s projects is motivationally stable goal systems for advanced forms of AI. If satisfactory predictive models or strategies for stable goal architectures can be developed, their value for AMAs is apparent. But will they be developed, and what other technological thresholds must be crossed, before such strategies could be implemented in AI? In a similar vein, no one questions the tremendous value machine learning would have for facilitating the acquisition by AI systems of many skills, including moral decision making. But until sophisticated machine learning strategies are developed, discussing their application is speculative. That said, since the publication of M

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Problems of the Deutsch-Wallace version of Many Worlds
by Mitchell_Porter — 2011-12-16T06:55:55.479Z

The subject has already been raised in this thread, but in a clumsy fashion. So here is a fresh new thread, where we can discuss, calmly and objectively, the pros and cons of the "Oxford" version of the Many Worlds interpretation of quantum mechanics.

This version of MWI is distinguished by two propositions. First, there is no definite number of "worlds" or "branches". They have a fuzzy, vague, approximate, definition-dependent existence. Second, the probability law of quantum mechanics (the Born rule) is to be obtained, not by counting the frequencies of events in the multiverse, but by an analysis of rational behavior in the multiverse. Normally, a prescription for rational behavior is obtained by maximizing expected utility, a quantity which is calculated by averaging "probability x utility" for each possible outcome of an action. In the Oxford school's "decision-theoretic" derivation of the Born rule, we somehow start with a ranking of actions that is deemed rational, then we "divide out" by the utilities, and obtain probabilities that were implicit in the original ranking.

I reject the two propositions. "Worlds" or "branches" can't be vague if they are to correspond to observed reality, because vagueness results from an object being dependent on observer definition, and the local portion of reality does not owe its existence to how we define anything; and the upside-down decision-theoretic derivation, if it ever works, must implicitly smuggle in the premises of probability theory in order to obtain its original rationality ranking.

Some references:

"Decoherence and Ontology: or, How I Learned to Stop Worrying and Love FAPP" by David Wallace. In this paper, Wallace says, for example, that the question "how many branches are there?" "does not... make sense", that the question "how many branches are there in which it is sunny?" is "a question which has no answer", "it is a non-question to ask how many [worlds]", etc.

"Quantum Probability from Decision Theory?" by Barnum et al. This is a rebuttal of the original argument (due to David Deutsch) that the Born rule can be justified by an analysis of multiverse rationality.
A discarded review of 'Godel, Escher Bach: an Eternal Golden Braid'
by lukeprog — 2011-12-16T05:51:55.864Z

Recently I began to write a review of Hofstadter's Godel, Escher, Bach, until I realized that the book defied summary more than all the other books I had previously said "defied summary." Thus, I gave up on reviewing the book after not too long. I present my discarded review below just in case it motivates someone else to pick up this masterful tome and let it enrich their life.

Of Hofstadter's GEB, Eliezer once wrote:

This is simply the best and most beautiful book ever written by the human species...

I'm not alone in this opinion, by the way. For one thing, Gödel, Escher, Bach won a Pulitzer Prize. Or just pick a random scientist and ask ver what vis favorite book is, and 1 out of 5 will say: "Gödel, Escher, Bach". No other book even comes close.

It is saddening to contemplate that every day, 150,000 humans die without reading what is indisputably one of the greatest achievements of our species. Don't let it happen to you.

Sure, if you're just an average person, you might not understand everything in this book - but when you're done reading, you won't be an average person any more.

It's easy to see GEB's effect on Eliezer's writing: the "concrete, then abstract" pattern, the koans, the puzzles, the conversational coverage of technical concepts in math and computer science... it's all here in spades in GEB.

What GEB Is

In the preface to the 20th anniversary edition, Hofstadter clarifies what GEB is and is not. It is not about how reality is "a system of interconnected braids." It is not about how "math, art, and music are really all the same thing at their core." Instead, says Hofstadter:

GEB is a very personal attempt to say how it is that animate beings can come out of inanimate matter... GEB approaches [this question] by slowly building up an analogy that likens inanimate molecules to meaningless symbols, and further likens selves... to certain special swirly, twisty, vortex-like, and meaningful patterns that arise only in particular types of systems of meaningless symbols. It is these strange, twisty patterns that the book spends so much time on, because they are little known, little appreciated, counterintuitive, and quite filled with mystery [that] I call... "strange loops"...

...the Godelian strange loop that arises in formal systems in mathematics... is a loop that allows such systems to "perceive its

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[SEQ RERUN] But There's Still A Chance, Right?
by MinibearRex — 2011-12-16T03:03:12.521Z

Today's post, But There's Still A Chance, Right? was originally published on 06 January 2008. A summary (taken from the LW wiki):

Sometimes, you calculate the probability of a certain event and find that the number is so unbelievably small that your brain really can't keep track of how small it is, any more than you can spot an individual grain of sand on a beach from 100 meters off. But, because you're already thinking about that event enough to calculate the probability of it, it feels like it's still worth keeping track of. It's not.

Discuss the post here (rather than in the comments to the original post).
This post is part of the Rerunning the Sequences series, where we'll be going through Eliezer Yudkowsky's old posts in order so that people who are interested can (re-)read and discuss them. The previous post was A Failed Just-So Story, and you can use the sequence_reruns tag or rss feed to follow the rest of the series.
Sequence reruns are a community-driven effort. You can participate by re-reading the sequence post, discussing it here, posting the next day's sequence reruns post, or summarizing forthcoming articles on the wiki. Go here for more details, or to have meta discussions about the Rerunning the Sequences series.
Do men have more partners than women?
by DuncanS — 2011-12-16T00:11:56.284Z

Today I came across an article in the Telegraph that states that an average man has 9 sexual partners in his lifetime, whilst a woman has only 4.

Let's assume for a moment that in fact all these men and women are heterosexuals. In that case, each partnership contains one man and one woman. So, in total, the number of partnerships that women enter into is exactly the same as the number of partnerships that men enter into. Given a few other pretty well-known facts - that men are roughly as numerous as women, and live roughly as long, we deduce that on average men enter into roughly as many sexual partnerships as women.

There is, of course, a potential flaw in this - we know not all partnerships are in fact heterosexual. We know that heterosexual partnerships must have as many female participants as male, but we know no such thing about homosexual ones. Perhaps homosexual men have many, many more partnerships than heterosexual men, or women of any inclination? Whilst there is some evidence in favour of this concept, I don't really think it's going to be a big enough effect to skew the entire ratio this much. In order to have a ration of 9 to 4, most male partnerships would have to be homosexual ones.

A better theory is that the data is not very good. Perhaps men tend to exaggerate the number of sexual partners they have, even in anonymous surveys. Perhaps women tend to emphasise their degree of virginity. Perhaps the distributions are different - perhaps for example, most women have fewer partners than most men, but some women have lots? And perhaps this sort of information is lost in the survey?

Probably the only safe conclusion we can draw from these figures is that journalists and statistics don't mix.
Rationality Verification Opportunity?
by beoShaffer — 2011-12-15T22:11:04.211Z

One of the challenges of rationality verification is that most people who are willing to contribute personal data for it are already familiar with the techniques involved. This makes it difficult to tell if their performance on any form of rationality test is due to their training or their innate abilities. Does the start of a new sequence present a way around this for that sequence's content?

I believe that it might, and will propose some ideas on how we can take advantage of these opportunities. But first I would suggest that you try to think through the problem for yourself (I know this is slightly different from what is talked about in that post, but I think the principle holds).

Did you think through the general problem of rationality verification for new sequences before thinking of any solutions. Did you then think of your own solutions before getting your mind contaminated with mine? If yes, good. If no, not so good.

If we had good measures of general rationality that could be retaken by the same person multiple times without losing reliability we could simply ask LWers to take them at various intervals and see if they improved after reading the new sequence. As that is not the case I suspect we would have to create specific measures for each sequence. It seems that most writers have a decent idea of what benefits they expect people to gain from their sequences' so perhaps they could try to come up with specific measures for the things that their sequences are supposed to improve. Then before running the sequence main sequence they could put out a call for people to complete these measures and send them in. They could then collect the data again from people who have read the completed sequence, preferably after they have had enough time to practice the material, but not long enough to have had to many other life changes. The necessity and viability of having additional experimental controls will vary between sequences. But I think we will generally be fine with a simple before and after picture.

While there are some time and talent limitations I would be willing to help with creating the measures, collecting and interpreting the data and any other necessary steps.

I declare Crocker's rules on the content and style...
How to label thoughts nonverbally
by eugman — 2011-12-15T18:23:55.946Z

Introduction

Recently I've been attempting to put a damper on my ruminations. Sometimes they can get out of control and be somewhat self-sustaining. These negative, repetitive thoughts can be harmful and make depression worse. Accordingly, I've been looking for techniques to help manage this.

In a previous post, I talked about how I stumbled onto a way to track emotions through kinesthetic memory. Specifically, I am using a checkmark gesture to mark negative thoughts, and at this point it has become semiautomatic. The results have been quite interesting.

A little later, someone wanted to know about the process in detail. My first impulse was to shout "MU!". It seems contradictory to try to use words to describe something that is inherently and intentionally a nonverbal process. However, I decided that is was worth a shot. Below, I cover the skills that you will need, how the process works, and my personal experiences with it.

Skill building

So, in order for this process to work, you need to develop three related but separate skills. First, you have to be able to tell when you are thinking/feeling. Second you have to be able to label these thoughts and emotions. Third is something I call the Pivot. It's changing the direction of your thoughts without mentally moving forward. Each of these are not natural skills, so don't be discouraged if you need a lot of practice.

Basic meditation is perfect for noticing what you are thinking. Starting out, catching thoughts is the hardest thing to do. In my experience, there are a surprising number of things that you think without even being aware of it. What's worse is most of them are quite fleeting. Until you get very good at catching fleeting thoughts, this process probably won't work for you.

Besides meditation, mindfulness practice helps too. The next time you are eating a meal, try to focus just on the food itself. Your thoughts are likely to wonder, or you may even end up checking Facebook on your phone. When you notice this, smile. You just caught yourself, congratulations. One last technique is to sit with a tablet and just write thoughts as they come to you. This is slow, but good starting practice.

The second step is to start being able to label your thoughts and emotions. At first this may be difficult, and I would suggest simply trying to label them as positive, negative, or neutral. The three techniques I used pe...
Compressing Reality to Math
by Vaniver — 2011-12-15T00:07:17.515Z

This is part of a sequence on decision analysis and follows 5 Axioms of Decision-Making, which explains how to turn a well-formed problem into a solution. Here we discuss turning reality into a well-formed problem. There are three basic actions I'd like to introduce, and then work through some examples.

Scope

The first thing you have to decide with a problem is, well, what the problem is. Suppose you're contemplating remodeling your kitchen, and the contractor you're looking at offers marble or granite countertops. While deciding whether you want marble or granite, you stop and wonder- is this really the contractor that you should be using? Actually, should you even be remodeling your kitchen? Maybe you should to move to a better city first. But if you're already thinking about moving, you might even want to emigrate to another country.

At this point the contractor awkwardly coughs and asks whether you'd like marble or granite.

Decisions take effort to solve, especially if you're trying to carefully avoid bias. It helps to partition the world and deal with local problems- you can figure out which countertops you want without first figuring out what country you want to live in. It's also important to keep in mind lost purposes- if you're going to move to a new city, remodeling your kitchen is probably a mistake, even after you already called a contractor. Be open to going up a level, but not paralyzed by the possibility, which is a careful balancing act. Spending time periodically going up levels and reevaluating your decisions and directions can help, as well as having a philosophy of life.

Model

Now that you've got a first draft of what your problem entails, how does that corner of the world work? What are the key decisions and the key uncertainties? A tool that can be of great help here is an influence diagram, which is a directed acyclic graph1 which represents the uncertainties, decisions, and values inherent in a problem. While sketching out your model, do you become more or less comfortable with the scope of the decision? If you're less comfortable, move up (or down) a level and remodel.

Elicit

Now that you have an influence diagram, you need to populate it with numbers. What (conditional) probabilities do you assign to uncertainty nodes? What preferences do you assign to possible outcomes? Are there any other uncertainty nodes you could add to cla...
[LINK] SMBC discusses the Singularity.
by radical_negative_one — 2011-12-14T19:58:17.516Z

A Short History of Tool Use:

http://www.smbc-comics.com/index.php?db=comics&id=2460#comic

A human applies a wrench to a rock.
A human applies a chain of interlinked wrenches to a tower.
A human applies a chain of interlinked wrenches to its own head.
A chain of interlinked wrenches forms a loop.

Hover your mouse over the red button at the lower-left to see the message, "Reddit is somewhere between 2 and 3."
Building case-studies of akrasia
by Mercurial — 2011-12-14T18:42:28.991Z

The idea for this came to me when reading nyan_sandwich's "An akrasia case study." I outlined the idea itself in my comment in that thread.

So here's the plan:

In a comment reply to this, describe a specific instance of akrasia in your own life. Place an emphasis on the specificity. Focus on a specific task, either positive (i.e., that you judge to be good to do but self-sabotage from doing, like writing a paper) or negative (i.e., that you know you shouldn't do but do anyway, like buying more Frosted Flakes for breakfast and continuing to eat them). The more specific, the better.

You can share multiple instances, but please create new comments for each.

If you tried an anti-akrasia technique in this specific context, explain what you did and what effect it had. If you have some way in which you measured its effects objectively, please share that. If not, though, that's okay; we can still learn something from what various attempts to tackle different manifestations of akrasia feel like from the inside. The goal here is not to propose solutions; instead, it's to see what different things that feel like solutions seem to do to different kinds of akrasia. So even failed attempts are useful.

If you tried multiple approaches or if your approach requires some explanation, you might consider describing it and its effects in a reply to your description of the instance of akrasia you applied it to.

Let me emphasize one more time that we are not looking for solutions in this thread. Please don't give each other suggestions! If you think you're on to something hot in terms of the "kicking" aspect of the Art, please show us with a description of how the technique worked for you on a specific instance - but share the instance first. The goal here is not to demonstrate that you have a clever anti-akrasia technique. The goal instead is to see what different instances of akrasia and attempts to tackle it actually look like.

If at all possible, please share both successes and failures. This is especially helpful if we can see successes and failures of the same technique. This helps to balance out positive bias and gives us a better idea of the parameters within which different techniques work. Be especially wary if you have a favorite anti-akrasia technique because of the subconscious desire to attempt to change reality by pretending your favori...
[SEQ RERUN] A Failed Just-So Story
by MinibearRex — 2011-12-14T18:22:15.044Z

Today's post, A Failed Just-So Story was originally published on 05 January 2008. A summary (taken from the LW wiki):

Part of the reason professional evolutionary biologists dislike just-so stories is that many of them are simply wrong.

Discuss the post here (rather than in the comments to the original post).
This post is part of the Rerunning the Sequences series, where we'll be going through Eliezer Yudkowsky's old posts in order so that people who are interested can (re-)read and discuss them. The previous post was Rational vs Scientific Ev-Psych, and you can use the sequence_reruns tag or rss feed to follow the rest of the series.
Sequence reruns are a community-driven effort. You can participate by re-reading the sequence post, discussing it here, posting the next day's sequence reruns post, or summarizing forthcoming articles on the wiki. Go here for more details, or to have meta discussions about the Rerunning the Sequences series.