trentmkelly/LessWrong-43k huggingface dataset:
[SEQ RERUN] Kahneman's Planning Anecdote
by MinibearRex — 2011-08-31T03:33:35.749Z

Today's post, Kahneman's Planning Anecdote was originally published on 17 September 2007. A summary (taken from the LW wiki):

Nobel Laureate Daniel Kahneman recounts an incident where the inside view and the outside view of the time it would take to complete a project of his were widely different.

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 Planning Fallacy, 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.
How likely is Peter Thiel's investment into seasteading to pay off? 
by  — 2011-08-30T16:54:36.285Z

Recently the relatively awesome entrepreneur invested 1.25 million USD into this (seasteading institute website here).

It seems such a wonderful concept, finally somewhere where new forms of government could be tried out. But I'm just wondering how in the world they hope to deal with existing governments since their reaction to any kind of serious alternatives, especially one that either economically or ideologically presented a significant challenge, is bound to not be positive.

I was just wondering what LWer thoughts are on this matter? Also has there been any discussion of seasteading in the past that I've missed? Also I'm wondering if anyone would hazard to perhaps offer a prediction or judge how likley this is to succeed (maybe on predictionbook)?
My intentions for my metaethics sequence
by lukeprog — 2011-08-30T16:52:56.122Z

Recently a friend of mine told me that he and a few others were debating how likely it is that I've 'solved metaethics.' Others on this site have gotten the impression that I'm claiming to have made a fundamental breakthrough that I'm currently keeping a secret, and that's what my metaethics sequence is leading up to. Alas, it isn't the case. The first post in my sequence began:

A few months ago, I predicted that we could solve metaethics in 15 years. To most people, that was outrageously optimistic. But I've updated since then. I think much of metaethics can be solved now (depending on where you draw the boundary around the term 'metaethics'.) My upcoming sequence 'No-Nonsense Metaethics' will solve the part that can be solved, and make headway on the parts of metaethics that aren't yet solved. Solving the easier problems of metaethics will give us a clear and stable platform from which to solve the hard questions of morality.

The part I consider 'solved' is the part discussed in Conceptual Analysis and Moral Theory and Pluralistic Moral Reductionism. These posts represent an application of the lessons learned from Eliezer's free will sequence and his words sequence to the subject of metaethics.

I did this because Eliezer mostly skipped this step in his metaethics sequence, perhaps assuming that readers had already applied these lessons to metaethics to solve the easy problems of metaethics, so he could skip right to discussing the harder problems of metaethics. But I think this move was a source of confusion for many LWers, so I wanted to go back and work through the details of what it looks like to solve the easy parts of metaethics with lessons learned from Eliezer's sequences.

The next part of my metaethics sequence will be devoted to "bringing us all up to speed" on several lines of research that seem relevant to solving open problems in metaethics: the literature on how human values work (in brain and behavior), the literature on extracting preferences from what human brains actually do, and the literature on value extrapolation algorithms. For the most part, these literature sets haven't been discussed on Less Wrong despite their apparent relevance to metaethics, so I'm trying to share them with LW myself (e.g. A Crash Course in the Neuroscience of Human Motivation).

Technically, most of these posts will not be listed as being part of m...
Frequentist vs Bayesian breakdown: interpretation vs inference
by Academian — 2011-08-30T15:58:03.442Z

Suppose we have two different human beings, Connor and Diane, who agree to interpret their subjective anticipations as probabilities, thereby commonly earning them the title "Bayesian". On a particular project or venture, they might disagree on Trick A or Trick B to decide the next step in the project. It might be that Trick A is commonly labelled a "Frequentist inference method" and B is a "Bayesian inference method". Why might they disagree?

As far as I can see, there are 3 disagreements that get labelled "Bayesian vs Frequentist" debates, and conflating them is a problem:

(1) Whether to interpret all subjective anticipations as probabilities.

(2) Whether to interpret all probabilities as subjective anticipations.

(3) Whether, on a particular project, to use Statistical Trick B instead of Statistical Trick A to infer the best course of action, when B is commonly labelled a "Bayesian method" and A is a "Frequentist method".

(Regarding 3, UC Berkeley professor Michael Jordan offers a good heuristic for how statistical tricks get labelled as Bayesisn or Frequentist, in terms of which terms in a loss function one treats as fixed or variable. I recommend watching the first twenty minutes of his video lecture on this if you're not familiar.)

The question "is Connor a Bayesian or a Frequentist?" is commonly posed as though Connor's position on 1, 2, and 3 must be either "yes, yes, yes" or "no, no, no". I don't believe this is so often the case. For example, my position is:

(1) - Yes. Insofar as we have subjective anticipations, I agree normatively that they should behave and update as probabilities.

(2) - Don't care much. Expressions like P(X|Y) and P(X and Y) are useful for denoting both subjective anticipations and proportions of a whole, and in particular, proportions of real future events. Whether to use the word "probability" is a terminological question. Personally I try to reserve the word "probability" for when they mean subjective anticipations, and say "proportion" when they mean proportions of real future, but this is word choice. Unfortunately this word choice is strongly associated and confused with positions on (1) and (3).

(3) - It depends. In statistical inference, we commonly consider data sets x, world models M, and parameters θ that specify the model ...
[LINK] "Academic publishers make Murdoch look like a socialist" says George Monbiot 
by  — 2011-08-30T12:27:19.528Z

link

Who are the most ruthless capitalists in the western world? Whose monopolistic practices make Walmart look like a corner shop and Rupert Murdoch a socialist? You won't guess the answer in a month of Sundays. While there are plenty of candidates, my vote goes not to the banks, the oil companies or the health insurers, but – wait for it – to academic publishers. Theirs might sound like a fusty and insignificant sector. It is anything but. Of all corporate scams, the racket they run is most urgently in need of referral to the competition authorities.

Everyone claims to agree that people should be encouraged to understand science and other academic research. Without current knowledge, we cannot make coherent democratic decisions. But the publishers have slapped a padlock and a "keep out" sign on the gates.

You might resent Murdoch's paywall policy, in which he charges £1 for 24 hours of access to the Times and Sunday Times. But at least in that period you can read and download as many articles as you like. Reading a single article published by one of Elsevier's journals will cost you $31.50. Springer charges €34.95, Wiley-Blackwell, $42. Read 10 and you pay 10 times. And the journals retain perpetual copyright. You want to read a letter printed in 1981? That'll be $31.50.

Of course, you could go into the library (if it still exists). But they too have been hit by cosmic fees. The average cost of an annual subscription to a chemistry journal is $3,792. Some journals cost $10,000 a year or more to stock. The most expensive I've seen, Elsevier's Biochimica et Biophysica Acta, is $20,930. Though academic libraries have been frantically cutting subscriptions to make ends meet, journals now consume 65% of their budgets, which means they have had to reduce the number of books they buy. Journal fees account for a significant component of universities' costs, which are being passed to their students.

Murdoch pays his journalists and editors, and his companies generate much of the content they use. But the academic publishers get their articles, their peer reviewing (vetting by other researchers) and even much of their editing for free. The material they publish was commissioned and funded not by them but by us, through government research grants and academic stipends. But to see it, we must pay again, and through the nose.

The returns are astronom

...
That cat: not dead and alive
by DavidPlumpton — 2011-08-30T08:23:22.578Z

I've read through the Quantum Physics sequence and feel that I managed to understand most of it. But now it seems to me that the Double Slit and Schrodinger's cat experiments are not described quite correctly. So I'd like to try to re-state them and see if anybody can correct any misunderstandings I likely have.

With the Double Slit experiment we usually hear it said the particle travels through both slits and then we see interference bands. The more precise explanation is that there is an complex valued amplitude flow corresponding to the particle moving through the left slit and another for the right slit. But if we could manage to magically "freeze time" then we would find ourselves in one position in configuration space where the particle is unambiguously in one position (let's say the left slit). Now any observer will have no way of knowing this at the time, and if they did detect the particle's position in any way it would change the configuration and there would be no interference banding.

But the particle really is going through the left slit right now (as far as we are concerned), simply because that is what it means to be at some point in configuration space. The particle is going through the right slit for other versions of ourselves nearby in configuration space.

The amplitude flow then continues to the point in configuration space where it arrives at the back screen, and it is joined by the amplitude flow via the right slit to the same region of configuration space, causing an interference pattern. So this present moment in time now has more than one past, now we can genuinely say that it did go through both. Both pasts are equally valid. The branching tree of amplitude flow has turned into a graph.

So far so good I hope (or perhaps I'm about to find out I'm completely wrong). Now for the cat.

I read recently that experimenters have managed to keep two clouds of caesium atoms in a coherent state for a hour. So what would this look like if we could scale it up to a cat?

The problem with this experiment is that a cat is a very complex system and the two particular types of states we are interested in (i.e. dead or alive) are very far apart in configuration space. It may help to imagine that we could rearrange configuration space a little to put all the points labelled "alive" on the left and all the dead points on the right of some line. If we want to m...
Defrag conference scholarships
by EvelynM — 2011-08-30T03:36:40.264Z

http://www.defragcon.com/2011/general/defrag-announcements/

Eric Nolin of the Defrag conference is looking to organize a scholarship fund for high school girls who want to study computer science in university.

Till that's in place, they're funding scholarships for people to attend the conference.
Philosophical apologetics book suggests replacing Bayes theorem with "Inference to the Best Explanation" (IBE)
by jwhendy — 2011-08-30T03:31:22.033Z

I'm about 2/3 through an apologetics book that was recommended to me, Menssen and Sullivan's, The Agnostic Inquirer, and was quite surprised to run into a discussion of Bayes theorem and wanted some input from the LW community. The book is quite philosophical and I admit that I am probably not following all of it. I find heady philosophy to be one of these areas where something doesn't seem quite right (as in the conclusion that someone pushes), but I can't always identify what.

In any case, the primary point of the book is to attempt to replace the traditional apologetics method with a new one. The status quo has been to appeal to "natural theology," non-theological areas of discussion which attempt to bring one to the conclusion that some kind of theistic being exists, and from there establish that Christianity is the true formulation of what, exactly, this theistic being is/wants/does, etc by examining revealed theistic truths (aka the Bible). Menssen and Sullivan attempt to suggest that revelation need not be put off so long.

I don't want to get too into it, but think this helps set the stage. Their argument is as follows:

(1) If it is not highly unlikely that a world-creator exists, then investigation of the contents of revelatory claims might well show that it is probable that a good God exists and has revealed.

(2) It is not highly unlikely that a world-creator exists.

(3) So, investigation of the content of a revelatory claim might well show it is probable that a good God exists and has revealed.

(4) So, a negative conclusion concerning the existence of a good God is not justified unless the content of a reasonable number of leading revelatory claims has been seriously considered. (p. 63)

Issues Menssen and Sullivan have with Bayes applicability to this arena:

Then they begin trying to choose the best method for evaluating revelatory content. This is where Bayes comes in. The pages are almost all available via Google books HERE in Section 4.2.1, beginning on page 173. They suggest the following limitations:

Bayesian probability works well when the specific values are known (they use the example of predicting the color of a ball to be drawn out of a container). In theology, the values are not known.

The philosophical community is divided about whether Bayesian probability is reliable, and thus everyone should be hesitant about i

...
Meetup : Shanghai Less Wrong Meetup
by Patrick — 2011-08-30T03:07:57.176Z

Discussion article for the meetup : Shanghai Less Wrong Meetup

WHEN:
12 September 2011 07:00:00PM (+1000)

WHERE:
Starbucks, Carrefour Mall, the Zhongshan Park Store, near the Zhongshan Park Station, Line 2, 3, or 4, Shanghai, China

Where: Starbucks, Carrefour Mall, the Zhongshan Park Store, near the Zhongshan Park Station, Line 2, 3, or 4, Shanghai, China
B1&B2, No.1018, ChangNing Road, ChangNing District, Shanghai ( 长宁路1018号, 龙之梦购物中心B1-2楼 近凯旋路 )
When: 2011, September 12th, Monday, 7pm-10pm
Contact John Teddy: 18721399070 (local phone no., just text me if you can't find us)

I'm looking for any willing Shanghai Lesswrong readers to join this group if they haven't already.
Up vote user Teddy in the comments below. This way I have karma to post to the meetup section without asking Patrick Robotham each time. This will help us boost members for the community here in Shanghai.

Discussion article for the meetup : Shanghai Less Wrong Meetup
Do you expect a singularity within your life time?
by  — 2011-08-30T02:38:33.482Z

By singularity I mean a recursive self-improving intelligence created by man that will help us solve the worlds problems.

please explain the downvotes.. sorry I didn't write an essay or link to lots of in-jokes about the sky being green. It's just a simple question so I didn't want to embellish it.
Michael Jordan dissolves Bayesian vs Frequentist inference debate [video lecture]
by Academian — 2011-08-30T01:12:08.851Z

UC Berkeley professor Michael Jordan, a leading researcher in machine learning, has a great reduction of the question "Are your inferences Bayesian or Frequentist?". The reduction is basically "Which term are you varying in the loss function?". He calls this the "decision theoretic perspective" on the debate, and uses this terminology well in keeping with LessWrong interests.

I don't have time to write a top-level post about this (maybe someone else does?), but I quite liked the lecture, and thought I should at least post the link!

http://videolectures.net/mlss09uk_jordan_bfway/

The discussion gets much clearer starting at the 10:11 slide, which you can click on and skip to if you like, but I watched the first 10 minutes anyway to get a sense of his general attitude.

Enjoy! I recommend watching while you eat, if it saves you time and the food's not too distracting :)
[SEQ RERUN] Planning Fallacy
by MinibearRex — 2011-08-30T00:28:27.767Z

Today's post, Planning Fallacy was originally published on 17 September 2007. A summary (taken from the LW wiki):

We tend to plan envisioning that everything will go as expected. Even assuming that such an estimate is accurate conditional on everything going as expected, things will not go as expected. As a result, we routinely see outcomes worse then the ex ante worst case scenario.

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 Why I'm Blooking, 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.
An introduction to Bayesianism [links]
by lukeprog — 2011-08-29T19:06:27.639Z

Two recent papers in Philosophy Compass summarize the arguments for and against Bayesianism:

Easwaran, Bayesianism I: Introduction and Arguments in Favor

Easwaran, Bayesianism II: Applications and Criticisms

Philosophy Compass is a journal of review articles, my favorite reading material.

Kenny Easwaran got his PhD from UC Berkeley under formal epistemologist Brandon Fitelson, did a post-doc at ANU, and is now an assistant professor at USC.
Call for Personal Volunteers
by lukeprog — 2011-08-29T16:31:02.939Z

Those who wish to volunteer some of their time toward reducing existential risk and increasing our chances of a positive singularity can follow the directions on SingularityVolunteers.org.

And as a freshly hired Singularity Institute researcher, I also have my own list of tasks that, if completed by volunteers instead of myself, will speed along the delivery of the projects I'm working on: an 'FAI Open Problems' document, two papers bound for peer review, metaethics research, and more.

So if you'd like to help me out with any of my volunteer-doable tasks, please contact me: luke [at] singinst [dot] org.

Thanks!
A History of Bayes' Theorem
by lukeprog — 2011-08-29T07:04:30.385Z

Sometime during the 1740s, the Reverend Thomas Bayes made the ingenious discovery that bears his name but then mysteriously abandoned it. It was rediscovered independently by a different and far more renowned man, Pierre Simon Laplace, who gave it its modern mathematical form and scientific application — and then moved on to other methods. Although Bayes’ rule drew the attention of the greatest statisticians of the twentieth century, some of them vilified both the method and its adherents, crushed it, and declared it dead. Yet at the same time, it solved practical questions that were unanswerable by any other means: the defenders of Captain Dreyfus used it to demonstrate his innocence; insurance actuaries used it to set rates; Alan Turing used it to decode the German Enigma cipher and arguably save the Allies from losing the Second World War; the U.S. Navy used it to search for a missing H-bomb and to locate Soviet subs; RAND Corporation used it to assess the likelihood of a nuclear accident; and Harvard and Chicago researchers used it to verify the authorship of the Federalist Papers. In discovering its value for science, many supporters underwent a near-religious conversion yet had to conceal their use of Bayes’ rule and pretend they employed something else. It was not until the twenty-first century that the method lost its stigma and was widely and enthusiastically embraced.

So begins Sharon McGrayne's fun new book, The Theory That Would Not Die, a popular history of Bayes' Theorem. Instead of reviewing the book, I'll summarize some of its content below. I skip the details and many great stories from the book, for example the (Bayesian) search for a lost submarine that inspired Hunt for Red October. Also see McGrayne's Google Talk here. She will be speaking at the upcoming Singularity Summit, too, which you can register for here (price goes up after August 31st).

Origins

In the 1700s, when probability theory was just a whiff in the air, the English Reverend Thomas Bayes wanted to know how to infer causes from effects. He set up his working problem like this: How could he learn the probability of a future event occurring if he only knew how many times it had occurred or not occurred in the past?

He needed a number, and it was hard to decide which number to choose. In the end, his solution was to just guess and then improve his guess later as he ...
[LINK] How Hard is Artificial Intelligence? The Evolutionary Argument and Observation Selection Effects 
by AnnaSalamon — 2011-08-29T05:27:31.636Z

If you're interested in evolution, anthropics, and AI timelines -- or in what the Singularity Institute has been producing lately -- you might want to check out this new paper, by SingInst research fellow Carl Shulman and FHI professor Nick Bostrom.

The paper:

How Hard is Artificial Intelligence? The Evolutionary Argument and Observation Selection Effects

The abstract:

Several authors have made the argument that because blind evolutionary processes produced human intelligence on Earth, it should be feasible for clever human engineers to create human-level artificial intelligence in the not-too-distant future. This evolutionary argument, however, has ignored the observation selection effect that guarantees that observers will see intelligent life having arisen on their planet no matter how hard it is for intelligent life to evolve on any given Earth-like planet. We explore how the evolutionary argument might be salvaged from this objection, using a variety of considerations from observation selection theory and analysis of specific timing features and instances of convergent evolution in the terrestrial evolutionary record. We find that a probabilistic version of the evolutionary argument emerges largely intact once appropriate corrections have been made.

I'd be interested to hear LW-ers' takes on the content; Carl, too, would much appreciate feedback.