trentmkelly/LessWrong-43k huggingface dataset:
How to test your mental performance at the moment?
by taw — 2009-11-23T18:35:47.136Z

We all have our good days and our bad days. Due to insufficient sleep, illness, stress, distractions, and many other causes we often find ourselves far below our usual levels of mental performance. When we find ourselves in such a state, it's not really worth putting effort in doing many tasks, like programming or long term planning - as quality will suffer a lot.

The problem is - other than observing deterioration of results, I have no idea if I'm in such a state or not. I cannot be sure if it's also true for others, but I had to find out a few tests of what's my mental performance at the moment. Tests that are deeply flawed, so I'd request better if there are any. I also cannot predict my mental state in advance, as my life isn't terribly regular.

The most reliable test I found, and by accident, was fighting bots on a certain Quake 3 map - me vs 10 or so highest difficulty bots. The challenge was to get 50 frags without dying. As the map was huge and full of power ups, it wasn't really that difficult as long as I could maintain full alertness for 10-15 minutes - but if I was tired or distracted, I would invariably fail. This test was unfortunately extremely slow.

Another test would be to go to goproblems, and do a few random problems at proper difficulty level. If I could think right, I would do most of them, if I was tired, I would fail almost 100%. This didn't test alertness, I guess it would be best described as short term memory test, as that's what used for game tree exploration. Unfortunately what's the proper difficulty varies a lot with how much go I played recently, so it needs to be recalibrated.

One more test would be to go to some decent online IQ test like this one. My results on such test would suffer a lot if I was sleepy or tired. The main problem is that such tests cannot repeated too often, or I'd just remember the answers.

So these are three ways to test how well my mind functions at the moment, all testing something different, and all flawed in one way or another.

How do you test yourself?
In conclusion: in the land beyond money pumps lie extreme events
by Stuart_Armstrong — 2009-11-23T15:03:05.628Z

In a previous article I've demonstrated that you can only avoid money pumps and arbitrage by using the von Neumann-Morgenstern axioms of expected utility. I argued in this post that even if you're not likely to face a money pump on one particular decision, you should still use expected utility (and sometimes expected money), because of the difficulties of combining two decision theories and constantly being on the look-out for which one to apply.

Even if you don't care about (weak) money pumps, expected utility sneaks in under much milder conditions. If you have a quasi-utility function (i.e. you have an underlying utility function, but you also care about the shape of the probability distribution), then this post demonstrates that you should generally stick with expected utility anyway, just by aggregating all your decisions.

So the moral of looking at money pumps, arbitrage and aggregation is that you should use expected utility for nearly all your decisions.

But the moral says exactly what it says, and nothing more. There are situations where there is not the slightest chance of you being money-pumped, or of aggregating enough of your decisions to achieve a narrow distribution. One-shot versions of Pascal's mugging, the Lifespan Dilemma, utility versions of the St Petersburg paradox, the risk to humanity of a rogue God-AI... Your behaviour on these issues is not constrained by money-pump considerations, nor should you behave as if they were, or as if expected utility had some magical claim to validity here. If you expect to meet Pascal's mugger 3^^^3 times, then you have to use expected utility; but if you don't, you don't.

In my estimation, the expected utility for the singularity institute's budget grows much faster than linearly with cash. But I would be most disappointed if the institute sunk all its income into triple-rollover lottery tickets. Expected utility is ultimately the correct decision theory; but if you most likely don't live to see that ultimately, then this isn't relevant.

In these extreme events, I'd personally advocate a quasi-utility function along with a decision theory that penalises monstrously large standard deviations, as long as these are rare. This solves all the examples above to my satisfaction, and can easily be tweaked to merge gracefully into expected utility as the number of extreme events rises to the point where they are no l...
Rational lies
by Alex Flint — 2009-11-23T03:32:08.789Z

If I were sitting opposite a psychopath who had a particular sensitivity about ants, and I knew that if I told him that ants have six legs then he would jump up and start killing the surrounding people, then it would be difficult to justify telling him my wonderful fact about ants, regardless of whether I believe that ants really have six legs or not.

Or suppose I knew my friend's wife was cheating on him, but I also knew that he was terminally ill and would die within the next few weeks. The question of whether or not to inform him of my knowledge is genuinely complex, and the truth or falsity of my knowledge about his wife is only one factor in the answer. Different people may disagree about the correct course of action, but no-one would claim that the only relevant fact is the truth of the statement that his wife is cheating on him.

This is all a standard result of expected utility maximization, of course. Vocalizing or otherwise communicating a belief is itself an action, and just like any other action it has a set of possible outcomes, to which we assign probabilities as well as some utility within our value coordinates. We then average out the utilities over the possible outcomes for each action, weighted by the probability that they will actually happen, and choose the action that maximizes this expected utility. Well, that's the gist of the situation, anyway. Much has been written on this site about the implications of expected utility maximization under more exotic conditions such as mind splitting and merging, but I'm going to be talking about more mundane situations, and the point I want to make is that beliefs are very different objects from the act of communicating those beliefs.

This distinction is particularly easy to miss as the line between belief and communication becomes subtler. Suppose that a friend of mine has built a wing suit and is about to jump off the empire state building with the belief that he will fly gracefully through the sky. Since I care about my friend's well-being I try to explain to him the concepts of gravity and aerodynamics, and the effect it will have on him if he launches himself from the building. Examining my decision in detail, I have placed a high probability on his death if he jumps off the building, and calculated that, since I value his well-being, my expected utility would not be maximized by him making t...
Calibration for continuous quantities
by Cyan — 2009-11-21T04:53:32.443Z

Related to: Calibration fail, Test Your Calibration!

Around here, calibration is mostly approached on a discrete basis: for example, the Technical Explanation of Technical Explanations talks only about discrete distributions, and the commonly linked tests and surveys are either explicitly discrete or offer only coarsely binned probability assessments. For continuous distributions (or "smooth" distributions over discrete quantities like dates of historical events, dollar amounts on the order of hundreds of thousands, populations of countries, or any actual measurement of a continuous quantity), we can apply a finer-grained assessment of calibration.

The problem of assessing calibration for continuous quantities is that our distributions can have very dissimilar shapes, so there doesn't seem to be a common basis for comparing one to another. As an example, I'll give some subjective (i.e., withdrawn from my nether regions) distributions for the populations of two countries, Canada and Botswana. I live in Canada, so I have years of dimly remembered geography classes in elementary school and high school to inform my guess. In the case of Botswana, I have only my impressions of the nation from Alexander McCall Smith's excellent No. 1 Ladies' Detective Agency series and my general knowledge of Africa.

For Canada's population, I'll set my distribution to be a normal distribution centered at 32 million with a standard deviation of 2 million. For Botswana's population, my initial gut feeling is that it is a nation of about 2 million people. I'll put 50% of my probability mass between 1 and 2 million, and the other 50% of my probability mass between 2 million and 10 million. Because I think that values closer to 2 million are more plausible than values at the extremes, I'll make each chunk of 50% mass a right-angle triangular distribution. Here are plots of the probability densities:

(These distributions are pretty rough approximations to my highest quality assessments. I don't hold, as the above normal distribution implies, that my probability that the population of Canada is less than 30 million is 16%, because I'm fairly sure that's what it was when I was starting university; nor would I assign a strictly nil chance to the proposition that Botswana's population is outside the interval from 1 million to 10 million. But the above distributions will do for ...
The One That Isn't There
by Annoyance — 2009-11-20T20:10:11.447Z

Q: What's the most important leg of a three-legged stool?

A: The one that isn't there.

- traditional joke-riddle

A specific neurological lesion can sometimes damage or impair specific neurological functions without touching others. In the condition famously known as "Ondine's Curse", for example, automatic control of breathing is destroyed while conscious control remains, so that without modern medical intervention nerve-damaged patients can survive only as long as they can remain awake. Such conditions are nevertheless unusual exceptions to the more general principle that complex, recently-developed, and 'meta'-functions (those that monitor and control others) are first to be impaired and lost when the nervous system is stressed, damaged, or altered.

Demonstrations of this principle can be found by examining such phenomena as reversion under stress, oxygen deprivation, sleep deprivation, and various sorts of poisoning - most especially drugs with a gradual effect on nervous function. The primary reason it is considered necessary to have designated drivers who refrain from consumption of alcohol is that drinkers frequently underestimate the degree to which they're affected by alcohol. Long before slowed reflexes and grossly impaired judgment become evident, the cognitive functions responsible for self-evaluation are dulled, and self-control diminished. A drinker who believes that they're capable of driving safely may or may not be correct, even if their judgments would normally be trustworthy. Similar effects are found with other types of intoxication - people who say that they drive better after smoking marijuana have been shown to in fact drive more poorly. The more demanding and complicated the mental task is, the more likely it will be disrupted by any interfering factor, leading to poor performance.

The natural human's an animal without logic. Your projections of logic onto all affairs is unnatural, but suffered to continue for its usefulness. You're the embodiment of logic--a Mentat. Yet, your problem solutions are concepts that, in a very real sense, are projected outside yourself, there to be studied and rolled around, examined from all sides."
"You think now to teach me my trade?" he asked, and he did not try to hide the disdain in his voice.
"The finest Mentats have a healthy respect for

...
Request For Article: Many-Worlds Quantum Computing
by pre — 2009-11-19T23:31:46.859Z

Through a path more tortuous than is worth describing, I ended up talking to friends about the quantum effects which are exploited by photosynthesis. There's an article describing the topic we were talking about here.

The article describes how quantum effects allow the molecular machinary of the chloroplasts to "simultaneously sample all the potential energy pathways and choose the most efficient one."

Which is essentially how Quantum Computing is usually described in the press too, only we get to set what we mean by "most efficient" to be "best solution to this problem".

Since I usually find myself arguing that "there is no wave collapse," the conversation has lead me to trying to picture how this "exploring" can happen unless there is also some "pruning" at the end of it.

Of course even in the Copenhagen Interpretation "wave collapse" always happens in accordance with the probabilities described by the wave function, so presumably the system is engineered in such a way as to make that "most efficient" result the most probable according to those equations.

It's not somehow consistently picking results from the far end of the bell-curve of probable outcomes. It's just engineered so that bell-curve is centred on the most efficient outcomes.

There's no 'collapse', it's just that the system has been set up in such a way that the most likely and therefore common universes have the property that the energy is transferred.

Or something. Dunno.

Can someone write an article describing how quantum computing works from a many-words perspective rather than the explore-and-then-prune perspective that it seems every press article I've ever read on the topic uses?

Pretty please?

I'd like to read that.
Why is poor communication popular?
by KatjaGrace — 2009-11-18T01:08:53.000Z

A great insight in one sentence seems obvious, no matter how much of history how many people have spent not coming up with it. The same insight alluded to and digressed from for hours on end seems like a fantastic mountain of understanding. Why is this? I think Paul Gowder’s explanation for people liking bad books probably extends to partially explain:

Why do people read bad books…[and] why do so many…end up praising them? …

1. The sunk cost fallacy. You get fifty, a hundred pages into Atlas Shrugged or something and you’ve bled so much — you’ve invested so much into getting through this book, tortured yourself with so much bad writing and so many stupid ideas! How horrible would it be to waste all that effort! Better grind on and finish. Or so we tell ourselves. Because we’re irrational.

2. Cognitive dissonance. You’ve read all of Of Grammatology! Holy shit that was unpleasant…You’re not sure whether you actually learned anything enlightening, or whether old Jacques was just spitting jive. But wait! You’re a rational person! You’d be a fool if you’d spent a hundred hours and endless tears trying to make sense of that stuff and it turned out to be nonsense. Therefore, it must be very wise and you should defend it and demand others read it! Or so we tell ourselves. Because we’re irrational.

Hat tip to Mike Blume. I’ll add:

3. Less concise works can easily be designed to cheat quality heuristics. You are always better off guessing whether a work was good or bad than admitting you didn’t understand it well and can’t remember most of it, because that does not distinguish you from the stupid people who didn’t understand or remember it because they don’t understand or remember anything. If you are going to guess, you use heuristics. Many of the same things that make writing less comprehensible also lead people to guess it is insightful: complexity, length, difficult words. If you can’t follow well enough to confidently compress it into the one sentence version you would have thought obvious, you will likely guess that it contains more than one sentence worth of interesting content.
A Less Wrong singularity article?
by Kaj_Sotala — 2009-11-17T14:15:52.346Z

Robin criticizes Eliezer for not having written up his arguments about the Singularity in a standard style and submitted them for publication. Others, too, make the same complaint: the arguments involved are covered over such a huge mountain of posts that it's impossible for most outsiders to seriously evaluate them. This is a problem for both those who'd want to critique the concept, and for those who tentatively agree and would want to learn more about it.

Since it appears (do correct me if I'm wrong!) that Eliezer doesn't currently consider it worth the time and effort to do this, why not enlist the LW community in summarizing his arguments the best we can and submit them somewhere once we're done? Minds and Machines will be having a special issue on transhumanism, cognitive enhancement and AI, with a deadline for submission in January; that seems like a good opportunity for the paper. Their call for papers is asking for submissions that are around 4000 to 12 000 words.

The paper should probably

Briefly mention some of the previous work about AI being near enough to be worth consideration (Kurzweil, maybe Bostrom's paper on the subject, etc.), but not dwell on it; this is a paper on the consequences of AI.

Devote maybe little less than half of its actual content to the issue of FOOM, providing arguments and references for building the case of a hard takeoff.

Devote the second half to discussing the question of FAI, with references to e.g. Joshua Greene's thesis and other relevant sources for establishing this argument. Carl Shulman says SIAI is already working on a separate paper on this, so it'd be better for us to concentrate merely on the FOOM aspect.

Build on the content of Eliezer's various posts, taking their primary arguments and making them stronger by reference to various peer-reviewed work.

Include as authors everyone who made major contributions to it and wants to be mentioned; certainly make (again, assuming he doesn't object) Eliezer as the lead author, since this is his work we're seeking to convert into more accessible form.

I have created a wiki page for the draft version of the paper. Anyone's free to edit.
Efficient prestige hypothesis
by taw — 2009-11-16T22:25:01.011Z

There's a contrarian theory presented by Robin that people go to highly reputable schools, visit highly reputable hospitals, buy highly reputable brands etc. to affiliate with high status individuals and institutions.

But what would a person who completely didn't care about such affiliations do? Pretty much the same thing. Unless you know a lot about schools, hospitals, and everything else, you're better off simply following prestige as proxy for quality (in addition to price and all the other usual criteria). There's no denying that prestige is better indicator of quality than random chance - the question is - is it the best we can do?

It's possible to come up with alternative measures, which might correlate with quality too, like operation success rates for hospitals, graduation rates for schools etc. But if they really indicated quality that well, wouldn't they be simply included in institution's prestige, and lose their predictive status? The argument is highly analogous to one for efficient market hypothesis (or to some extent with Bayesian beauty contest with schools, as prestige might indicate quality of other students). Very often there are severe faults with alternative measures, like with operation success rates without correcting for patient demographics.

If you postulate that you have better indicator of quality than prestige, you need to do some explaining. Why is it not included in prestige already? I don't propose any magical thinking about prestige, but we shouldn't be as eager to throw it away completely as some seem to be.
Why (and why not) Bayesian Updating?
by Wei Dai — 2009-11-16T21:27:43.855Z

the use of Bayesian belief updating with expected utility maximization may be just an approximation that is only relevant in special situations which meet certain independence assumptions around the agent's actions.

— Steve Rayhawk

For those who aren't sure of the need for an updateless decision theory, the paper Revisiting Savage in a conditional world by Paolo Ghirardato might help convince you. (Although that's probably not the intention of the author!) The paper gives a set of 7 axioms, based on Savage's axioms, which is necessary and sufficient for an agent's preferences in a dynamic decision problem to be represented as expected utility maximization with Bayesian belief updating. This helps us see in exactly which situations Bayesian updating works and why. (In many other axiomatizations of decision theory, the updating part is left out, and only expected utility maximization is derived in a static setting.)

A key assumption is Axiom 7, which the author calls "Consequentialism". I won't try to reproduce the mathematical notation here (see the page numbered 88 in this ungated PDF), but here's the informal explanation given in the paper:

This axiom says that the preference conditional on non-null A should not depend
on how the strategy f behaves in the counterfactual states of Ac (in other words,
it should only depend on the truncation f|A).

This axiom is clearly violated in Vladmir Nesov's Counterfactual Mugging counter-example to Bayesian updating.

Another example that I used to motivate UDT involves indexical uncertainty. In Ghirardato's framework it's relatively easy to see what goes wrong when we try to apply it to indexical uncertainty. In that case, "states" in the formalism would have to be centered possible worlds, in other words an ordinary world-state plus a location. But if A above is a set of centered possible worlds, then after learning A, your preferences can still depend on how strategies behave in AC since elements of A and AC may belong to the same possible world.

If there is demand, I can try to give an informal/intuitive explanation of why Bayesian updating works (in the situations where it does). I was about to attempt that when I decided to do a Google search and found this paper.

P.S., I noticed a curiosity about Bayesian updating while thinking about it in the context of decision theory, and this seems like a good opportunity t...
BHTV: Yudkowsky / Robert Greene
by Eliezer Yudkowsky — 2009-11-16T20:26:09.545Z

Latest Bloggingheads up with Robert Greene, bestselling author of The 48 Laws of Power and most recently The 50th Law ("Fear nothing").

Excellent commentary/summary by Andy McKenzie here.

The most important piece of advice I got from The 50th Law was "always attack before you are ready".