Zombies Redacted

33 Eliezer_Yudkowsky 02 July 2016 08:16PM

I looked at my old post Zombies! Zombies? and it seemed to have some extraneous content.  This is a redacted and slightly rewritten version.

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You Can Face Reality

53 Eliezer_Yudkowsky 09 August 2007 01:46AM

What is true is already so.
Owning up to it doesn't make it worse.
Not being open about it doesn't make it go away.
And because it's true, it is what is there to be interacted with.
Anything untrue isn't there to be lived.
People can stand what is true,
for they are already enduring it.
Eugene Gendlin

(Hat tip to Stephen Omohundro.)

 

Part of the Letting Go subsequence of How To Actually Change Your Mind

Next post: "The Meditation on Curiosity"

Previous post: "The Proper Use of Doubt"

Why startup founders have mood swings (and why they may have uses)

47 AnnaSalamon 09 December 2015 06:59PM

(This post was collaboratively written together with Duncan Sabien.)

 

Startup founders stereotypically experience some pretty serious mood swings.  One day, their product seems destined to be bigger than Google, and the next, it’s a mess of incoherent, unrealistic nonsense that no one in their right mind would ever pay a dime for.  Many of them spend half of their time full of drive and enthusiasm, and the other half crippled by self-doubt, despair, and guilt.  Often this rollercoaster ride goes on for years before the company either finds its feet or goes under.

 

 

 

 

 

Well, sure, you might say.  Running a startup is stressful.  Stress comes with mood swings.  

 

But that’s not really an explanation—it’s like saying stuff falls when you let it go.  There’s something about the “launching a startup” situation that induces these kinds of mood swings in many people, including plenty who would otherwise be entirely stable.

 

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[LINK] Scott Aaronson: Common knowledge and Aumann's agreement theorem

13 gjm 17 August 2015 08:41AM

The excellent Scott Aaronson has posted on his blog a version of a talk he recently gave at SPARC, about Aumann's agreement theorem and related topics. I think a substantial fraction of LW readers would enjoy it. As well as stating Aumann's theorem and explaining why it's true, the article discusses other instances where the idea of "common knowledge" (the assumption that does a lot of the work in the AAT) is important, and offers some interesting thoughts on the practical applicability (if any) of the AAT.

(Possibly relevant: an earlier LW discussion of AAT.)

What are "the really good ideas" that Peter Thiel says are too dangerous to mention?

2 James_Miller 12 April 2015 09:07PM

TYLER COWEN: Peter, tell me something that’s true that everyone agrees with you on.

 

PETER THIEL: Well there are lots of things that are true that everyone agrees with me on. I think for example even this idea that the university system is somewhat screwed up and somewhat broken at this point....You know, the ideas that are really controversial are the ones I don’t even want to tell you. I want to be more careful than that. I gave you these halfway, in-between ideas that are a little bit edgier.

But I will also go a little bit out on a limb: I think the monopoly idea, that the goal of every successful business is to have a monopoly, that’s on the border of what I want to say. But the really good ideas are way more dangerous than that.

Full interview.  HT Quora.

 

What are some good answers and your guess as to his answer?  Please exclude issues relating to race and gender.

16 types of useful predictions

90 Julia_Galef 10 April 2015 03:31AM

How often do you make predictions (either about future events, or about information that you don't yet have)? If you're a regular Less Wrong reader you're probably familiar with the idea that you should make your beliefs pay rent by saying, "Here's what I expect to see if my belief is correct, and here's how confident I am," and that you should then update your beliefs accordingly, depending on how your predictions turn out.

And yet… my impression is that few of us actually make predictions on a regular basis. Certainly, for me, there has always been a gap between how useful I think predictions are, in theory, and how often I make them.

I don't think this is just laziness. I think it's simply not a trivial task to find predictions to make that will help you improve your models of a domain you care about.

At this point I should clarify that there are two main goals predictions can help with:

  1. Improved Calibration (e.g., realizing that I'm only correct about Domain X 70% of the time, not 90% of the time as I had mistakenly thought). 
  2. Improved Accuracy (e.g., going from being correct in Domain X 70% of the time to being correct 90% of the time)

If your goal is just to become better calibrated in general, it doesn't much matter what kinds of predictions you make. So calibration exercises typically grab questions with easily obtainable answers, like "How tall is Mount Everest?" or  "Will Don Draper die before the end of Mad Men?" See, for example, the Credence Game, Prediction Book, and this recent post. And calibration training really does work.

But even though making predictions about trivia will improve my general calibration skill, it won't help me improve my models of the world. That is, it won't help me become more accurate, at least not in any domains I care about. If I answer a lot of questions about the heights of mountains, I might become more accurate about that topic, but that's not very helpful to me.

So I think the difficulty in prediction-making is this: The set {questions whose answers you can easily look up, or otherwise obtain} is a small subset of all possible questions. And the set {questions whose answers I care about} is also a small subset of all possible questions. And the intersection between those two subsets is much smaller still, and not easily identifiable. As a result, prediction-making tends to seem too effortful, or not fruitful enough to justify the effort it requires.

But the intersection's not empty. It just requires some strategic thought to determine which answerable questions have some bearing on issues you care about, or -- approaching the problem from the opposite direction -- how to take issues you care about and turn them into answerable questions.

I've been making a concerted effort to hunt for members of that intersection. Here are 16 types of predictions that I personally use to improve my judgment on issues I care about. (I'm sure there are plenty more, though, and hope you'll share your own as well.)

  1. Predict how long a task will take you. This one's a given, considering how common and impactful the planning fallacy is. 
    Examples: "How long will it take to write this blog post?" "How long until our company's profitable?"
  2. Predict how you'll feel in an upcoming situation. Affective forecasting – our ability to predict how we'll feel – has some well known flaws. 
    Examples: "How much will I enjoy this party?" "Will I feel better if I leave the house?" "If I don't get this job, will I still feel bad about it two weeks later?"
  3. Predict your performance on a task or goal. 
    One thing this helps me notice is when I've been trying the same kind of approach repeatedly without success. Even just the act of making the prediction can spark the realization that I need a better game plan.
    Examples: "Will I stick to my workout plan for at least a month?" "How well will this event I'm organizing go?" "How much work will I get done today?" "Can I successfully convince Bob of my opinion on this issue?" 
  4. Predict how your audience will react to a particular social media post (on Facebook, Twitter, Tumblr, a blog, etc.).
    This is a good way to hone your judgment about how to create successful content, as well as your understanding of your friends' (or readers') personalities and worldviews.
    Examples: "Will this video get an unusually high number of likes?" "Will linking to this article spark a fight in the comments?" 
  5. When you try a new activity or technique, predict how much value you'll get out of it.
    I've noticed I tend to be inaccurate in both directions in this domain. There are certain kinds of life hacks I feel sure are going to solve all my problems (and they rarely do). Conversely, I am overly skeptical of activities that are outside my comfort zone, and often end up pleasantly surprised once I try them.
    Examples: "How much will Pomodoros boost my productivity?" "How much will I enjoy swing dancing?"
  6. When you make a purchase, predict how much value you'll get out of it.
    Research on money and happiness shows two main things: (1) as a general rule, money doesn't buy happiness, but also that (2) there are a bunch of exceptions to this rule. So there seems to be lots of potential to improve your prediction skill here, and spend your money more effectively than the average person.
    Examples: "How much will I wear these new shoes?" "How often will I use my club membership?" "In two months, will I think it was worth it to have repainted the kitchen?" "In two months, will I feel that I'm still getting pleasure from my new car?"
  7. Predict how someone will answer a question about themselves.
    I often notice assumptions I'm been making about other people, and I like to check those assumptions when I can. Ideally I get interesting feedback both about the object-level question, and about my overall model of the person.
    Examples: "Does it bother you when our meetings run over the scheduled time?" "Did you consider yourself popular in high school?" "Do you think it's okay to lie in order to protect someone's feelings?"
  8. Predict how much progress you can make on a problem in five minutes.
    I often have the impression that a problem is intractable, or that I've already worked on it and have considered all of the obvious solutions. But then when I decide (or when someone prompts me) to sit down and brainstorm for five minutes, I am surprised to come away with a promising new approach to the problem.  
    Example: "I feel like I've tried everything to fix my sleep, and nothing works. If I sit down now and spend five minutes thinking, will I be able to generate at least one new idea that's promising enough to try?"
  9. Predict whether the data in your memory supports your impression.
    Memory is awfully fallible, and I have been surprised at how often I am unable to generate specific examples to support a confident impression of mine (or how often the specific examples I generate actually contradict my impression).
    Examples: "I have the impression that people who leave academia tend to be glad they did. If I try to list a bunch of the people I know who left academia, and how happy they are, what will the approximate ratio of happy/unhappy people be?"
    "It feels like Bob never takes my advice. If I sit down and try to think of examples of Bob taking my advice, how many will I be able to come up with?" 
  10. Pick one expert source and predict how they will answer a question.
    This is a quick shortcut to testing a claim or settling a dispute.
    Examples: "Will Cochrane Medical support the claim that Vitamin D promotes hair growth?" "Will Bob, who has run several companies like ours, agree that our starting salary is too low?" 
  11. When you meet someone new, take note of your first impressions of him. Predict how likely it is that, once you've gotten to know him better, you will consider your first impressions of him to have been accurate.
    A variant of this one, suggested to me by CFAR alum Lauren Lee, is to make predictions about someone before you meet him, based on what you know about him ahead of time.
    Examples: "All I know about this guy I'm about to meet is that he's a banker; I'm moderately confident that he'll seem cocky." "Based on the one conversation I've had with Lisa, she seems really insightful – I predict that I'll still have that impression of her once I know her better."
  12. Predict how your Facebook friends will respond to a poll.
    Examples: I often post social etiquette questions on Facebook. For example, I recently did a poll asking, "If a conversation is going awkwardly, does it make things better or worse for the other person to comment on the awkwardness?" I confidently predicted most people would say "worse," and I was wrong.
  13. Predict how well you understand someone's position by trying to paraphrase it back to him.
    The illusion of transparency is pernicious.
    Examples: "You said you think running a workshop next month is a bad idea; I'm guessing you think that's because we don't have enough time to advertise, is that correct?"
    "I know you think eating meat is morally unproblematic; is that because you think that animals don't suffer?"
  14. When you have a disagreement with someone, predict how likely it is that a neutral third party will side with you after the issue is explained to her.
    For best results, don't reveal which of you is on which side when you're explaining the issue to your arbiter.
    Example: "So, at work today, Bob and I disagreed about whether it's appropriate for interns to attend hiring meetings; what do you think?"
  15. Predict whether a surprising piece of news will turn out to be true.
    This is a good way to hone your bullshit detector and improve your overall "common sense" models of the world.
    Examples: "This headline says some scientists uploaded a worm's brain -- after I read the article, will the headline seem like an accurate representation of what really happened?"
    "This viral video purports to show strangers being prompted to kiss; will it turn out to have been staged?"
  16. Predict whether a quick online search will turn up any credible sources supporting a particular claim.
    Example: "Bob says that watches always stop working shortly after he puts them on – if I spend a few minutes searching online, will I be able to find any credible sources saying that this is a real phenomenon?"

I have one additional, general thought on how to get the most out of predictions:

Rationalists tend to focus on the importance of objective metrics. And as you may have noticed, a lot of the examples I listed above fail that criterion. For example, "Predict whether a fight will break out in the comments? Well, there's no objective way to say whether something officially counts as a 'fight' or not…" Or, "Predict whether I'll be able to find credible sources supporting X? Well, who's to say what a credible source is, and what counts as 'supporting' X?"

And indeed, objective metrics are preferable, all else equal. But all else isn't equal. Subjective metrics are much easier to generate, and they're far from useless. Most of the time it will be clear enough, once you see the results, whether your prediction basically came true or not -- even if you haven't pinned down a precise, objectively measurable success criterion ahead of time. Usually the result will be a common sense "yes," or a common sense "no." And sometimes it'll be "um...sort of?", but that can be an interestingly surprising result too, if you had strongly predicted the results would point clearly one way or the other. 

Along similar lines, I usually don't assign numerical probabilities to my predictions. I just take note of where my confidence falls on a qualitative "very confident," "pretty confident," "weakly confident" scale (which might correspond to something like 90%/75%/60% probabilities, if I had to put numbers on it).

There's probably some additional value you can extract by writing down quantitative confidence levels, and by devising objective metrics that are impossible to game, rather than just relying on your subjective impressions. But in most cases I don't think that additional value is worth the cost you incur from turning predictions into an onerous task. In other words, don't let the perfect be the enemy of the good. Or in other other words: the biggest problem with your predictions right now is that they don't exist.

My mind must be too highly trained

5 PhilGoetz 20 February 2015 09:43PM

I've played various musical instruments for nearly 40 years now, but some simple things remain beyond my grasp. Most frustrating is sight reading while playing piano. Though I've tried for years, I can't read bass and treble clef at the same time. To sight-read piano music, when you see this:

C D E F

you need your right hand to read it as C D E F, but your left hand to read it as E F G A. To this day, I can't do it, and I can only learn piano music by learning the treble and bass clef parts separately to the point where I don't rely on the score for more than reminders, then playing them together.

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The Galileo affair: who was on the side of rationality?

35 Val 15 February 2015 08:52PM

Introduction

A recent survey showed that the LessWrong discussion forums mostly attract readers who are predominantly either atheists or agnostics, and who lean towards the left or far left in politics. As one of the main goals of LessWrong is overcoming bias, I would like to come up with a topic which I think has a high probability of challenging some biases held by at least some members of the community. It's easy to fight against biases when the biases belong to your opponents, but much harder when you yourself might be the one with biases. It's also easy to cherry-pick arguments which prove your beliefs and ignore those which would disprove them. It's also common in such discussions, that the side calling itself rationalist makes exactly the same mistakes they accuse their opponents of doing. Far too often have I seen people (sometimes even Yudkowsky himself) who are very good rationalists but can quickly become irrational and use several fallacies when arguing about history or religion. This most commonly manifests when we take the dumbest and most fundamentalist young Earth creationists as an example, winning easily against them, then claiming that we disproved all arguments ever made by any theist. No, this article will not be about whether God exists or not, or whether any real world religion is fundamentally right or wrong. I strongly discourage any discussion about these two topics.

This article has two main purposes:

1. To show an interesting example where the scientific method can lead to wrong conclusions

2. To overcome a certain specific bias, namely, that the pre-modern Catholic Church was opposed to the concept of the Earth orbiting the Sun with the deliberate purpose of hindering scientific progress and to keep the world in ignorance. I hope this would prove to also be an interesting challenge for your rationality, because it is easy to fight against bias in others, but not so easy to fight against bias on yourselves.

The basis of my claims is that I have read the book written by Galilei himself, and I'm very interested (and not a professional, but well read) in early modern, but especially 16-17th century history.

 

Geocentrism versus Heliocentrism

I assume every educated person knows the name of Galileo Galilei. I won't waste the space on the site and the time of the readers to present a full biography about his life, there are plenty of on-line resources where you can find more than enough biographic information about him.

The controversy?

What is interesting about him is how many people have severe misconceptions about him. Far too often he is celebrated as the one sane man in an era of ignorance, the sole propagator of science and rationality when the powers of that era suppressed any scientific thought and ridiculed everyone who tried to challenge the accepted theories about the physical world. Some even go as far as claiming that people believed the Earth was flat. Although the flat Earth theory was not propagated at all, it's true that the heliocentric view of the Solar System (the Earth revolving around the Sun) was not yet accepted.

However, the claim that the Church was suppressing evidence about heliocentrism "to maintain its power over the ignorant masses" can be disproved easily:

- The common people didn't go to school where they could have learned about it, and those commoners who did go to school, just learned to read and write, not much more, so they wouldn't care less about what orbits around what. This differs from 20-21th century fundamentalists who want to teach young Earth creationism in schools - back then in the 17th century, there would be no classes where either the geocentric or heliocentric views could have been taught to the masses.

- Heliocentrism was not discovered by Galilei. It was first proposed by Nicolaus Copernicus almost 100 years before Galilei. Copernicus didn't have any affairs with the Inquisition. His theories didn't gain wide acceptance, but he and his followers weren't persecuted either.

- Galilei was only sentenced to house arrest, and mostly because of insulting the pope and doing other unwise things. The political climate in 17th century Italy was quite messy, and Galilei did quite a few unfortunate choices regarding his alliances. Actually, Galilei was the one who brought religion into the debate: his opponents were citing Aristotle, not the Bible in their arguments. Galilei, however, wanted to redefine the Scripture based on his (unproven) beliefs, and insisted that he should have the authority to push his own views about how people interpret the Bible. Of course this pissed quite a few people off, and his case was not helped by publicly calling the pope an idiot.

- For a long time Galilei was a good friend of the pope, while holding heliocentric views. So were a couple of other astronomers. The heliocentrism-geocentrism debates were common among astronomers of the day, and were not hindered, but even encouraged by the pope.

- The heliocentrism-geocentrism debate was never an ateism-theism debate. The heliocentrists were committed theists, just like  the defenders of geocentrism. The Church didn't suppress science, but actually funded the research of most scientists.

- The defenders of geocentrism didn't use the Bible as a basis for their claims. They used Aristotle and, for the time being, good scientific reasoning. The heliocentrists were much more prone to use the "God did it" argument when they couldn't defend the gaps in their proofs.

 

The birth of heliocentrism.

By the 16th century, astronomers have plotted the movements of the most important celestial bodies in the sky. Observing the motion of the Sun, the Moon and the stars, it would seem obvious that the Earth is motionless and everything orbits around it. This model (called geocentrism) had only one minor flaw: the planets would sometimes make a loop in their motion, "moving backwards". This required a lot of very complicated formulas to model their motions. Thus, by the virtue of Occam's razor, a theory was born which could better explain the motion of the planets: what if the Earth and everything else orbited around the Sun? However, this new theory (heliocentrism) had a lot of issues, because while it could explain the looping motion of the planets, there were a lot of things which it either couldn't explain, or the geocentric model could explain it much better.

 

The proofs, advantages and disadvantages

The heliocentric view had only a single advantage against the geocentric one: it could describe the motion of the planets by a much simper formula.

However, it had a number of severe problems:

- Gravity. Why do the objects have weight, and why are they all pulled towards the center of the Earth? Why don't objects fall off the Earth on the other side of the planet? Remember, Newton wasn't even born yet! The geocentric view had a very simple explanation, dating back to Aristotle: it is the nature of all objects that they strive towards the center of the world, and the center of the spherical Earth is the center of the world. The heliocentric theory couldn't counter this argument.

- Stellar parallax. If the Earth is not stationary, then the relative position of the stars should change as the Earth orbits the Sun. No such change was observable by the instruments of that time. Only in the first half of the 19th century did we succeed in measuring it, and only then was the movement of the Earth around the Sun finally proven.

- Galilei tried to used the tides as a proof. The geocentrists argued that the tides are caused by the Moon even if they didn't knew by what mechanisms, but Galilei said that it's just a coincidence, and the tides are not caused by the Moon: just as if we put a barrel of water onto a cart, the water would be still if the cart was stationary and the water would be sloshing around if the cart was pulled by a horse, so are the tides caused by the water sloshing around as the Earth moves. If you read Galilei's book, you will discover quite a number of such silly arguments, and you'll see that Galilei was anything but a rationalist. Instead of changing his views against overwhelming proofs, he used  all possible fallacies to push his view through.

Actually the most interesting author in this topic was Riccioli. If you study his writings you will get definite proof that the heliocentrism-geocentrism debate was handled with scientific accuracy and rationality, and it was not a religious debate at all. He defended geocentrism, and presented 126 arguments in the topic (49 for heliocentrism, 77 against), and only two of them (both for heliocentrism) had any religious connotations, and he stated valid responses against both of them. This means that he, as a rationalist, presented both sides of the debate in a neutral way, and used reasoning instead of appeal to authority or faith in all cases. Actually this was what the pope expected of Galilei, and such a book was what he commissioned from Galilei. Galilei instead wrote a book where he caricatured the pope as a strawman, and instead of presenting arguments for and against both world-views in a neutral way, he wrote a book which can be called anything but scientific.

By the way, Riccioli was a Catholic priest. And a scientist. And, it seems to me, also a rationalist. Studying the works of such people like him, you might want to change your mind if you perceive a conflict between science and religion, which is part of today's public consciousness only because of a small number of very loud religious fundamentalists, helped by some committed atheists trying to suggest that all theists are like them.

Finally, I would like to copy a short summary about this book:

Journal for the History of Astronomy, Vol. 43, No. 2, p. 215-226
In 1651 the Italian astronomer Giovanni Battista Riccioli published within his Almagestum Novum, a massive 1500 page treatise on astronomy, a discussion of 126 arguments for and against the Copernican hypothesis (49 for, 77 against). A synopsis of each argument is presented here, with discussion and analysis. Seen through Riccioli's 126 arguments, the debate over the Copernican hypothesis appears dynamic and indeed similar to more modern scientific debates. Both sides present good arguments as point and counter-point. Religious arguments play a minor role in the debate; careful, reproducible experiments a major role. To Riccioli, the anti-Copernican arguments carry the greater weight, on the basis of a few key arguments against which the Copernicans have no good response. These include arguments based on telescopic observations of stars, and on the apparent absence of what today would be called "Coriolis Effect" phenomena; both have been overlooked by the historical record (which paints a picture of the 126 arguments that little resembles them). Given the available scientific knowledge in 1651, a geo-heliocentric hypothesis clearly had real strength, but Riccioli presents it as merely the "least absurd" available model - perhaps comparable to the Standard Model in particle physics today - and not as a fully coherent theory. Riccioli's work sheds light on a fascinating piece of the history of astronomy, and highlights the competence of scientists of his time.

The full article can be found under this link. I recommend it to everyone interested in the topic. It shows that geocentrists at that time had real scientific proofs and real experiments regarding their theories, and for most of them the heliocentrists had no meaningful answers.

 

Disclaimers:

- I'm not a Catholic, so I have no reason to defend the historic Catholic church due to "justifying my insecurities" - a very common accusation against someone perceived to be defending theists in a predominantly atheist discussion forum.

- Any discussion about any perceived proofs for or against the existence of God would be off-topic here. I know it's tempting to show off your best proofs against your carefully constructed straw-men yet again, but this is just not the place for it, as it would detract from the main purpose of this article, as summarized in its introduction.

- English is not my native language. Nevertheless, I hope that what I wrote was comprehensive enough to be understandable. If there is any part of my article which you find ambiguous, feel free to ask.

I have great hopes and expectations that the LessWrong community is suitable to discuss such ideas. I have experience with presenting these ideas on other, predominantly atheist internet communities, and most often the reactions was outright flaming, a hurricane of unexplained downvotes, and prejudicial ad hominem attacks based on what affiliations they assumed I was subscribing to. It is common for people to decide whether they believe a claim or not, based solely by whether the claim suits their ideological affiliations or not. The best quality of rationalists, however, should be to be able to change their views when confronted by overwhelming proof, instead of trying to come up with more and more convoluted explanations. In the time I spent in the LessWrong community, I became to respect that the people here can argue in a civil manner, listening to the arguments of others instead of discarding them outright.

 

New, Brief Popular-Level Introduction to AI Risks and Superintelligence

21 LyleN 23 January 2015 03:43PM

The very popular blog Wait But Why has published the first part of a two-part explanation/summary of AI risks and superintelligence, and it looks like the second part will be focused on Friendly AI. I found it very clear, reasonably thorough and appropriately urgent without signaling paranoia or fringe-ness. It may be a good article to share with interested friends.

Update: Part 2 is now here.

[LINK] Wait But Why - The AI Revolution Part 2

17 adamzerner 04 February 2015 04:02PM

Part 1 was previously posted and it seemed that people likd it, so I figured that I should post part 2 - http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-2.html

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