Well, there's still intermittent fasting.

IF would get around

"The non-aging-related causes of death included monkeys who died while taking blood samples under anesthesia, from injuries or from infections, such as gastritis and endometriosis. These causes may not be aging-related as defined by the researchers, but they could realistically be adverse effects of prolonged calorie restrictions on the animals’ health, their immune system, ability to handle stress, physical agility, cognition or behavior."

and would also work well with the musings about variability and duration:

"From an evolutionary standpoint, he explained, mice who subsist on less food for a few years is analogous, in terms of natural selection, to humans who survive 20-year famines. But nature seldom demands that humans endure such conditions.

Similar conclusions were reached by Dr. Aubrey D.N.J. de Grey with the Department of Genetics at the University of Cambridge, UK. Species have widely evolved to be able to adapt to transient periods of starvation. “What has been generally overlooked is that the extent of the evolutionary pressure to maintain adaptability to a given duration of starvation varies with the frequency of that duration,” he said."

(Our ancestors most certainly did have to survive frequent daily shortfalls. Feast or famine.)

Where do you get that I thought I was wrong about CR? I'd like to lose weight but I had been aware for a while that the state of evidence on caloric restriction doing the purported job of extending lifespan in mammals was bad.

That's a dopey article. My council is to not get your diet advice from there.

the main hurdle in my experience is getting people over biases that cause them to think that the future is going to look mostly like the present. if you can get people over this then they do a lot of the remaining work for you.

I think of LessWrong from a really, really pragmatic viewpoint: it's like software patches for your brain to eliminate costly bugs. There was a really good illustration in the Allais mini-sequence - that is a literal example of people throwing away their money because they refused to consider how their brain might let them down.

Edit: Related to The Lens That Sees Its Flaws.

It shows you that there is really more to most things than meets the eye, but more often than not much less than you think. It shows you that even smart people can be completely wrong but that most people are not even wrong. It tells you to be careful in what you emit and to be skeptical of what you receive. It doesn't tell you what is right, it teaches you how to think and to become less wrong. And to do so is in your own self interest because it helps you to attain your goals, it helps you to achieve what you want. Thus what you want is to read and participate on LessWrong.

Behind a paywall

But freely available from one of the authors' website.

Basically, pigeons also start with a slight bias towards keeping their initial choice. However, they find it much easier to "learn to switch" than humans, even when humans are faced with a learning environment as similar as possible to that of pigeons (neutral descriptions, etc.). Not sure how interesting that is.

It makes the hurdle less likely to be before the fish stage, so more likely to be after the fish stage. While the biggest increase in probability is immediately after the fish stage, all subsequent stages are a more likely culprit now (especially as we could simply have missed fossils/their not have been formed for the post-fish stages).

Mars dried out a while ago. Finding fossils there would prove very little about the great filter - since they would probably be distant relatives of ours whose planet gave out on them (since the solar system is one big melting pot for life). Basically, it is a bad example.

Some googling around yielded a pdf about a controversial use of Bayes in court. The controversy seems to center around using one probability distribution on both sides of the equation. Lesser complaints include mixing in a frequentist test without a good reason.

One problem is that I just don't have enough "evidence" to make meaningful probability estimates. Another is that I'm only weakly aware of my own utility function.

Based on those two lucid observations, I'd say you're doing well so far.

There are some principles I used to weigh major life decisions. I'm not sure they are "rationalist" principles; I don't much care. They've turned out well for me.

Here's one of them: "having one option is called a trap; having two options is a dilemma; three or more is truly a choice". Think about the terms of your decision and generate as many different options as you can. Not necessarily a list of final choices, but rather a list of candidate choices, or even of choice-components.

If you could wave a magic wand and have whatever you wanted, what would be at the top of your list? (This is a mind-trick to improve awareness of your desires, or "utility function" if you want to use that term.) What options, irrespective of their downsides, give you those results?

Given a more complete list you can use the good old Benjamin Franklin method of listing pros and cons of each choice. Often this first step of option generation turns out sufficient to get you unstuck anyway.

It feels to me that rationalist principles are most useful in avoiding failure modes. But they're much less useful in coming up with new things you should do (as opposed to specifying things you shouldn't do).

...I don't suppose you can tell us what? I expect that if you could, you would have said, but thought I'd ask. It's difficult to work with this little.

I could toss around advices like "A lot of Major Life Decisions consist of deciding which of two high standards you should hold yourself to" but it's just a shot in the dark at this point.

A few principles that can help in such cases (major decision, very little direct data):

• Outside view. You're probably more similar to other people than you like to think. What has worked for them?
• Far vs Near mode: beware of generalizations when visualizing distant (more than a few weeks!) results of a choice. Consider what daily activities will be like.
• Avoiding oversimplified modeling: With the exceptions of procreation and suicide, there are almost no life decisions that are permanent and unchangeable.
• Shut up and multiply, even for yourself: Many times it turns out that minor-but-frequent issues dominate your happiness. Weight your pros/cons for future choices based on this, not just on how important something "should" be.

I am not that far in the sequences, but these are posts I would expect to come into play during Major Life Decisions. These are ordered by my perceived relevance and accompanied with a cool quote. (The quotes are not replacements for the whole article, however. If the connection isn't obvious feel free to skim the article again.)

To do better, ask yourself straight out: If I saw that there was a superior alternative to my current policy, would I be glad in the depths of my heart, or would I feel a tiny flash of reluctance before I let go? If the answers are "no" and "yes", beware that you may not have searched for a Third Alternative. ~ The Third Alternative

The moral is that the decision to terminate a search procedure (temporarily or permanently) is, like the search procedure itself, subject to bias and hidden motives. You should suspect motivated stopping when you close off search, after coming to a comfortable conclusion, and yet there's a lot of fast cheap evidence you haven't gathered yet - Web sites you could visit, counter-counter arguments you could consider, or you haven't closed your eyes for five minutes by the clock trying to think of a better option. You should suspect motivated continuation when some evidence is leaning in a way you don't like, but you decide that more evidence is needed - expensive evidence that you know you can't gather anytime soon, as opposed to something you're going to look up on Google in 30 minutes - before you'll have to do anything uncomfortable. ~ Motivated Stopping and Continuation

I suspect that a more powerful (and more difficult) method is to hold off on thinking of an answer. To suspend, draw out, that tiny moment when we can't yet guess what our answer will be; thus giving our intelligence a longer time in which to act. ~ Hold Off On Proposing Solutions

"Rationality" is the forward flow that gathers evidence, weighs it, and outputs a conclusion. [...] "Rationalization" is a backward flow from conclusion to selected evidence.
~ Rationalization

Your effectiveness as a rationalist is determined by whichever algorithm actually writes the bottom line of your thoughts. If your car makes metallic squealing noises when you brake, and you aren't willing to face up to the financial cost of getting your brakes replaced, you can decide to look for reasons why your car might not need fixing. ~ The Bottom Line

Hope that helps.

The dissolving the question mindset has actually served me pretty well as a TA - just bearing in mind the principle that you should determine what led to this particular confused bottom line is useful in correcting it afterwards.

I just came out of a tough Major Life Situation myself. The rationality 'tools' I used were mostly directed at forcing myself to be honest with myself, confronting the facts, not privileging certain decisions over others, recognizing when I was becoming emotional (and more importantly recognizing when my emotions were affecting my judgement), tracking my preferred choice over time and noticing correlations with my mood and pertinent events.

Overall, less like decision theory and more like a science: trying to cut away confounding factors to discover my true desire. Of course, sometimes knowing your desires isn't sufficient to take action, but I find that for many personal choices it is (or at least is enough to reduce the decision theory component to something much more manageable).

I'd start by asking whether the unknowns of the problem are primarily social and psychological, or whether they include things that the human intuition doesn't handle well (like large numbers).

If it's the former, then good news! This is basically the sort of problem your frontal cortex is optimized to solve. In fact, you probably unconsciously know what the best choice is already, and you might be feeling conflicted so as to preserve your conscious image of yourself (since you'll probably have to trade off conscious values in such a choice, which we're never happy to do).

In such a case, you can speed up the process substantially by finding some way of "letting the choice be made for you" and thus absolving you of so much responsibility. I actually like to flip a coin when I've thought for a while and am feeling conflicted. If I like the way it lands, then I do that. If I don't like the way it lands, well, I have my answer then, and in that case I can just disobey the coin!

(I've realized that one element of the historical success of divination, astrology, and all other vague soothsaying is that the seeker can interpret a vague omen as telling them what they wanted to hear— thus giving divine sanction to it, and removing any human responsibility. By thus revealing one's wants and giving one permission to seek them, these superstitions may have actually helped people make better decisions throughout history! That doesn't mean it needs the superstitious bits in order to work, though.)

If it's the latter case, though, you probably need good specific advice from a rational friend. Actually, that practically never hurts.

It's not anti-logical, it's rude logic. The point of Suber's paper is that at no point does the logically rude debater reason incorrectly from their premises, and yet we consider what they have done to be a violation of a code of etiquette.

I think they are legitimate objections, but ones that have been partially addressed in this community. I take the principle objection to be, "Bayesian rationality can't justify induction." Admittedly true (see for instance Eliezer's take). Albert ignores sophisticated responses (like Robin's) and doesn't make a serious effort to explain why his alternative doesn't have the same problem.

I considered putting that link here in the open thread after I read about it on Marginal Revolution, but I read the paper and found it weak enough to not really be worth a lengthy response.

What annoyed me about it is how Albert's title is "Why Bayesian Rationality Is Empty," and he in multiple places makes cute references to that title (e.g. "The answer is summarized in the paper’s title") without qualificaiton.

Then later, in a footnote, he mentions "In this paper, I am only concerned with subjective Bayesianism."

Seems like he should re-title his paper to me. He makes references to other critiques of objective Bayesianism, but doesn't engage them.

If you don't mind a slightly mathy article, I thought Legg & Hutter's Universal Intelligence was nice. It talks about machine intelligence, but I believe it applies to all forms of intelligence. It also addresses some of the points you made here.

If I were standing there catching the pencil and directing it to the spot on the floor, you wouldn't consider the pencil intelligent. The behavior observed is not pointing to the pencil in particular being intelligent.

Just my two cents.

I don't know anything about the concept of intelligence being defined as being able to pursue goals through complicated obstacles. If I had to guess at the missing piece it would probably be some form of self-referential goal making. Namely, this takes the form of the word, "want." I want to go to this spot on the floor. I can ignore a goal but it is significantly harder to ignore a want.

At some point, my wants begin to dictate and create other wants. If I had to start pursing a definition of intelligence, I would probably start here. But I don't know anything about the field so this could have already been tried and failed.

Some food for philosophical thought, an oil drop that "solves" a maze.

TL;DR it follows a chemical gradient due to it changing surface tension.

I'd read something on the intentional stance.

So if something is capable, contrary to expectations, of achieving a constant state despite varying conditions, it's probably intelligent?

I guess that in space, everything is intelligent.

You are talking about control systems.

A control system has two inputs (called its "perception" and "reference") and one output. The perception is a signal coming from the environment, and the output is a signal that has an effect on the environment. For artificial control systems, the reference is typically set by a human operator; for living systems it is typically set within the organism.

What makes it a control system is that firstly, the output has an effect, via the environment, on the perception, and secondly, the feedback loop thus established is such as to cause the perception to remain close to the reference, in spite of all other influences from the environment on that perception.

The answers to your questions are:

1. A "goal" is the reference input of a control system.

2. An "obstacle" is something which, in the absence of the output of the control system, would cause its perception to deviate from its reference.

3. "Complicated" means "I don't (yet) understand this."

Suggestions for readings.

And a thought: "Romeo wants Juliet as the filings want the magnet; and if no obstacles intervene he moves towards her by as straight a line as they. But Romeo and Juliet, if a wall be built between them, do not remain idiotically pressing their faces against its opposite sides like the magnet and the filings with the card. Romeo soon finds a circuitous way, by scaling the wall or otherwise, of touching Juliet's lips directly. With the filings the path is fixed; whether it reaches the end depends on accidents. With the lover it is the end which is fixed, the path may be modified indefinitely."

-- William James, "The Principles of Psychology"

Personally, I'm a big fan of Haskell. It will make your brain hurt, but that's part of the point -- it's very good at easily creating and using mathematically sound abstractions. I'm not a big fan of Lua, though it's a perfectly reasonable choice for its niche of embeddable scripting language. I have no experience with Processing. The most commonly recommended starting language is python, and it's not a bad choice at all.

Processing and Lua seem pretty exotic to me. How did you hear of them? If you know people who use a particular language, that's a pretty good reason to choose it.

Even if you don't have a goal in mind, I would recommend choosing a language with applications in mind to keep you motivated. For example, if (but only if) you play wow, I would recommend Lua; or if the graphical applications of Processing appeal to you, then I'd recommend it. If you play with web pages, javascript...

At least that's my advice for one style of learning, a style suggested by your mention of those two languages, but almost opposite from your "Nevertheless, I want to start from the very beginning," which suggests something like SICP. There are probably similar courses built around OCaml. The proliferation of monad tutorials suggests that the courses built around Haskell don't work. That's not to disagree with wnoise about the value of Haskell either practical or educational, but I'm skeptical about it as an introduction.

ETA: SICP is a textbook using Scheme (Lisp). Lisp or OCaml seems like a good stepping-stone to Haskell. Monads are like burritos.

As mentioned in another comment, the best introduction to programming is probably SICP. I recommend going with this route, as trying to learn programming from language-specific tutorials will almost certainly not give you an adequate understanding of fundamental programming concepts.

After that, you will probably want to start dabbling in a variety of programming styles. You could perhaps learn some C for imperative programming, Java for object-oriented, Python for a high-level hybrid approach, and Haskell for functional programming as starters. If you desire more programming knowledge you can branch out from there, but this seems to be a good start.

Just keep in mind that when starting out learning programming, it's probably more important to dabble in as many different languages as you can. Doing this successfully will enable you to quickly learn any language you may need to know. I admit I may be biased in this assessment, though, as I tend to get bored focusing on any one topic for long periods of time.

I recommend Haskell (more fun) or Ruby (more mainstream).

In an amazing coincidence, many of the suggestions you get will be the suggester's current favorite language. Many of these recommendations will be esoteric or unpopular languages. These people will say you should learn language X first because of the various features language X. They'll forget that they did not learn language X first, and while language X is powerful, it might not be easy to set up a development environment. Tutorials might be lacking. Newbie support might be lacking. Etc.

Others have said this but you can't hear it enough: It is not mandatory to learn computer programming. If you force yourself, you probably won't enjoy it.

So, what language should you learn first? Well the answer is... (drumroll) it depends! Mostly, it depends on what you are trying to do. (Side note: You can get a lot of help on mailing lists or IRC if you say, "I'm trying to do X." instead of, "I'm having a problem getting feature blah blah blah to work.")

I have no particular goal in mind that demands a practical orientation. My aim is to acquire general knowledge of computer programming to be used as starting point that I can build upon.

I paused after reading this. The main way people learn to program is by writing programs and getting feedback from peers/mentors. If you're not coding something you find interesting, it's hard to stay motivated for long enough to learn the language.

My advice is to learn a language that a lot of people learn as a first language. You'll be able to take advantage of tutorials and support geared toward newbies. You can always learn "cooler" languages later, but if you start with something advanced you might give up in frustration. Common first languages in CS programs are Java and C++, but Python is catching on pretty quickly. It also helps if your first language is used by people you already know. That way they'll be able to mentor/advise you.

Finally, I should give some of my background. I've been writing code for a while. I write code for work and leisure. My first language was QBasic. I moved on to C, C++, TI-BASIC, Perl, PHP, Java, C#, Ruby, and some others. I've played with but don't really know Lisp, Lua, and Haskell. My favorite language right now is Python, but I'm probably still in the honeymoon phase since I've been using it for less than a year.

Argh, see what I said at the start? I recommended Python and my favorite language is currently Python!

I think the path outlined in ESR's How to Become a Hacker is pretty good. Python is in my opinion far and away the best choice as a first language, but Haskell as a second or subsequent language isn't a bad idea at all. Perl is no longer important; you probably need never learn it.

My first language was, awfully enough, GW-Basic. It had line numbers. I don't recommend anything like it.

My first real programming language was Perl. Perl is... fun. ;)

I'm thinking about starting with Processing and Lua. What do you think?

Those two seem great, Lua in particular seems to match exactly the purpose you describe.

I'd weakly recommend Python, it's free, easy enough, powerful enough to do simple but useful things (rename and reorganize files, extract data from text files, generate simple html pages ...),is well-designed and has features you'll encounter in other languages (classes, functional programming ...), and has a nifty interactive command line in which to experiment quickly. Also, some pretty good websites run on it.

But a lot of those advantages apply to languages like Ruby.

If you want to go into more exotic languages, I'd suggest Scheme over Haskell, it seems more beginner-friendly to me.

It mostly depends on what occasions you'll have of using it : if you have a website, Javascript might be better; If you like making game mods, go for lua. It also depends of who you know that can answer questions. If you have a good friend who's a good teacher and a Java expert, go for Java.

Interesting article, but the title is slightly misleading. What he seems to be complaining are people who mistake picking up a superficial overview of a topic for actually learning a subject, but I rather doubt they'd learn any more in school than by themselves.

Learning is what you make of it; getting a decent education is hard work, whether you're sitting in a lecture hall with other students, or digging through books alone in your free time.

What probability should you assign as a Bayesian to the answer of a yes/no question being yes if you have absolutely no clue about what the answer should be?

If you truly have no clue, .5 yes and .5 no.

For example, let's say you are suddenly sent to the planet Progsta and a Sillpruk comes and asks you whether the game of Doldun will be won by the team Strigli.

Ah, but here you have some clues, which you should update on, and knowing how is much trickier. One clue is that the unkown game of Doldun could possibly have more than 2 teams competing, of which only 1 could win, and this should shift the probabilities in favor of "No". How much? Well that depends on your probability distribution for an unknown game to have n competing teams. Of course, there may be other clues that should shift the probabilty towards "yes".

1: If you have no information to support either alternative more than the other, you should assign them both equal credence. So, fifty-fifty. Note that yes-no questions are the easiest possible case, as you have exactly two options. Things get much trickier once it's not obvious what things should be classified as the alternatives that should be considered equally plausible.

Though I would say that in this situation, the most rational approach would be to tell the Sillpruk, "I'm sorry, I'm not from around here. Before I answer, does this planet have a custom of killing people who give the wrong answer to this question, or is there anything else I should be aware of before replying?"

2: This depends a lot how we define a rationalist and a Bayesian. A question like "is the Bible literally true" could reveal a lot of irrational people, but I'm not certain of the amount of questions that'd need to be asked before we could know for sure that they were irrational. (Well, since 1 and 0 aren't probabilities, the strict answer to this question is "it can't be done", but I'm assuming you mean "before we know with such a certainty that in practice we can say it's for sure".)

This is somewhat similar to the question I asked in Reacting to Inadequate Data. It was hit with a -3 rating though... so apparently it wasn't too useful.

The consensus of the comments was that the correct answer is .5.

Also of note is Bead Jar Guesses and its sequel.

For two, can I just have an extended preface that describes a population, an infection rate for some disease and a test with false positivity rates and false negativity rates and see if the person gives me the right answer?

For #2, I don't see how you could ever be completely sure the other was rationalist or Bayesian, short of getting their source code; they could always have one irrational belief hiding somewhere far from all the questions you can think up.

In practice, though, I think I could easily decide within 10 questions whether a given (honest) answerer is in the "aspiring rationalist" cluster and/or the "Bayesian" cluster, and get the vast majority of cases right. People cluster themselves pretty well on many questions.

Can people ROT13 their answers so I get a chance to solve this on my own? Or will there be too much math for ROT13 to work well?

Do we choose a probability p the machine picks A, or does the machine start with a probability p, which we adjust to p+q chance it picks A?

Smartass answer: use two computers, one for each of the keys. Computer time is cheap these days. If you don't have two computers, rent computation time from a cloud.

hidden answer

To venture a guess: their true objection was probably "you didn't follow the rules for dealing cards". And, to be fair to your friends, those rules were designed to defend honest players against card sharps, which makes violations Bayesian grounds to suspect you of cheating.

An important element of it being fair for you to cut the deck in the middle of dealing, which your friends may not trust, is that you do so in ignorance of who it will help and who it will hinder. By cutting the deck, you have explicitly made and acted on a choice (it is far less obvious when you choose not to cut the deck, the default expected action), and this causes your friends to worry that the choice may have been optimized for interests other than their own.

As you note, regular poker and poker with an extra cut mid-deal are completely isomorphic. In a professional game you would obviously care, because the formality of the shuffle and deal are part of a tradition to instill trust that the deck isn't rigged. For a casual game, where it is assumed no one is cheating, then, unless you're a stickler for tradition, who cares? Your friends are wrong. We have two different pointers pointing to the same thing, and they are complaining because the pointers aren't the same, even though all that matters is what those pointers point to. It would be like complaining if you tried to change the name of Poker to Wallaboo mid-deal.

To modify RobinZ's hypothesis:

Rather than focusing on any Bayesian evidence for cheating, let's think like evolution for a second: how do you want your organism to react when someone else's voluntary action changes who receives a prize? Do you want the organism to react, on a gut level, as if the action could have just as easily swung the balance in their favor as against them? Or do you want them to cry foul if they're in a social position to do so?

Your friends' response could come directly out of that adaptation, whatever rationalizations they make for it afterwards. I'd expect to see the same reaction in experiments with chimps.

It's a side effect.

Yes, they were being irrational in this case. But the heuristics they were using are there for good reason. Suppose they had money coming to them and you swooped in and took it away before it could reach them, they would be rational to object, right? That's why those heuristics are there. In practice the trigger conditions for these things are not specified with unlimited precision, and pure but interruptible random number generators are not common in real life, so the trigger conditions harmlessly spill over to this case. But the upshot is that they were irrational as a side effect of usually rational heuristics.

Vote this comment up if you think I suck at metaphors and should avoid them like the plague.

Vote this comment up if you think only crystal metaphors in particular suck, while light metaphors are nifty.

Vote this comment up if it's okay to use metaphors but I should tone it way down.

Vote this comment up if you want to revisit the issue after I've actually posted the first luminosity sequence post, to see how it's going then.

Karma balance. Vote down if you voted up another comment in the poll.

Note: in such cases, you need to offer some options that aren't self-deprecating, in case some of your readers liked the crystal metaphors just fine.

(Er, although I personally fall into the category of your third option.)

EDIT: ADDRESSED BY EDIT TO ABOVE

Well to begin with I don't think a person needs to know even close to that amount of information to be justified in their vote and, moreover, a person can know all of that information and still vote for stupid reasons. Say I am an uneducated black person living in the segregation era in a southern American state. All I know is one candidate supports passing a civil rights bill on my behalf and the other is a bitter racist. I vote for the non-racist. Given this justification for my vote why should my vote be reduced to almost nothing because I don't know anything else about the candidates, economics, political science etc.?

On the other hand, I could be capable of answering every question on that test correctly and still believe that the book is a lie and Barack Obama is really a secret Muslim. I can't tell you the number of people I've met who have taken Poli Sci, Econ (even four semsesters worth!), history and can recite candidate talking points verbatim who are still basically clueless about everything that matters.