trentmkelly/LessWrong-43k huggingface dataset:
I’m behind my eyes
by KatjaGrace — 2010-05-25T20:00:33.000Z

Where does your mind feel like it is?

Ken Aizawa asks why we intuitively feel like our minds are in our heads, and answers by saying it’s because humans discovered early on that damaging the head disables the mind, and have passed the knowledge of their equivalence on since. This seems unlikely to me, since damaging other parts of the body well enough also disables the mind and damaging the head also disables other bodily functions. Plus it seems a much stronger intuition to me than ‘my feet are made of atoms’ for instance, a belief about the composition of my body that culture gave me early on. I also doubt the ‘I am in my head’ intuition is a direct evolutionary result, since it doesn’t seem useful. I suspect instead that I feel like ‘I’ am located in my head since my eyes are there, and they give me most of the information about my location. I can look down and see my feet a long way away, and it would be complicated to think I was over there. Next I might think I was a person on the other side of the room. I am simply at the center of my perspective of the world.

A way to test this is to ask blind people, though they may get the same effect with their ears. Better would be to ask people who are blind and deaf. I know few of the former and none of the latter – can any of my readers enlighten me?

Also, I’m not sure that the assumption in the original question is right, since at least once I have heard someone imply they feel like they are located elsewhere. Do most people actually feel like their minds are in their heads?
LessWrong meetup, London UK, 2010-06-06 16:00
by Paul Crowley — 2010-05-23T13:46:44.536Z

The next London LessWrong meetup will be at 16:00 on Sunday 6 June in the Shakespeare's Head near Holborn station. I'll put a Less Wrong sign on the table so you can find us; I look like this. Send me a direct message with your mobile number or email me (paul at ciphergoth dot org), and I'll reciprocate.

We're trying out a different venue this time; this is where we ended up meeting after Humanity+ which means that at least six of us already know where it is. Looking forward to seeing some of you there!

Update: Sad to say, I may now not make this myself - a domestic emergency has come up. Sorry to let people down! If another volunteer could step forward to put the "Less Wrong" notice on the table and kick things off, that would be a great service - thanks!
30th Soar workshop
by Johnicholas — 2010-05-23T13:33:04.631Z

This is a report from a LessWrong perspective, on the 30th Soar workshop. Soar is a cognitive architecture that has been in continuous development for nearly 30 years, and is in a direct line of descent from some of the earliest AI research (Simon's LT and GPS). Soar is interesting to LessWrong readers for two reasons:

Soar is a cognitive science theory, and has had some success at modeling human reasoning - this is relevant to the central theme of LessWrong, improving human rationality.

Soar is an AGI research project - this is relevant to the AGI risks sub-theme of LessWrong.

Where I'm coming from: I'm a skeptic about EY/SIAI dogmas that AI research is more risky than software development, and that FAI research is not AI research, and has little to learn from the field of AI research. In particular, I want to understand why AI researchers are generally convinced that their experiments and research are fairly safe - I don't think that EY/SIAI are paying sufficient attention to these expert opinions.

Overall summary: John Laird and his group are smart, dedicated, and funded. Their theory and implementation moves forward slowly but continuously. There's no (visible) work being done on self-modifying, bootstrapping or approximately-universal (e.g. AIXItl) entities. There is some concern about how to build trustworthy and predictable AIs (for the military's ROE) - for example, Scott Wallace's research.

As far as I can tell, the Soar group's work is no more (or less) risky than narrow AI research or ostensibly non-AI software development. To be blunt - package managers like APT seem more risky than Soar, because the economic forces that push them to more capability and complexity are more difficult to control.

Impressions of (most of) the talks - they can be roughly categorized into three types.

Miscellaneous

Paul Rosenbloom (one of the original authors of Soar, with John Laird and Allen Newell) spoke about trying to create a layer architecturally beneath Soar based on Bayesian graphical models; specifically factor graphs. There were not a lot of people using or trying to use Bayesian magic at the workshop, but Paul Rosenbloom is definitely a Bayesian magician; he's getting Rete to run as an emergent consequence of the sum-product algorithm.

Ken Forbus (of "Structure-Mapping Engine" fame) spoke generally about his research, including Companions and CogSketch.

...
Link: Strong Inference
by Daniel_Burfoot — 2010-05-23T02:49:38.419Z

The paper "Strong Inference" by John R. Platt is a meta-analysis of scientific methodology published in Science in 1964. It starts off with a wonderfully aggressive claim:

Scientists these days tend to keep up a polite fiction that all science is equal.

The paper starts out by observing that some scientific fields progress much more rapidly than others. Why should this be?

I think the usual explanations we tend to think of - such as the tractability of the subject, or the quality or education of the men drawn into it, or the size of the research contracts - are important but inadequate... Rapidly moving fields are fields where a particular method of doing scientific research is systematically used and taught, an accumulative method of inductive inference that is so effective that I think it should be given the name "Strong Inference".

The definition of Strong Inference, according to Platt, is the formal, explicit, and regular adherence to the following procedure:

Devise alternative hypotheses;

Devise a crucial experiment (or several of them), with alternative possible outcomes, each of which will, as nearly as possible, exclude one or more of the hypotheses;

Carry out the experiment so as to get a clean result;

(Goto 1) - Recycle the procedure, making subhypotheses or sequential hypotheses to refine the problems that remain; and so on.

This seems like a simple restatement of the scientific method. Why does Platt bother to tell us something we already know?

The reason is that many of us have forgotten it. Science is now an everyday business. Equipment, calculations, lectures become ends in themselves. How many of us write down our alternatives and crucial experiments every day, focusing on the exclusion of a hypothesis?

Platt gives us some nice historical anecdotes of strong inference at work. One is from high-energy physics:

[One of the crucial experiments] was thought of one evening at suppertime: by midnight they had arranged the apparatus for it, and by 4am they had picked up the predicted pulses showing the non-conservation of parity.

The paper emphasizes the importance of systematicity and rigor over raw intellectual firepower. Roentgen, proceeding systematically, shows us the meaning of haste:

Within 8 weeks after the discovery of X-rays, Roentgen had identified 17 of their major properties.

Later, Platt argues against the overuse...
Why is reductionism rude?
by KatjaGrace — 2010-05-23T01:19:42.000Z

People have a similar dislike for many quantification related things:

Being referred to by numbers rather than names (though numbers are befitting for robots)

Being objectified

Becoming a statistic

Attempts to measure, model or derive quantitatively things like art, culture, meaning, relationships

‘Reductionism‘

People who are calculating

Economics‘ attempts to quantify things that ‘just can’t be quantified’

Public rankings of school test scores

Why?

Individual explanations abound. Being thought of as an object, number, or statistic is ‘dehumanizing’. Tv-tropes suggest serial numbers and prison numbers make numbers suggest inhumanity. ‘Being a number’ prevents you being unique (strangely – how many people share your credit card number? How many share your name?’). Being objectified makes others disrespect you as they do objects. Measuring art or culture misses important, indefinable or intangible things. Being a statistic is bad because people don’t care about statistics. Publishing school tests scores misleads parents because test scores aren’t everything, and parents might think they are.

These explanations mostly seem unexplanatory or implausible to me, and the similarity of the concerns suggests that they have a common cause. The explanations have an idea in common: quantification destroys important, especially human related, aspects of things.

This seems an odd concern. Measuring things naturally leaves some of their aspects unmeasured, but if you are worried about missing information, refusing to measure what you can is a strange solution. And fear of Goodhart’s law doesn’t account for the offense and disdain these things prompt.

One explanation is that explicit measurement inhibits one using ‘judgement’ to come to preferred conclusions. That is, it restricts hypocrisy. This explanation requires that the things people don’t want to measure are the things they like to lie about the importance of. This tentatively seems to fit – the things we don’t want to quantify are usually manifestations of admirable values that people tend to talk of more than act on. We mind quantifying love more than sex, nice views more than nice timber, friendship more than hairdressing.

It’s been argued before that we like to say ‘sacred val...
To signal effectively, use a non-human, non-stoppable enforcer
by Clippy — 2010-05-22T22:03:00.354Z

Follow-up to: this comment in this thread

Summary: see title

Much effort is spent (arguably wasted) by humans in a zero-sum game of signaling that they hold good attributes. Because humans have strong incentive to fake these attributes, they cannot simply inform each other that:

I am slightly more committed to this group’s welfare, particularly to that of its weakest members, than most of its members are. If you suffer a serious loss of status/well-being I will still help you in order to display affiliation to this group even though you will no longer be in a position to help me. I am substantially more kind and helpful to the people I like and substantially more vindictive and aggressive towards those I dislike. I am generally stable in who I like. I am much more capable and popular than most members of this group, demand appropriate consideration, and grant appropriate consideration to those more capable than myself. I adhere to simple taboos so that my reputation and health are secure and so that I am unlikely to contaminate the reputations or health of my friends. I currently like you and dislike your enemies but I am somewhat inclined towards ambivalence on regarding whether I like you right now so the pay-off would be very great for you if you were to expend resources pleasing me and get me into the stable 'liking you' region of my possible attitudinal space. Once there, I am likely to make a strong commitment to a friendly attitude towards you rather than wasting cognitive resources checking a predictable parameter among my set of derivative preferences.

Or, even better:

I would cooperate with you if and only if (you would cooperate with me if and only if I would cooperate with you).

An obvious solution to this problem, which allows all humans to save resources and redirect them toward higher-valued ends, is to designate a central enforcer that is inexorably committed toward visibly punishing those who deviate from a specified "cooperative"-type decision theory. This enforcer would have a central database of human names, the decision theory they have committed to, and the punishment regime they will endure for deviating therefrom.

Such a system could use equally strong protocols, such as public key/private key encryption and signing, so that, on encounter with another human, any human can give an extremely strong signal of being coo...
LessWrong downtime 2010-05-11, and other recent outages and instability
by matt — 2010-05-22T01:33:08.403Z

Incident report and hosting update

In the leadup to 2010-05-11 we (Tricycle) were unhappy with repeated short downtime incidents on the Less Wrong (LW) server (serpent). The apparent cause was the paster process hanging during heavy IO. We had scripted an automatic restart of the process when this problem was detected, but each incident caused up to a minute of downtime and it was obvious that we needed a proper solution. We concluded that IO on serpent was abnormally slow, and that the physical machine at Slicehost that serpent ran on had IO problems (Slicehost was unable to confirm our diagnosis). We requested migration to a new physical machine.

Error 1: We requested this migration at the end of our working day, and didn't nurse the migration through.

After the migration LW booted properly, but was quickly unstable. Since we didn’t nurse the migration through we failed to notice ourselves. Our website monitoring system (nagios) should have notified us of the failure, but it, too failed. We have a website monitoring system monitoring system (who watches the watchers? this system does - it is itself watched by nagios).

Error 2: Our website monitoring system monitoring system (a cron job running on a separate machine) was only capable of reporting nagios failures by email. It "succeeded" in so far as it sent an email to our sysadmin notifying him that nagios was failing. It clearly failed in that it failed to actually notify a human in reasonable time (our sysadmin very reasonably doesn’t check his email during meals).

serpent continued to be unstable through our next morning as we worked on diagnosing and fixing the problem. IO performance did not improve on a new physical server.

2010-05-17 we migrated the system again to an AWS server, and saw significant speed and general stability improvements.

Error 3: The new AWS server didn’t include one of the python dependencies the signup captcha relies on. We didn’t notice. Until davidjr raised an issue in the tracker (#207), which notified us, no-one was able to sign up.

What we have achieved:

LW is now significantly faster and more responsive. It also has much more headroom on its server - even large load spikes should not reduce performance.

What has been done to prevent recurrence of errors:

Error 1: Human error. We won’t do that again. Generally “don’t do that again” isn&...
Taking the awkwardness out of a Prenup - A Game Theoretic solution
by VijayKrishnan — 2010-05-22T00:45:29.406Z

I would strongly advise you to look at the short review on Thomas Schelling's Strategy of Conflict posted on Less Wrong some time back. The idea that deliberately constraining one's own choices can actually leave a person better off in a negotiation is a very interesting one. The most classic game theoretic example of this is the game of Chicken. In the game of Chicken, two people drive toward each other on a wide freeway. If neither of them swerve, they both stand to lose by way of substantial financial damage and possible loss of lives. If not, the first one to swerve is the proverbial "chicken" and stands to lose face against the other person who was brave enough to not swerve. If one person were to throw away their steering wheel and blindfold themselves before driving on the freeway, that would force the other person to swerve given that the first person has completely given up control of the situation.

There is a slightly more generalizable example of a similar principle at work. Suppose you wanted to buy a used car from a car dealer and were prepared to pay up to $5000 for the car and the car dealer in turn was willing to sell it for any price above $4000. In such a situation, any price between $4000 and $5000 is an admissible solution. However you ideally want to pay as close to $4000 as possible, while the car dealer would like you to pay close to $5000. In a such a situation, each party would pretend that their "last price" (the price that represents the worst possible outcome for them, which they would nonetheless be willing to accept) was different from the true last price, since if one party realizes the other party's true last price, that party can put it to effective use in the negotiation. Let us now assume a situation wherein you and the car dealer know perfectly well about the each other's financial details, the degree of urgency in having the transaction done etc., and have a very reliable idea of the last price of the other person. Now, you can break the symmetry and get the best possible deal out of the situation by deliberately handicapping yourself in the following fashion. You sign a contract with a third party individual which states that if you happen to do this transaction and pay more than $4000, you will have to pay the third party $1500. Now, all you need to do is show this contract to your used car...
The Tragedy of the Social Epistemology Commons
by Roko — 2010-05-21T12:42:38.103Z

In Brief: Making yourself happy is not best achieved by having true beliefs, primarily because the contribution of true beliefs to material comfort is a public good that you can free ride on, but the signaling benefits and happiness benefits of convenient falsehoods pay back locally, i.e. you personally benefit from your adoption of convenient falsehoods. The consequence is that many people hold beliefs about important subjects in order to feel a certain way or be accepted by a certain group. Widespread irrationality is ultimately an incentive problem.

Note: this article has been edited to take into account Tom McCabe, Vladimir_M and Morendil's comments1

In asking why the overall level of epistemic rationality in the world is low and what we can do to change that, it is useful to think about the incentives that many people face concerning the effects that their beliefs have on their quality of life, i.e. on how it is that beliefs make people win.

People have various real and perceived needs; of which our material/practical needs and our emotional needs are two very important subsets. Material/practical needs include adequate nutrition, warmth and shelter, clothing, freedom from crime or attack by hostiles, sex and healthcare. Our emotional needs include status, friendship, family, love, a feeling of belonging and perhaps something called "self actualization".

Data strongly suggests that when material and practical needs are not satisfied, people live extremely miserable lives (this can be seen in the happiness/income correlation—note that very low incomes predict very low happiness). The comfortable life that we lead in developed countries seems to mostly protect us from the lowest depths of anguish, and I would postulate that a reasonable explanation is that almost all of us never starve, die of cold or get killed in violence.

The comfort that we experience (in the developed world) due to our modern technology is very much a product of the analytic-rational paradigm. That is to say a tradition of rational, analytic thinking stretching back through Watson & Crick, Bardeen, Einstein, Darwin, Adam Smith, Newton, Bacon, etc, is a crucial (necessary, and "nearly" sufficient) reason for our comfort.

However, that comfort is given roughly equally to everyone and is certainly not given preferentially to the kind of person who most contributed causally to it ha...
Chicago Meetup
by Airedale — 2010-05-20T20:42:25.049Z

Hey Chicagoans and any Midwesterners from further afield who would like to join us, let’s start building a vibrant Less Wrong community here in the Windy City!

Steven0461 and I are proposing the first ever Less Wrong meetup in Chicago. The meet-up will be held at 2 pm on June 6 at the C-Shop in Hyde Park on the University of Chicago campus, which is located on the South Side of Chicago. The address is 5706 S. University Ave. Here is a map of the relevant part of the University of Chicago; the C-Shop is in the Reynolds Club building. We will have a Less Wrong sign on the table so you can identify us.

Steven and I have both been Visiting Fellows at SIAI, lived at the SIAI house, and attended the Bay Area Less Wrong meetups, and we’re excited about introducing Less Wrong meetups to the great city of Chicago.

Please comment if you plan to attend or if you would like to propose an alternative date, time, or location.

Edited to add a link to the related Google Group.

Edited to add final meeting place and details.
Development of Compression Rate Method
by Daniel_Burfoot — 2010-05-20T17:11:34.085Z

Summary: This post provides a brief discussion of the traditional scientific method, and mentions some areas where the method cannot be directly applied. Then, through a series of thought experiments, a set of minor modifications to the traditional method are presented. The result is a refined version of the method, based on data compression.

Related to: Changing the Definition of Science, Einstein's Arrogance, The Dilemma: Science or Bayes?

ETA: For those who are familiar with notions such as Kolmogorov Complexity and MML, this piece may have a low ratio of novelty:words. The basic point is that one can compare scientific theories by instantiating them as compression programs, using them to compress a benchmark database of measurements related to a phenomenon of interest, and comparing the resulting codelengths (taking into account the length of the compressor itself).

Notes on Traditional Method

This post proposes a refined version of the scientific method which, it will be argued later, is more directly applicable to the problems of interest in artificial intelligence. Before doing so, it is worth briefly examining the traditional method and the circumstances in which it can be applied. The scientific method is not an exact procedure, but a qualitative statement of it goes roughly as follows:

Observe a natural phenomenon.

Develop a theory of that phenomenon.

Use the theory to make a prediction.

Test the prediction experimentally.

A full discussion of the philosophical significance of the scientific method is beyond the scope of this post, but some brief remarks are in order. The power of the scientific method is in the way it links theory with experimental observation; either one of these alone is worthless. The long checkered intellectual history of humanity clearly shows how rapidly pure theoretical speculation goes astray when it is not tightly constrained by an external guiding force. Pure experimental investigation, in contrast, is of limited value because of the vast number of possible configurations of objects. To make predictions solely on the basis of experimental data, it would be necessary to exhaustively test each configuration.

As articulated in the above list, the goal of the method appears to be the verification of a single theory. This is a bit misleading; in reality the goal of the method is to facilitate selection betw...