[link] Choose your (preference) utilitarianism carefully – part 1

15 Kaj_Sotala 25 June 2015 12:06PM

Summary: Utilitarianism is often ill-defined by supporters and critics alike, preference utilitarianism even more so. I briefly examine some of the axes of utilitarianism common to all popular forms, then look at some axes unique but essential to preference utilitarianism, which seem to have received little to no discussion – at least not this side of a paywall. This way I hope to clarify future discussions between hedonistic and preference utilitarians and perhaps to clarify things for their critics too, though I’m aiming the discussion primarily at utilitarians and utilitarian-sympathisers.

http://valence-utilitarianism.com/?p=8

I like this essay particularly for the way it breaks down different forms of utilitarianism to various axes, which have rarely been discussed on LW much.

For utilitarianism in general:

Many of these axes are well discussed, pertinent to almost any form of utilitarianism, and at least reasonably well understood, and I don’t propose to discuss them here beyond highlighting their salience. These include but probably aren’t restricted to the following:

  • What is utility? (for the sake of easy reference, I’ll give each axis a simple title – for this, the utility axis); eg happiness, fulfilled preferences, beauty, information(PDF)
  • How drastically are we trying to adjust it?, aka what if any is the criterion for ‘right’ness? (sufficiency axis); eg satisficing, maximising[2], scalar
  • How do we balance tradeoffs between positive and negative utility? (weighting axis); eg, negative, negative-leaning, positive (as in fully discounting negative utility – I don’t think anyone actually holds this), ‘middling’ ie ‘normal’ (often called positive, but it would benefit from a distinct adjective)
  • What’s our primary mentality toward it? (mentality axis); eg act, rule, two-level, global
  • How do we deal with changing populations? (population axis); eg average, total
  • To what extent do we discount future utility? (discounting axis); eg zero discount, >0 discount
  • How do we pinpoint the net zero utility point? (balancing axis); eg Tännsjö’s test, experience tradeoffs
  • What is a utilon? (utilon axis) [3] – I don’t know of any examples of serious discussion on this (other than generic dismissals of the question), but it’s ultimately a question utilitarians will need to answer if they wish to formalise their system.

For preference utilitarianism in particular:

Here then, are the six most salient dependent axes of preference utilitarianism, ie those that describe what could count as utility for PUs. I’ll refer to the poles on each axis as (axis)0 and (axis)1, where any intermediate view will be (axis)X. We can then formally refer to subtypes, and also exclude them, eg ~(F0)R1PU, or ~(F0 v R1)PU etc, or represent a range, eg C0..XPU.

How do we process misinformed preferences? (information axis F)

(F0 no adjustment / F1 adjust to what it would have been had the person been fully informed / FX somewhere in between)

How do we process irrational preferences? (rationality axis R)

(R0 no adjustment / R1 adjust to what it would have been had the person been fully rational / RX somewhere in between)

How do we process malformed preferences? (malformation axes M)

(M0 Ignore them / MF1 adjust to fully informed / MFR1 adjust to fully informed and rational (shorthand for MF1R1) / MFxRx adjust to somewhere in between)

How long is a preference relevant? (duration axis D)

(D0 During its expression only / DF1 During and future / DPF1 During, future and past (shorthand for  DP1F1) / DPxFx Somewhere in between)

What constitutes a preference? (constitution axis C)

(C0 Phenomenal experience only / C1 Behaviour only / CX A combination of the two)

What resolves a preference? (resolution axis S)

(S0 Phenomenal experience only / S1 External circumstances only / SX A combination of the two)

What distinguishes these categorisations is that each category, as far as I can perceive, has no analogous axis within hedonistic utilitarianism. In other words to a hedonistic utilitarian, such axes would either be meaningless, or have only one logical answer. But any well-defined and consistent form of preference utilitarianism must sit at some point on every one of these axes.

See the article for more detailed discussion about each of the axes of preference utilitarianism, and more.

A List of Nuances

31 abramdemski 10 November 2014 05:02AM

Abram Demski and George Koleszarik


Much of rationality is pattern-matching. An article on lesswrong might point out a thing to look for. Noticing this thing changes your reasoning in some way. This essay is a list of things to look for. These things are all associated, but the reader should take care not to lump them together. Each dichotomy is distinct, and although the brain will tend to abstract them into some sort of yin/yang correlated mush, in reality they have a more complicated structure; some things may be similar, but if possible, try to focus on the complex interrelationships.

 

  1. Map vs. Territory

    1. Eliezer’s sequences use this as a jump-off point for discussion of rationality.

    2. Many thinking mistakes are map vs. territory confusions.

      1. A map and territory mistake is a mix-up of seeming vs being.

      2. Humans need frequent reminders that we are not omniscient.

  2. Cached Thoughts vs. Thinking

    1. This document is a list of cached thoughts.

  3. Clusters vs. Properties

    1. These words could be used in different ways, but the distinction I want to point at is that of labels we put on things vs actual differences in things.

    2. The mind projection fallacy is the fallacy of thinking a mental category (a “cluster”) is an actual property things have.

      1. If we see something as good for one reason, we are likely to attribute other good properties to it, as if it had inherent goodness. This is called the halo effect. (If we see something as bad and infer other bad properties as a result, it is referred to as the reverse-halo effect.)

    3. Categories are inference applicability heuristics; ruling X an instance of Y without expecting novel inferences is cargo cult classification.

  4. Syntax vs. Semantics

    1. The syntax is the physical instantiation of the map. The semantics is the way we are meant to read the map; that is, the intended relationship to the territory.

  5. Semantics vs. Pragmatics

    1. The semantics is the literal contents of a message, whereas the pragmatics is the intended result of conveying the message.

      1. An example of a message with no semantics and only pragmatics is a command, such as “Stop!”.

      2. Almost no messages lack pragmatics, and for good reason. However, if you seek truth in a discussion, it is important to foster a willingness to say things with less pragmatic baggage.

      3. Usually when we say things, we do so with some “point” which is beyond the semantics of our statement. The point is usually to build up or knock down some larger item of discussion. This is not inherently a bad thing, but has a failure mode where arguments are battles and statements are weapons, and the cleverer arguer wins.

    2. The meaning of a thing is the way you should be influenced by it.

  6. Object-level vs. Meta-level

    1. The difference between making a map and writing a book about map-making.

    2. A good meta-level theory helps get things right at the object level, but it is usually impossible to get things right at the meta level before before you’ve made significant progress at the object level.

  7. Seeming vs. Being

    1. We can only deal with how things seem, not how they are. Yet, we must strive to deal with things as they are, not as they seem.

      1. This is yet another reminder that we are not omniscient.

    2. If we optimize too hard for things which seem good rather than things which are good, we will get things which seem very good but which may only be somewhat good, or even bad.

    3. The dangerous cases are the cases where you do not notice there is a distinction.

      1. This is why humans need constant reminders that we are not omniscient.

    4. We must take care to notice the difference between how things seem to seem, and how they actually seem.

  8. Signal vs. Noise

    1. Not all information is equal. It is often the case that we desire certain sorts of information and desire to ignore other sorts.

    2. In a technical setting, this has to do with the error rate present in a communication channel; imperfections in the channel will corrupt some bits, making a need for redundancy in the message being sent.

    3. In a social setting, this is often used to refer to the amount of good information vs irrelevant information in a discussion. For example, letting a mediocre writer add material to a group blog might increase the absolute amount of good information, yet worsen the signal-to-noise ratio.

    4. Attention is a scarce resource; yes everyone has something to teach you, but many people are much more efficient sources of wisdom than others.

  9. Selection Effects

    1. Filtered evidence.

      1. In many situations, if we can present evidence to a Bayesian agent without the agent knowing that we are being selective, we can convince the agent of anything we like. For example, if I want to convince you that smoking causes obesity, I could find many people who became obese after they started smoking.

      2. The solution to this is for the Bayesian agent to model where the information is coming from. If you know I am selecting people based on this criteria, then you will not take it as evidence of anything, because the evidence has been cherry-picked.

      3. Most of the information you receive is intensely filtered. Nothing comes to your attention with a good conscience.

    2. The silent evidence problem.

      1. Selection bias need not be the result of purposeful interference as in cherry-picking. Often, an unrelated process may hide some of the evidence needed. For example, we hear far more about successful people than unsuccessful. It is tempting to look at successful people and attempt to draw conclusion about what it takes to be successful. This approach suffers from the silent evidence problem: we also need to look at the unsuccessful people and examine what is different about the two groups.

    3. Observer selection effects.

  10. What You Mean vs. What You Think You Mean

    1. Very often, people will say something and then that thing will be refuted. The common response to this is to claim you meant something slightly different, which is more easily defended.

      1. We often do this without noticing, making it dangerous for thinking. It is an automatic response generated by our brains, not a conscious decision to defend ourselves from being discredited. You do this far more often than you notice. The brain fills in a false memory of what you meant without asking for permission.

  11. What You Mean vs. What the Others Think You Mean

    1. The illusion of transparency.

    2. The double illusion of transparency.

    3. Wiio’s Laws

  12. What You Optimize vs. What You Think You Optimize

    1. Evolution optimizes for reproduction but in doing so creates animals with a variety of goals which are correlated with reproduction.

    2. Extrinsic motivation is weaker than intrinsic motivation.

    3. The people who value practice for its own sake do better than the people who only value being good at what they’re practicing.

    4. “Consequentialism is true, but virtue ethics is what works.”

  13. Stated Preferences vs. Revealed Preferences

    1. Revealed preferences are the preferences we can infer from your actions. These are usually different from your stated preferences.

      1. X is not about Y:

        1. Food isn’t about nutrition.

        2. Clothes aren’t about comfort.

        3. Bedrooms aren’t about sleep.

        4. Marriage isn’t about love.

        5. Talk isn’t about information.

        6. Laughter isn’t about humour.

        7. Charity isn’t about helping.

        8. Church isn’t about God.

        9. Art isn’t about insight.

        10. Medicine isn’t about health.

        11. Consulting isn’t about advice.

        12. School isn’t about learning.

        13. Research isn’t about progress.

        14. Politics isn’t about policy.

        15. Going meta isn’t about the object level.

        16. Language isn’t about communication.

        17. The rationality movement isn’t about epistemology.

      2. Everything is actually about signalling.

    2. Humans Are Not Automatically Strategic

      1. Never attribute to malice that which can be adequately explained by stupidity. The difference between stated preferences and revealed preferences does not indicate dishonest intent. We should expect the two to differ in the absence of a mechanism to align them.

      2. Hidden Motives vs. Innocent Failure

    3. People, ideas, and organizations respond to incentives.

      1. Evolution selects humans who have reproductively selfish behavioral tendencies, but prosocial and idealistic stated preferences.

        1. Near vs. Far

      2. Social forces select ideas for virality and comprehensibility as opposed to truth or even usefulness.

        1. Motte-and-bailey fallacy

      3. Organizations are by default bad at being strategic about their own survival, but the ones that survive are the ones you see.

  14. What You Achieve vs. What You Think You Achieve

    1. Most of the consequences of our actions are totally unknown to us.

    2. It is impossible to optimize without proper feedback.

  15. What You Optimize vs. What You Actually Achieve

    1. Consequentialism is more about expected consequences than actual consequences.

  16. What You Seem Like vs. What You Are

    1. You can try to imagine yourself from the outside, but no one has the full picture.

  17. What Other People Seem Like vs. What They Are

    1. When people assume that they understand others, they are wrong.

  18. What People Look Like vs. What They Think They Look Like

    1. People underestimate the gap between stated preferences and revealed preferences.

  19. What Your Brain Does vs. What You Think It Does

    1. You are running on corrupted hardware.

      1. The brain’s machinations are fundamentally social; it automatically does things like signal, save face, etc., which distort the truth.

    2. The reverse of stupidity is not intelligence.

      1. Knowing that you are running on corrupted hardware should cause skepticism about the outputs of your thought-processes. Yet, too much skepticism will cause you to stumble, particularly when fast thinking is needed.

        1. Producing a correct result plus justification is harder than producing only the correct result.

        2. Justifications are important, but the correct result is more important.

        3. Much of our apparent self-reflection is confabulation, generating plausible explanations after the brain spits out an answer.

        4. Example: doing quick mental math. If you are good at this, attempting to explicitly justify every step as you go would likely slow you down.

        5. Example: impressions formed over a long period of time. Wrong or right, it is unlikely that you can explicitly give all your reasons for the impression. Requiring your own beliefs to be justifiable would preempt impressions that require lots of experience and/or many non-obvious chains of subconscious inference.

        6. Impressions are not beliefs and they are always useful data.

  20. Clever Argument vs. Truth-seeking; The Bottom Line

    1. People believe what they want to believe.

      1. Believing X for some reason unrelated to X being true is referred to as motivated cognition.

      2. Giving a smart person more information and more methods of argument may actually make their beliefs less accurate, because you are giving them more tools to construct clever arguments for what they want to believe.

    2. Your actual reason for believing X determines how well your belief correlates with the truth.

      1. If you believe X because you want to, any arguments you make for X no matter how strong they sound are devoid of informational context about X and should properly be ignored by a truth-seeker.

    3. If you believe true things when doing so improves your life, that is no credit to you at all. Everyone does that.

  21. Lumpers vs. Splitters

    1. A lumper is a thinker who attempts to fit things into overarching patterns. A splitter is a thinker who makes as many distinctions as possible, recognizing the importance of being specific and getting the details right.

    2. Specifically, some people want big Wikipedia and TVTropes articles that discuss many things, and others want smaller articles that discuss fewer things.

    3. This list of nuances is a lumper attempting to think more like a splitter.

  22. Fox vs. Hedgehog

    1. “A fox knows many things, but a hedgehog knows One Big Thing.” Closely related to a splitter, a fox is a thinker whose strength is in a broad array of knowledge. A hedgehog is a thinker who, in contrast, has one big idea and applies it everywhere.

    2. The fox mindset is better for making accurate judgements, according to Tetlock.

  23. Traps vs. Gardens

    1. Well-kept gardens die by pacifism.

      1. Conversations tend to slide toward contentious and useless topics.

      2. Societies tend to decay.

      3. Systems in general work poorly or not at all.

      4. Thermodynamic equilibrium is entropic.

      5. Without proper institutions being already in place, it takes large amounts of constant effort and vigilance to stay out of traps.

    2. From the outside of a broken Molochian system it is easy to see how to fix. But it cannot be fixed from the inside.

Cross-posted to In Search Of Logic

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.

How to sign up for Alcor cryo

32 oge 26 April 2015 02:51AM

I wrote an article about the process of signing up for cryo since I couldn't find any such accounts online. If you have questions about the sign-up process, just ask.

A few months ago, I signed up for Alcor's brain-only cryopreservation. The entire process took me 11 weeks from the day I started till the day I received my medical bracelet (the thing that’ll let paramedics know that your dead body should be handled by Alcor). I paid them $90 for the application fee. From now on, every year I’ll pay $530 for Alcor membership fees, and also pay $275 for my separately purchased life insurance.

http://specterdefied.blogspot.com/2015/04/how-to-sign-up-for-alcor-cryo.html

Timeless Decision Theory and Meta-Circular Decision Theory

24 Eliezer_Yudkowsky 20 August 2009 10:07PM

(This started as a reply to Gary Drescher's comment here in which he proposes a Metacircular Decision Theory (MCDT); but it got way too long so I turned it into an article, which also contains some amplifications on TDT which may be of general interest.)

continue reading »

The Truth About Mathematical Ability

61 JonahSinick 12 February 2015 01:29AM

There's widespread confusion about the nature of mathematical ability, for a variety of reasons:

  • Most people don't know what math is.
  • Most people don't know enough statistics to analyze the question properly.
  • Most mathematicians are not very metacognitive.
  • Very few people have more than a casual interest in the subject.

If the nature of mathematical ability were exclusively an object of intellectual interest, this would be relatively inconsequential. For example, many people are confused about Einstein’s theory of relativity, but this doesn’t have much of an impact on their lives. But in practice, people’s misconceptions about the nature of mathematical ability seriously interfere with their own ability to learn and do math, something that hurts them both professionally and emotionally.

I have a long standing interest in the subject, and I’ve found myself in the unusual position of being an expert. My experiences include:

  • Completing a PhD in pure math at University of Illinois.
  • Four years of teaching math at the high school and college levels (precalculus, calculus, multivariable calculus and linear algebra)
  • Personal encounters with some of the best mathematicians in the world, and a study of great mathematicians’ biographies.
  • A long history of working with mathematically gifted children: as a counselor at MathPath for three summers, through one-on-one tutoring, and as an instructor at Art of Problem Solving.
  • Studying the literature on IQ and papers from the Study of Exceptional Talent as a part of my work for Cognito Mentoring.
  • Training as a full-stack web developer at App Academy.
  • Doing a large scale data science project where I applied statistics and machine learning to make new discoveries in social psychology.

I’ve thought about writing about the nature of mathematical ability for a long time, but there was a missing element: I myself had never done genuinely original and high quality mathematical research. After completing much of my data science project, I realized that this had changed. The experience sharpened my understanding of the issues.

This is a the first of a sequence of posts where I try to clarify the situation. My main point in this post is:

There are several different dimensions to mathematical ability. Common measures rarely assess all of these dimensions, and can paint a very incomplete picture of what somebody is capable of.

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Why We Can't Take Expected Value Estimates Literally (Even When They're Unbiased)

75 HoldenKarnofsky 18 August 2011 11:34PM

Note: I am cross-posting this GiveWell Blog post, after consulting a couple of community members, because it is relevant to many topics discussed on Less Wrong, particularly efficient charity/optimal philanthropy and Pascal's Mugging. The post includes a proposed "solution" to the dilemma posed by Pascal's Mugging that has not been proposed before as far as I know. It is longer than usual for a Less Wrong post, so I have put everything but the summary below the fold. Also, note that I use the term "expected value" because it is more generic than "expected utility"; the arguments here pertain to estimating the expected value of any quantity, not just utility.

While some people feel that GiveWell puts too much emphasis on the measurable and quantifiable, there are others who go further than we do in quantification, and justify their giving (or other) decisions based on fully explicit expected-value formulas. The latter group tends to critique us - or at least disagree with us - based on our preference for strong evidence over high apparent "expected value," and based on the heavy role of non-formalized intuition in our decisionmaking. This post is directed at the latter group.

We believe that people in this group are often making a fundamental mistake, one that we have long had intuitive objections to but have recently developed a more formal (though still fairly rough) critique of. The mistake (we believe) is estimating the "expected value" of a donation (or other action) based solely on a fully explicit, quantified formula, many of whose inputs are guesses or very rough estimates. We believe that any estimate along these lines needs to be adjusted using a "Bayesian prior"; that this adjustment can rarely be made (reasonably) using an explicit, formal calculation; and that most attempts to do the latter, even when they seem to be making very conservative downward adjustments to the expected value of an opportunity, are not making nearly large enough downward adjustments to be consistent with the proper Bayesian approach.

This view of ours illustrates why - while we seek to ground our recommendations in relevant facts, calculations and quantifications to the extent possible - every recommendation we make incorporates many different forms of evidence and involves a strong dose of intuition. And we generally prefer to give where we have strong evidence that donations can do a lot of good rather than where we have weak evidence that donations can do far more good - a preference that I believe is inconsistent with the approach of giving based on explicit expected-value formulas (at least those that (a) have significant room for error (b) do not incorporate Bayesian adjustments, which are very rare in these analyses and very difficult to do both formally and reasonably).

The rest of this post will:

  • Lay out the "explicit expected value formula" approach to giving, which we oppose, and give examples.
  • Give the intuitive objections we've long had to this approach, i.e., ways in which it seems intuitively problematic.
  • Give a clean example of how a Bayesian adjustment can be done, and can be an improvement on the "explicit expected value formula" approach.
  • Present a versatile formula for making and illustrating Bayesian adjustments that can be applied to charity cost-effectiveness estimates.
  • Show how a Bayesian adjustment avoids the Pascal's Mugging problem that those who rely on explicit expected value calculations seem prone to.
  • Discuss how one can properly apply Bayesian adjustments in other cases, where less information is available.
  • Conclude with the following takeaways:
    • Any approach to decision-making that relies only on rough estimates of expected value - and does not incorporate preferences for better-grounded estimates over shakier estimates - is flawed.
    • When aiming to maximize expected positive impact, it is not advisable to make giving decisions based fully on explicit formulas. Proper Bayesian adjustments are important and are usually overly difficult to formalize.
    • The above point is a general defense of resisting arguments that both (a) seem intuitively problematic (b) have thin evidential support and/or room for significant error.

continue reading »

Is there a rationalist skill tree yet?

15 fowlertm 30 January 2015 04:02PM

A while back I came across a delightful web developer skill tree, and I was wondering if technical rationality has gotten to the point where someone could make one of these for an aspiring rationalist.

I think seeing a clear progression from beginning skills to advanced ones laid out graphically helps those starting on the path conceptualize the process. 

Immortality: A Practical Guide

34 G0W51 26 January 2015 04:17PM

Immortality: A Practical Guide

Introduction

This article is about how to increase one’s own chances of living forever or, failing that, living for a long time. To be clear, this guide defines death as the long-term loss of one’s consciousness and defines immortality as never-ending life. For those who would like less lengthy information on decreasing one’s risk of death, I recommend reading the sections “Can we become immortal,” “Should we try to become immortal,” and “Cryonics,” in this guide, along with the article Lifestyle Interventions to Increase Longevity.

This article does not discuss how to treat specific disease you may have. It is not intended as a substitute for the medical advice of physicians. You should consult a physician with respect to any symptoms that may require diagnosis or medical attention.

When reading about the effect sizes in scientific studies, keep in mind that many scientific studies report false-positives and are biased,101 though I have tried to minimize this by maximizing the quality of the studies used. Meta-analyses and scientific reviews seem to typically be of higher quality than other study types, but are still subject to biases.114

Corrections, criticisms, and suggestions for new topics are greatly appreciated. I’ve tried to write this article tersely, so feedback on doing so would be especially appreciated. Apologies if the article’s font type, size and color isn’t standard on Less Wrong; I made it in google docs without being aware of Less Wrong’s standard and it would take too much work changing the style of the entire article.

 

Contents

  1. Can we become immortal?

  2. Should we try to become immortal?

  3. Relative importance of the different topics

  4. Food

    1. What to eat and drink

    2. When to eat and drink

    3. How much to eat

    4. How much to drink

  5. Exercise

  6. Carcinogens

    1. Chemicals

    2. Infections

    3. Radiation

  7. Emotions and feelings

    1. Positive emotions and feelings

    2. Psychological distress

    3. Stress

    4. Anger and hostility

  8. Social and personality factors

    1. Social status

    2. Giving to others

    3. Social relationships

    4. Conscientiousness

  9. Infectious diseases

    1. Dental health

  10. Sleep

  11. Drugs

  12. Blood donation

  13. Sitting

  14. Sleep apnea

  15. Snoring

  16. Exams

  17. Genomics

  18. Aging

  19. External causes of death

    1. Transport accidents

    2. Assault

    3. Intentional self harm

    4. Poisoning

    5. Accidental drowning

    6. Inanimate mechanical forces

    7. Falls

    8. Smoke, fire, and heat

    9. Other accidental threats to breathing

    10. Electric current

    11. Forces of nature

  20. Medical care

  21. Cryonics

  22. Money

  23. Future advancements

  24. References

 

Can we become immortal?

In order to potentially live forever, one never needs to make it impossible to die; one instead just needs to have one’s life expectancy increase faster than time passes, a concept known as the longevity escape velocity.61 For example, if one had a 10% chance of dying in their first century of life, but their chance of death decreased by 90% at the end of each century, then one’s chance of ever dying would be be 0.1 + 0.12 + 0.13… = 0.11… = 11.11...%. When applied to risk of death from aging, this akin to one’s remaining life expectancy after jumping off a cliff while being affected by gravity and jet propulsion, with gravity being akin to aging and jet propulsion being akin to anti-aging (rejuvenation) therapies, as shown below.

The numbers in the above figure denote plausible ages of individuals when the first rejuvenation therapies arrive. A 30% increase in healthy lifespan would give the users of first-generation rejuvenation therapies 20 years to benefit from second-generation rejuvenation therapies, which could give an additional 30% increase if life span, ad infinitum.61

As for causes of death, many deaths are strongly age-related. The proportion of deaths that are caused by aging in the industrial world approaches 90%.53 Thus, I suppose postponing aging would drastically increase life expectancy.

As for efforts against aging, the SENS Research foundation and Science for Life Extension are charitable foundations for trying to cure aging.54, 55 Additionally, Calico, a Google-backed company, and AbbVie, a large pharmaceutical company, have each committed fund $250 million to cure aging.56

I speculate that one could additionally decrease risk of death by becoming a cyborg, as mechanical bodies seem easier to maintain than biological ones, though I’ve found no articles discussing this.

Similar to becoming a cyborg, another potential method of decreasing one’s risk of death is mind uploading, which is, roughly speaking, the transfer of most or all of one’s mental contents into a computer.62 However, there are some concerns about the transfer creating a copy of one’s consciousness, rather than being the same consciousness. This issue is made very apparent if the mind-uploaded process leaves the original mind intact, making it seem unlikely that one’s consciousness was transferred to the new body.63 Eliezer Yudkowsky doesn’t seem to believe this is an issue, though I haven't found a citation for this.

With regard to consciousness, it seems that most individuals believe that the consciousness in one’s body is the “same” consciousness as the one that was in one’s body in the past and will be in it in the future. However, I know of no evidence for this. If one’s consciousness isn’t the same of the one in one’s body in the future, and one defined death as one’s consciousness permanently ending, then I suppose one can’t prevent death for any time at all. Surprisingly, I’ve found no articles discussing this possibility.

Although curing aging, becoming a cyborg, and mind uploading may prevent death from disease, they still seem to leave oneself vulnerable to accidents, murder, suicide, and existential catastrophes. I speculate that these problems could be solved by giving an artificial superintelligence the ability to take control of one’s body in order to prevent such deaths from occurring. Of course, this possibility is currently unavailable.

Another potential cause of death is the Sun expanding, which could render Earth uninhabitable in roughly one billion years. Death from this could be prevented by colonizing other planets in the solar system, although eventually the sun would render the rest of the solar system uninhabitable. After this, one could potentially inhabit other stars; it is expected that stars will remain for roughly 10 quintillion years, although some theories predict that the universe will be destroyed in a mere 20 billion years. To continue surviving, one could potentially go to other universes.64 Additionally, there are ideas for space-time crystals that could process information even after heat death (i.e. the “end of the universe”),65 so perhaps one could make oneself composed of the space-time crystals via mind uploading or another technique. There could also be other methods of surviving the conventional end of the universe, and life could potentially have 10 quintillion years to find them.

Yet another potential cause of death is living in a computer simulation that is ended. The probability of one living in a computer simulation actually seems to not be very improbable. Nick Bostrom argues that:

...at least one of the following propositions is true: (1) The fraction of human-level civilizations that reach a posthuman stage is very close to zero; (2) The fraction of posthuman civilizations that are interested in running ancestor-simulations is very close to zero; (3) The fraction of all people with our kind of experiences that are living in a simulation is very close to one.

The argument for this is here.100

If one does die, one could potentially be revived. Cryonics, discussed later in this article, may help in this. Additionally, I suppose one could possibly be revived if future intelligences continually create new conscious individuals and eventually create one of them that have one’s “own” consciousness, though consciousness remains a mystery, so this may not be plausible, and I’ve found no articles discussing this possibility. If the probability of one’s consciousness being revived per unit time does not approach or equal zero as time approaches infinity, then I suppose one is bound to become conscious again, though this scenario may be unlikely. Again, I’ve found no articles discussing this possibility.

As already discussed, in order to be live forever, one must either be revived after dying or prevent death from the consciousness in one’s body not being the same as the one that will be in one’s body in the future, accidents, aging, the sun dying, the universe dying, being in a simulation and having it end, and other, unknown, causes. Keep in mind that adding extra details that aren’t guaranteed to be true can only make events less probable, and that people often don’t account for this.66 A spreadsheet for estimating one’s chance of living forever is here.

 

Should we try to become immortal?

Before deciding whether one should try to become immortal, I suggest learning about the cognitive biases scope insensitivity, hyperbolic discounting, and bias blind spot if you don’t know currently know about them. Also, keep in mind that one study found that simply informing people of a cognitive bias made them no less likely to fall prey to it. A study also found that people only partially adjusted for cognitive biases after being told that informing people of a cognitive bias made them no less likely to fall prey to it.67

Many articles arguing against immortality are found via a quick google search, including this, this, this, and this. This article along with its comments discusses counter-arguments to many of these arguments. The Fable of the Dragon Tyrant provides an argument for curing aging, which can be extended to be an argument against mortality as a whole. I suggest reading it.

One can also evaluate the utility of immortality via decision theory. Assuming individuals receive a finite amount of utility per unit time such that it is never less than some above-zero constant, living forever would give infinitely more utility than living for a finite amount of time. Using these assumptions, in order to maximize utility, one should be willing to accept any finite cost to become immortal. However, the situation is complicated when one considers the potential of becoming immortal and receiving an infinite positive utility unintentionally, in which case one would receive infinite expected utility regardless of if one tried to become immortal. Additionally, if one both has the chance of receiving infinitely high and infinitely low utility, one’s expected utility would be undefined. Infinite utilities are discussed in “Infinite Ethics” by Nick Bostrom.

For those interested in decreasing existential risk, living for a very long time, albeit not necessarily forever, may give one more opportunity to do so. This idea can be generalized to many goals one has in life.

On whether one can influence one’s chances of becoming immortal, studies have shown that only roughly 20-30% of longevity in humans is accounted for by genetic factors.68 There are multiple actions one can to increase one’s chances of living forever; these are what the rest of this article is about. Keep in mind that you should consider continuing reading this article even if you don’t want to try to become immortal, as the article provides information on living longer, even if not forever, as well.

 

Relative importance of the different topics

The figure below gives the relative frequencies of preventable causes of death.

1

Some causes of death are excluded from the graph, but are still large causes of death. Most notably, 440,000 deaths in the US, roughly one sixth of total deaths in the US are estimated to be from preventable medical errors in hospitals.2

Risk calculators for cardiovascular disease are here and here. Though they seem very simplistic, they may be worth looking at and can probably be completed quickly.

Here are the frequencies of causes of deaths in the US in year 2010 based off of another classification:

  • Heart disease: 596,577

  • Cancer: 576,691

  • Chronic lower respiratory diseases: 142,943

  • Stroke (cerebrovascular diseases): 128,932

  • Accidents (unintentional injuries): 126,438

  • Alzheimer's disease: 84,974

  • Diabetes: 73,831

  • Influenza and Pneumonia: 53,826

  • Nephritis, nephrotic syndrome, and nephrosis: 45,591

  • Intentional self-harm (suicide): 39,518

113

 

Food

What to eat and drink

Keep in mind that the relationship between health and the consumption of types of substances aren’t necessarily linear. I.e. some substances are beneficial in small amounts but harmful in large amounts, while others are beneficial in both small and large amounts, but consuming large amounts is no more beneficial than consuming small amounts.

 

Recommendations from The Nutrition Source

The Nutrition Source is part of the Harvard School of Public Health.

Its recommendations:

  • Make ½ of your “plate” consist of a variety of fruits and a variety of vegetables, excluding potatoes, due to potatoes’ negative effect on blood sugar. The Harvard School of Public Health doesn’t seem to specify if this is based on calories or volume. It also doesn’t explain what it means by plate, but presumably ½ of one’s plate means ½ solid food consumed.

  • Make ¼ of your plate consist of whole grains.

  • Make ¼ of your plate consist of high-protein foods.

  • Limit red meat consumption.

  • Avoid processed meats.

  • Consume monounsaturated and polyunsaturated fats in moderation; they are healthy.

  • Avoid partially hydrogenated oils, which contain trans fats, which are unhealthy.

  • Limit milk and dairy products to one to two servings per day.

  • Limit juice to one small glass per day.

  • It is important to eat seafood one or two times per week, particularly fatty (dark meat) fish that are richer in EPA and DHA.

  • Limit diet drink consumption or consume in moderation.

  • Avoid sugary drinks like soda, sports drinks, and energy drinks.3

 

Fat

The bottom line is that saturated fats and especially trans fats are unhealthy, while unsaturated fats are healthy and the types of unsaturated fats omega-3 and omega-6 fatty acids fats are essential. The proportion of calories from fat in one’s diet isn’t really linked with disease.

Saturated fat is unhealthy. It’s generally a good idea to minimize saturated fat consumption. The latest Dietary Guidelines for Americans recommends consuming no more than 10% of calories from saturated fat, but the American Heart Association recommends consuming no more than 7% of calories from saturated fat. However, don’t decrease nut, oil, and fish consumption to minimize saturated fat consumption. Foods that contain large amounts of saturated fat include red meat, butter, cheese, and ice cream.

Trans fats are especially unhealthy. For every 2% increase of calories from trans-fat, risk of coronary heart disease increases by 23%. The Federal Institute for Medicine states that there are no known requirements for trans fats for bodily functions, so their consumption should be minimized. Partially hydrogenated oils contain trans fats, and foods that contain trans fats are often processed foods. In the US, products can claim to have zero grams of trans fat if they have no more than 0.5 grams of trans fat. Products with no more than 0.5 grams of trans fat that still have non-negligible amounts of trans fat will probably have the ingredients “partially hydrogenated vegetable oils” or “vegetable shortening” in their ingredient list.

Unsaturated fats have beneficial effects, including improving cholesterol levels, easing inflammation, and stabilizing heart rhythms. The American Heart Association has set 8-10% of calories as a target for polyunsaturated fat consumption, though eating more polyunsaturated fat, around 15%of daily calories, in place of saturated fat may further lower heart disease risk. Consuming unsaturated fats instead of saturated fat also prevents insulin resistance, a precursor to diabetes. Monounsaturated fats and polyunsaturated fats are types of unsaturated fats.

Omega-3 fatty acids (omega-3 fats) are a type of unsaturated fat. There are two main types: Marine omega-3s and alpha-linolenic acid (ALA). Omega-3 fatty acids, especially marine omega-3s, are healthy. Though one can make most needed types of fats from other fats or substances consumed, omega-3 fat is an essential fat, meaning it is an important type of fat and cannot be made in the body, so they must come from food. Most americans don’t get enough omega-3 fats.

Marine omega-3s are primarily found in fish, especially fatty (dark mean) fish. A comprehensive review found that eating roughly two grams per week of omega-3s from fish, equal to about one or two servings of fatty fish per week, decreased risk of death from heart disease by more than one-third. Though fish contain mercury, this is insignificant the positive health effects of their consumption (for the consumer, not the fish). However, it does benefit one’s health to consult local advisories to determine how much local freshwater fish to consume.

ALA may be an essential nutrient, and increased ALA consumption may be beneficial. ALA is found in vegetable oils, nuts (especially walnuts), flax seeds, flaxseed oil, leafy vegetables, and some animal fat, especially those from grass-fed animals. ALA is primarily used as energy, but a very small amount of it is converted into marine omega-3s. ALA is the most common omega-3 in western diets.

Most Americans consume much more omega-6 fatty acids (omega-6 fats) than omega-3 fats. Omega-6 fat is an essential nutrient and its consumption is healthy. Some sources of it include corn and soybean oils. The Nutrition Sources stated that the theory that omega-3 fats are healthier than omega-6 fats isn’t supported by evidence. However, in an image from the Nutrition Source, seafood omega-6 fats were ranked as healthier than plant omega-6 fats, which were ranked as healthier than monounsaturated fats, although such a ranking was to the best of my knowledge never stated in the text.3

 

Carbohydrates

There seems to be two main determinants of carbohydrate sources’ effects on health: nutrition content and effect on blood sugar. The bottom line is that consuming whole grains and other less processed grains and decreasing refined grain consumption improves health. Additionally, moderately low carbohydrate diets can increase heart health as long as protein and fat comes from health sources, though the type of carbohydrate at least as important as the amount of carbohydrates in a diet.

Glycemic index and is a measure of how much food increases blood sugar levels. Consuming carbohydrates that cause blood-sugar spikes can increase risk of heart disease and diabetes at least as much as consuming too much saturated fat does. Some factors that increase the glycemic index of foods include:

  • Being a refined grain as opposed to a whole grain.

  • Being finely ground, which is why consuming whole grains in their whole form, such as rice, can be healthier than consuming them as bread.

  • Having less fiber.

  • Being more ripe, in the case of fruits and vegetables.

  • Having a lower fat content, as meals with fat are converted more slowly into sugar.

Vegetables (excluding potatoes), fruits, whole grains, and beans, are healthier than other carbohydrates. Potatoes have a negative effect on blood sugar, due to their high glycemic index. Information on glycemic index and the index of various foods is here.

Whole grains also contain essential minerals such as magnesium, selenium, and copper, which may protect against some cancers. Refining grains takes away 50% of the grains’ B vitamins, 90% of vitamin E, and virtually all fiber. Sugary drinks usually have little nutritional value.

Identifying whole grains as food that has at least one gram of fiber for every gram of carbohydrate is a more effective measure of healthfulness than identifying a whole grain as the first ingredient, any whole grain as the first ingredient without added sugars in the first 3 ingredients, the word “whole” before any grain ingredient, and the whole grain stamp.3

 

Protein

Proteins are broken down to form amino acids, which are needed for health. Though the body can make some amino acids by modifying others, some must come from food, which are called essential amino acids. The institute of medicine recommends that adults get a minimum of 0.8 grams of protein per kilogram of body weight per day, and sets the range of acceptable protein intake to 10-35% of calories per day. The Institute of Medicine recommends getting 10-35% of calories from protein each day. The US recommended daily allowance for protein is 46 grams per day for women over 18 and 56 grams per day for men over 18.

Animal products tend to give all essential amino acids, but other sources lack some essential amino acids. Thus, vegetarians need to consume a variety of sources of amino acids each day to get all needed types. Fish, chicken, beans, and nuts are healthy protein sources.3

 

Fiber

There are two types of fiber: soluble fiber and insoluble fiber. Both have important health benefits, so one should eat a variety of foods to get both.94 The best sources of fiber are whole grains, fresh fruits and vegetables, legumes, and nuts.3

 

Micronutrients

There are many micronutrients in food; getting enough of them is important. Most healthy individuals can get sufficient micronutrients by consuming a wide variety of healthy foods, such as fruits, vegetables, whole grains, legumes, and lean meats and fish. However, supplementation may be necessary for some. Information about supplements is here.110

Concerning supplementation, potassium, iodine, and lithium supplementation are recommended in the first-place entry in the Quantified Health Prize, a contest on determining good mineral intake levels. However, others suggest that potassium supplementation isn’t necessarily beneficial, as shown here. I’m somewhat skeptical that the supplements are beneficial, as I have not found other sources recommending their supplementation. The suggested supplementation levels are in the entry.

Note that food processing typically decreases micronutrient levels, as described here. In general, it seems cooking, draining and drying foods sizably, taking potentially half of nutrients away, while freezing and reheating take away relatively few nutrients.111

One micronutrient worth discussing is sodium. Some sodium is needed for health, but most Americans consume more sodium than needed. However, recommendations on ideal sodium levels vary. The US government recommends limiting sodium consumption to 2,300mg/day (one teaspoon). The American Heart Association recommends limiting sodium consumption to 1,500mg/day (⅔ of a teaspoon), especially for those who are over 50, have high or elevated blood pressure, have diabetes, or are African Americans3 However, As RomeoStevens pointed out, the Institute of Medicine found that there's inconclusive evidence that decreasing sodium consumption below 2,300mg/day effects mortality,115 and some meta-analyses have suggested that there is a U-shaped relationship between sodium and mortality.116, 117

Vitamin D is another micronutrient that’s important for health. It can be obtained from food or made in the body after sun exposure. Most people who live farther north than San Francisco or don’t go outside at least fifteen minutes when it’s sunny are vitamin D deficient. Vitamin D deficiency is increases the risk of many chronic diseases including heart disease, infectious diseases, and some cancers. However, there is controversy about optimal vitamin D intake. The Institute of medicine recommends getting 600 to 4000 IU/day, though it acknowledged that there was no good evidence of harm at 4000 IU/day. The Nutrition Sources states that these recommendations are too low and fail to account for new evidence. The nutrition source states that for most people, supplements are the best source of vitamin D, but most multivitamins have too little vitamin D in them. The Nutrition Source recommends considering and talking to a doctor about taking an additional multivitamin if the you take less than 1000 IU of vitamin D and especially if you have little sun exposure.3

 

Blood pressure

Information on blood pressure is here in the section titled “Blood Pressure.”

 

Cholesterol and triglycerides

Information on optimal amounts of cholesterol and triglycerides are here.

 

The biggest influences on cholesterol are fats and carbohydrates in one’s diet, and cholesterol consumption generally has a far weaker influence. However, some people’s cholesterol levels rise and fall very quickly with the amount of cholesterol consumed. For them, decreasing cholesterol consumption from food can have a considerable effect on cholesterol levels. Trial and error is currently the only way of determining if one’s cholesterol levels risk and fall very quickly with the amount of cholesterol consumed.

 

Antioxidants

Despite their initial hype, randomized controlled trials have offered little support for the benefit is single antioxidants, though studies are inconclusive.3

 

Dietary reference intakes

For the numerically inclined, the Dietary Reference Intake provides quantitative guidelines on good nutrient consumption amounts for many nutrients, though it may be harder to use for some, due to its quantitative nature.

 

Drinks

The Nutrition Source and SFGate state that water is the best drink,3, 112 though I don’t know why it’s considered healthier than drinks such as tea.

Unsweetened tea decreases the risk of many diseases, likely largely due to polyphenols, and antioxidant, in it. Despite antioxidants typically having little evidence of benefit, I suppose polyphenols are relatively beneficial. All teas have roughly the same levels of polyphenols except decaffeinated tea,3 which has fewer polyphenols.96 Research suggests that proteins and possibly fat in milk decrease the antioxidant capacity of tea.

It’s considered safe to drink up to six cups of coffee per day. Unsweetened coffee is healthy and may decrease some disease risks, though coffee may slightly increase blood pressure. Some people may want to consider avoiding coffee or switching to decaf, especially women who are pregnant or people who have a hard time controlling their blood pressure or blood sugar. The nutrition source states that it’s best to brew coffee with a paper filter to remove a substance that increases LDL cholesterol, despite consumed cholesterol typically having a very small effect on the body’s cholesterol level.

Alcohol increases risk of diseases for some people3 and decreases it for others.3, 119 Heavy alcohol consumption is a major cause of preventable death in most countries. For some groups of people, especially pregnant people, people recovering from alcohol addiction, and people with liver disease, alcohol causes greater health risks and should be avoided. The likelihood of becoming addicted to alcohol can be genetically determined. Moderate drinking, generally defined as no more than one or two drinks per day for men, can increase colon and breast cancer risk, but these effects are offset by decreased heart disease and diabetes risk, especially in middle age, where heart disease begins to account for an increasingly large proportion of deaths. However, alcohol consumption won’t decrease cardiovascular disease risk much for those who are thin, physically active, don’t smoke, eat a healthy diet, and have no family history of heart disease. Some research suggests that red wine, particularly when consumed after a meal, has more cardiovascular benefits than beers or spirits, but alcohol choice has still little effect on disease risk. In one study, moderate drinkers were 30-35% less likely to have heart attacks than non-drinkers and men who drank daily had lower heart attack risk than those who drank once or twice per week.

There’s no need to drink more than one or two glasses of milk per day. Less milk is fine if calcium is obtained from other sources.

The health effects of artificially sweetened drinks are largely unknown. Oddly, they may also cause weight gain. It’s best to limit consuming them if one drinks them at all.

Sugary drinks can cause weight gain, as they aren’t as filling as solid food and have high sugar. They also increase the risk of diabetes, heart disease, and other diseases. Fruit juice has more calories and less fiber than whole fruit and is reportedly no better than soft drinks.3

 

Solid food

Fruits and vegetables are an important part of a healthy diet. Eating a variety of them is as important as eating many of them.3 Fish and nut consumption is also very healthy.98

Processed meat, on the other hand, is shockingly bad.98 A meta-analysis found that processed meat consumption is associated with a 42% increased risk of coronary heart disease (relative risk per 50g serving per day; 95% confidence interval: 1.07 - 1.89) and 19% increased risk of diabetes.97 Despite this, a bit of red meat consumption has been found to be beneficial.98 Consumption of well-done, fried, or barbecued meat has been associated with certain cancers, presumably due to carcinogens made in the meat from being cooked, though this link isn’t definitive. The amount of carcinogens increases with increased cooking temperature (especially above 300ºF, increased cooking time, charring, or being exposed to smoke.99

Eating less than one egg per day doesn’t increase heart disease risk in healthy individuals and can be part of a healthy diet.3

Organic foods have lower levels of pesticides than inorganic foods, though the residues of most organic and inorganic products don’t exceed government safety threshold. Washing fresh fruits and vegetables in recommended, as it removes bacteria and some, though not all, pesticide residues. Organic foods probably aren’t more nutritious than non-organic foods.103

 

When to eat and drink

A randomized controlled trial found an increase in blood sugar variation for subjects who skipped breakfast.6 Increasing meal frequency and decreasing meal size appears to have some metabolic advantages, and doesn’t appear to have metabolic disadvantages.7 Note:  old source; made in 1994 However, Mayo Clinic states that fasting for 1-2 days per week may increase heart health.32 Perhaps it is optimal for health to fast, but to have high meal frequency when not fasting.

 

How much to eat

One’s weight gain is directly proportional to the number of calories consumed divided by the number of calories burnt. Centers for Disease Control and Prevention (CDC) has guidelines for healthy weights and information on how to lose weight.

Some advocate restricting weight to a greater extent, which is known as calorie restriction. It’s unknown whether calorie restriction increases lifespan in humans or not, but moderate calorie restriction with adequate nutrition decreases risk of obesity, type 2 diabetes, inflammation, hypertension, cardiovascular disease, and metabolic risk factors associated with cancer, and is the most effective way of consistently increasing lifespan in a variety of organisms. The CR Society has information on getting started on calorie restriction.4

 

How much to drink

Generally, drinking enough to rarely feel thirsty and to have colorless or light yellow urine is usually sufficient. It’s also possible to drink too much water. In general, drinking too much water is rare in healthy adults who eat an average American diet, although endurance athletes are at a higher risk.10

 

Exercise

A meta-analysis found the data in the following graphs for people aged over 40.

8

A weekly total of roughly five hours of vigorous exercise has been identified by several studies to be the safe upper limit for life expectancy. It may be beneficial to take one or two days off from vigorous exercise per week and to limit chronic vigorous exercise to <= 60 min/day.9 Based on the above, I my best guess for the optimal amount of exercise for longevity is roughly 30 MET-hr/wk. Calisthenics burn 6-10 METs/hr11, so an example exercise routine to get this amount of exercise is doing calisthenics 38 minutes per day and 6 days/wk. Guides on how to exercise are available, e.g. this one.

 

Carcinogens

Carcinogens are cancer-causing substances. Since cancer causes death, decreasing exposure to carcinogens presumably decreases one’s risk of death. Some foods are also carcinogenic, as discussed in the “Food” section.

 

Chemicals

Tobacco use is the greatest avoidable risk factor for cancer worldwide, causing roughly 22% of cancer deaths. Additionally, second hand smoke has been proven to cause lung cancer in nonsmoking adults.

Alcohol use is a risk factor for many types of cancer. The risk of cancer increases with the amount of alcohol consumed, and substantially increases if one is also a heavy smoker. The attributable fraction of cancer from alcohol use varies depending on gender, due to differences in consumption level. E.g. 22% of mouth and oropharynx cancer is attributable to cancer in men but only 9% is attributable to alcohol in women.

Environmental air pollution accounts for 1-4% of cancer.84 Diesel exhaust is one type of carcinogenic air pollution. Those with the highest exposure to diesel exhaust are exposed to it occupationally. As for residential exposure, diesel exhaust is highest in homes near roads where traffic is heaviest. Limiting time spent near large sources of diesel exhaust decreases exposure. Benzene, another carcinogen, is found in gasoline and vehicle exhaust but exposure to it can also be cause by being in areas with unventilated fumes from gasoline, glues, solvents, paints, and art supplies. It can cause exposure from inhalation or skin contact.86

Some occupations exposure workers to occupational carcinogens.84 A list of some of the occupations is here, all of which involve manual labor, except for hospital-related jobs.87

 

Infections

Infections are responsible for 6% of cancer deaths in developed nations.84 Many of the infections are spread via sexual contact and sharing needles and some can be vaccinated against.85

 

Radiation

Ionizing radiation is carcinogenic to humans. Residential exposure to radon gas is estimated to cause 3-14% of lung cancers, which is the largest source of radon exposure for most people 84 Being exposed to radon and cigarette smoke together increases one’s cancer risk much more than they do separately. There is much variation radon levels depending on where one lives and and radon is usually higher inside buildings, especially levels closer to the ground, such as basements. The EPA recommends taking action to reduce radon levels if they are greater than or equal to 4.0 pCi/L. Radon levels can be reduced by a qualified contractor. Reducing radon levels without proper training and equipment can increase instead of decrease them.88

Some medical tests can also increase exposure to radiation. The EPA estimates that exposure to 10 mSv from a medical imaging test increases risk of cancer by  roughly 0.05%. To decrease exposure to radiation from medical imaging tests, one can ask if there are ways to shield parts of one’s body from radiation that aren’t being tested and making sure  the doctor performing the test is qualified.89

 

Small doses of ionizing radiation increase risk by a very small amount. Most studies haven’t detected increased cancer risk in people exposed to low levels of ionizing radiation. For example, people living in higher altitudes don’t have noticeably higher cancer rates than other people. In general, cancer risk from radiation increases as the dose of radiation increases and there is thought to be no safe level of exposure. Ultraviolet radiation as a type of radiation that can be ionizing radiation. Sunlight is the main source of ultraviolet radiation.84

Factors that increase one’s exposure to ultraviolet radiation when outside include:

  • Time of day. Almost ⅓ of UV radiation hits the surface between 11AM and 1PM, and ¾ hit the surface between 9AM and 5PM.  

  • Time of year. UV radiation is greater during summer. This factor is less significant near the equator.

  • Altitude. High elevation causes more UV radiation to penetrate the atmosphere.

  • Clouds. Sometimes clouds decrease levels of UV radiation because they block UV radiation from the sun. Other times, they increase exposure because they reflect UV radiation.

  • Reflection off surfaces, such as water, sand, snow, and grass increases UV radiation.

  • Ozone density, because ozone stops some UV radiation from reaching the surface.

Some tips to decrease exposure to UV radiation:

  • Stay in the shade. This is one of the best ways to limit exposure to UV radiation in sunlight.

  • Cover yourself with clothing.

  • Wear sunglasses.

  • Use sunscreen on exposed skin.90

 

Tanning beds are also a source of ultraviolet radiation. Using tanning booths can increase one’s chance of getting skin melanoma by at least 75%.91

 

Vitamin D3 is also produced from ultraviolet radiation, although the American Society for Clinical Nutrition states that vitamin D is readily available from supplements and that the controversy about reducing ultraviolet radiation exposure was fueled by the tanning industry.92

 

There could be some risk of cell phone use being associated with cancer, but the evidence is not strong enough to be considered causal and needs to be investigated further.93, 118

 

Emotions and feelings

Positive emotions and feelings

A review suggested that positive emotions and feelings decreased mortality. Proposed mechanisms include positive emotions and feelings being associated with better health practices such as improved sleep quality, increased exercise, and increased dietary zinc consumption, as well as lower levels of some stress hormones. It has also been hypothesized to be associated with other health-relevant hormones, various aspects of immune function, and closer and more social contacts.33 Less Wrong has a good article on how to be happy.

 

Psychological distress

A meta-analysis was conducted on psychological stress. To measure psychological stress, it used the GHQ-12 score, which measured symptoms of anxiety, depression, social dysfunction, and loss of confidence. The scores range from 0 to 12, with 0 being asymptomatic, 1-3 being subclinically symptomatic, 4-6 being symptomatic, and 7-12 being highly symptomatic. It found the results shown in the following graphs.

http://www.bmj.com/content/bmj/345/bmj.e4933/F3.large.jpg?width=800&height=600

This association was essentially unchanged after controlling for a range of covariates including occupational social class, alcohol intake, and smoking. However, reverse causality may still partly explain the association.30

 

Stress

A study found that individuals with moderate and high stress levels as opposed to low stress had hazard ratios (HRs) of mortality of 1.43 and 1.49, respectively.27 A meta-analysis found that high perceived stress as opposed to low perceived stress had a coronary heart disease relative risk (RR) of 1.27. The mean age of participants in the studies used in the meta-analysis varied from 44 to 72.5 years and was significantly and positively associated with effect size. It explained 46% of the variance in effect sizes between the studies used in the meta-analysis.28

A cross-sectional study (which is a relatively weak study design) not in the aforementioned meta-analysis used 28,753 subjects to study the effect on mortality from the amount of stress and the perception of whether stress is harmful or not. It found that neither of these factors predicted mortality independently, but but that taken together, they did have a statistically significant effect. Subjects who reported much stress and that stress has a large effect on health had a HR of 1.43 (95% CI: 1.2, 1.7). Reverse causality may partially explain this though, as those who have had negative health impacts from stress may have been more likely to report that stress influences health.83

 

Anger and hostility

A meta-analysis found that after fully controlling for behavior covariates such as smoking, physical activity or body mass index, and socioeconomic status, anger and hostility was not associated with coronary heart disease (CHD), though the results are inconclusive.34

 

Social and personality factors

Social status

A review suggested that social status is linked to health via gender, race, ethnicity, education levels, socioeconomic differences, family background, and old age.46

 

Giving to others

An observational study found that stressful life events was not a predictor for mortality for those who engaged in unpaid helping behavior directed towards friends, neighbors, or relatives who did not live with them. This association may be due to giving to others causing one to have a sense of mattering, opportunities for generativity, improved social well-being, the emotional state of compassion, and the physiology of the caregiving behavioral system.35

 

Social relationships

A large meta-analysis found that the odds ratio of mortality of having weak social relationships is 1.5 (95% confidence interval (CI): 1.42 to 1.59). However, this effect may be a conservative estimate. Many of the studies used in the meta-analysis used single item measures of social relations, but the size of the association was greatest in studies that used more complex measurements. Additionally, some of the studies in the meta-analysis adjusted for risk factors that may be mediators of social relationships’ effect on mortality (e.g. behavior, diet, and exercise). Many of the studies in the meta-analysis also ignored the quality of social relationships, but research suggests that negative social relationships are linked to increased mortality. Thus, the effect of social relationships on mortality could be even greater than the study found.

Concerning causation, social relationships are linked to better health practices and psychological processes, such as stress and depression, which influence health outcomes on their own. However, the meta-analysis also states that social relationships exert an independent effect. Some studies show that social support is linked to better immune system functioning and to immune-mediated inflammatory processes.36

 

Conscientiousness

A cohort study with 468 deaths found that each 1 standard deviation decrease in conscientiousness was associated with HR being multiplied by 1.07 (95% CI: 0.98 – 1.17), though it gave no mechanism for the association.39 Although it adjusted for several variables, (e.g.  socioeconomic status, smoking, and drinking), it didn’t adjust for drug use, risky driving, risky sex, suicide, and violence, which were all found by a meta-analysis to have statistically significant associations with conscientiousness.40 Overall, it seems to me that conscientiousness doesn’t seem to have a significant effect on mortality.

 

Infectious diseases

Mayo clinic has a good article on preventing infectious disease.

 

Dental health

A cohort study of 5611 adults found that compared to men with 26-32 teeth, men with 16-25 teeth had an HR of 1.03 (95% CI: 0.91-1.17), men with 1-15 teeth had an HR of 1.21 (95% CI: 1.05-1.40) and men with 0 teeth had an HR of 1.18 (95% CI: 1.00-1.39).

In the study, men who never brushed their teeth at night had a HR of 1.34 (95% CI: 1.14-1.57) relative to those who did every night. Among subjects who brushed at night, HR was similar between those who did and didn’t brush daily in the morning or day. The HR for men who brushed in the morning every day but not at night every day was 1.19 (95% CI: 0.99-1.43).

In the study, men who never used dental floss had an HR of 1.27 (95% CI: 1.11-1.46) and those who sometimes used it had an HR or 1.14 (95% CI: 1.00-1.30) compared to men who used it every day. Among subjects who brushed their teeth at night daily, not flossing was associated with a significantly increased HR.

Use of toothpicks didn’t significantly decrease HR and mouthwash had no effect.

The study had a list of other studies on the effect of dental health on mortality. It seems to us that almost all of them found a negative correlation between dental health and risk of mortality, although the study didn’t say their methodology for selecting the studies to show. I did a crude review of other literature by only looking at their abstracts and found that five studies found that poor dental health increased risk of mortality and one found it didn’t.

Regarding possible mechanisms, the study says that toothpaste helps prevent dental caries and that dental floss is the most effective means of removing interdental plaque and decreasing interdental gingival inflammation.38

 

Sleep

It seems that getting too little or too much sleep likely increases one’s risk of mortality, but it’s hard to tell exactly how much is too much and how little is too little.

 

One review found that the association between amount of sleep and mortality is inconsistent in studies and that what association does exist may be due to reverse-causality.41 However, a meta-analysis found that the RR associated with short sleep duration (variously defined as sleeping from < 8 hrs/night to < 6 hrs/night) was 1.10 (95% CI: 1.06-1.15). It also found that the RR associated with long sleep duration (variously defined as sleeping for > 8 hrs/night to > 10 hrs per night) compared with medium sleep duration (variously defined as sleeping for 7-7.9 hrs/night to 9-9.9 hrs/night) was 1.23 (95% CI: 1.17 - 1.30).42

 

The National Heart, Lung, and Blood Institute and Mayo Clinic recommend adults get 7-8 hours of sleep per night, although it also says sleep needs vary from person to person. It gives no method of determining optimal sleep for an individual. Additionally, it doesn’t say if its recommendations are for optimal longevity, optimal productivity, something else, or a combination of factors.43 The Harvard Medical School implies that one’s optimal amount of sleep is enough sleep to not need an alarm to wake up, though it didn’t specify the criteria for determining optimality either.45

 

Drugs

None of the drugs I’ve looked into have a beneficial effect for the people without a special disease or risk factor. Notes on them are here.

 

Blood donation

A quasi-randomized experiment with a validity near that of a randomized trial presumably suggested that blood donation didn’t significantly decrease risk of coronary heart disease (CHD). Observational studies have shown much lower CHD incidence among donors, although the authors of the former experiment suspect that bias and reverse causation played a role in this.29 That said, a review found that reverse causation accounted for only 30% of the effect of blood donation, though I haven't been able to find the review. RomeoStevens suggests that the potential benefits of blood donation are high enough and the costs are low enough that blood donation is worth doing.120

 

Sitting

After adjusting for amount of physical activity, a meta-analysis estimated that for every one hour increment of sitting in intervals 0-3, >3-7 and >7 h/day total sitting time, the hazard ratios of mortality were 1.00 (95% CI: 0.98-1.03), 1.02 (95% CI: 0.99-1.05) and 1.05 (95% CI: 1.02-1.08) respectively. It proposed no mechanism for sitting time having this effect,37 so it might have been due to confounding variables it didn’t control.

 

Sleep apnea

Sleep apnea is an independent risk factor for mortality and cardiovascular disease.26 Symptoms and other information on sleep apnea are here.

 

Snoring

A meta-analysis found that self-reported habitual snoring had a small but statistically significant association with stroke and coronary heart disease, but not with cardiovascular disease and all-cause mortality [HR 0.98 (95% CI: 0.78-1.23)]. Whether the risk is due to obstructive sleep apnea is controversial. Only the abstract is able to be viewed for free, so I’m just basing this off the abstract.31

 

Exams

The organization Susan G. Komen, citing a meta-analysis that used randomized controlled trials, doesn’t recommend breast self exams as a screening tool for breast cancer, as it hasn’t been shown to decrease cancer death. However, it still stated that it is important to be familiar with one’s breasts’ appearance and how they normally feel.49 According to the Memorial Sloan Kettering Cancer Center, no study has been able to show a statistically significant decrease in breast cancer deaths from breast self-exams.50 The National Cancer Institute states that breast self-examinations haven’t been shown to decrease breast cancer mortality, but does increase biopsies of benign breast lesions.51

The American Cancer Society doesn’t recommend testicular self-exams for all men, as they haven’t been studied enough to determine if they decrease mortality. However, it states that men with risk factors of testicular cancer (e.g. an undescended testical, previous testicular cancer, of a family member who previously had testicular cancer) should consider self-exams and discuss them with a doctor. The American Cancer Society also recommends having testicular self-exams in routine cancer-related check-ups.52

 

Genomics

Genomics is the study of genes in one’s genome, and may help increase health by using knowledge of one’s genes to have personalized treatment. However, it hasn’t proved to be useful for most; recommendations rarely change after knowledge from genomic testing. Still, genomics has much future potential.102

 

Aging

Like I’ve said in the section “Can we become immortal,” the proportion of deaths that are caused by aging in the industrial world approaches 90%,53 but some organizations and companies are working on curing it.54, 55, 56

One could support these organizations in an effort to hasten the development of anti-aging therapies, although I doubt an individual would have a noticeable impact on one’s own chance of death unless one is very wealthy. That said, I have little knowledge in investments, but I suppose investing in companies working on curing aging may be beneficial, as if they succeed, they may offer an enormous return on investment, and if they fail, one would probably die, so losing one’s money may not be as bad. Calico currently isn’t a public stock, though.

 

External causes of death

Unless otherwise specified, graphs in this section are on data collected from American citizens ages 15-24, as based off the Less Wrong census results, this seems to be the most probable demographic that will read this. For this demographic, external causes cause 76% of deaths. Note that although this is true, one is much more likely to die when older than when aged 15-24, and older individuals are much more likely to die from disease than from external causes of death. Thus, I think it’s more important when young to decrease risk of disease than external causes of death. The graph below shows the percentage of total deaths from external causes caused by various causes.

21

 

Transport accidents

Below are the relative death rates of specified means of transportation for people in general:

71

Much information about preventing death from car crashes is here. Information on preventing death from car crashes is here, here, here, and here.

 

Assault

Lifehacker's “Basic Self-Defense Moves Anyone Can Do (and Everyone Should Know)” gives a basic introduction to self defence.

 

Intentional self harm

Intentional self harm such as suicide, presumably, increases one’s risk of death.47 Mayo Clinic has a guide on preventing suicide. I recommend looking at it if you are considering killing yourself. Additionally, if are are considering killing yourself, I suggest reviewing the potential rewards of achieving immortality from the section “Should we try to become immortal.”

 

Poisoning

What to do if a poisoning occurs

CDC recommends staying calm, dialing 1-800-222-1222, and having this information ready:

  • Your age and weight.

  • If available, the container of the poison.

  • The time of the poison exposure.

  • The address where the poisoning occurred.

It also recommends staying on the phone and following the instructions of the emergency operator or poison control center.18

 

Types of poisons

Below is a graph of the risk of death per type of poison.

21

Some types of poisons:

  • Medicine overdoses.

  • Some household chemicals.

  • Recreational drug overdoses.

  • Carbon monoxide.

  • Metals such as lead and mercury.

  • Plants12 and mushrooms.14

  • Presumably some animals.

  • Some fumes, gases, and vapors.15

 

Recreational drugs

Using recreational drugs increases risk of death.

 

Medicine overdoses and household chemicals

CDC has tips for these here.

 

Carbon monoxide

CDC and Mayo Clinic have tips for this here and here.

 

Lead

Lead poisoning causes 0.2% of deaths worldwide and 0.0% of deaths in developed countries.22 Children under the age of 6 are at higher risk of lead poisoning.24 Thus, for those who aren’t children, learning more about preventing lead poisoning seems like more effort than it’s worth. No completely safe blood lead level has been identified.23

 

Mercury

MedlinePlus has an article on mercury poisoning here.

 

Accidental drowning

Information on preventing accidental drowning from CDC is here and here.

 

Inanimate mechanical forces

Over half of deaths from inanimate mechanical forces for Americans aged 15-24 are from firearms. Many of the other deaths are from explosions, machinery, and getting hit by objects. I suppose using common sense, precaution, and standard safety procedures when dealing with such things is one’s best defense.

 

Falls

Again, I suppose common sense and precaution is one’s best defense. Additionally, alcohol and substance abuse is a risk factor of falling.72

 

Smoke, fire and heat

Owning smoke alarms halves one’s risk of dying in a home fire.73 Again, common sense when dealing with fires and items potentially causing fires (e.g. electrical wires and devices) seems effective.

 

Other accidental threats to breathing

Deaths from other accidental threats to breathing are largely caused by strangling or choking on food or gastric contents, and occasionally by being in a cave-in or trapped in a low-oxygen environment.21 Choking can be caused by eating quickly or laughing while eating.74 If you are choking:

  • Forcefully cough. Lean as far forwards as you can and hold onto something that is firmly anchored, if possible. Breathe out and then take a deep breath in and cough; this may eject the foreign object.

  • Attract someone’s attention for help.75

 

Additionally, choking can be caused by vomiting while unconscious, which can be caused by being very drunk.76 I suggest lying in the recovery position if you think you may vomit while unconscious, so as to to decrease the chance of choking on vomit.77 Don’t forget to use common sense.

 

Electric current

Electric shock is usually caused by contact with poorly insulated wires or ungrounded electrical equipment, using electrical devices while in water, or lightning.78 Roughly ⅓ of deaths from electricity are caused by exposure to electric transmission lines.21

 

Forces of nature

Deaths from forces of nature in (for Americans ages 15-24) in descending order of number of deaths caused are: exposure to cold, exposure to heat, lightning, avalanches or other earth movements, cataclysmic storms, and floods.21 Here are some tips to prevent these deaths:

  • When traveling in cold weather, carry emergency supplies in your car and tell someone where you’re heading.79

  • Stay hydrated during hot weather.80

  • Safe locations from lightning include substantial buildings and hard-topped vehicles. Safe locations don’t include small sheds, rain shelters, and open vehicles.

  • Wait until there are no thunderstorm clouds in the area before going to a location that isn’t lightning safe.81

 

Medical care

Since medical care is tasked with treating diseases, receiving medical care when one has illnesses presumably decreases risk of death. Though necessary medical care may be essential when one has illnesses, a review estimated that preventable medical errors contributed to roughly 440,000 deaths per year in the US, which is roughly one-sixth of total deaths in the US. It gave a lower limit of 210,000 deaths per year.

The frequency of deaths from preventable medical errors varied across studies used in the review, with a hospital that was shown the put much effort into improving patient safety having a lower proportion of deaths from preventable medical errors than that of others.57 Thus, I suppose that it would be beneficial to go to hospitals that are known for their dedication to patient safety. There are several rankings of hospital safety available on the internet, such as this one. Information on how to help prevent medical errors is found here and under the “What Consumers Can Do” section here. One rare medical error is having a surgery be done on the wrong body part. The New York Times gives tips for preventing this here.

Additionally, I suppose it may be good to live relatively close to a hospital so as to be able to quickly reach it in emergencies, though I’ve found no sources stating this.

A common form of medical care are general health checks. A comprehensive Cochrane review with 182,880 subjects concluded that general health checks are probably not beneficial.107 A meta-analysis found that general health checks are associated with small but statistically significant benefits in factoring related to mortality, such as blood pressure and body mass index. However, it found no significant association with mortality.109 The New York Times acknowledged that health checks are probably not beneficial and gave some explanation why general health checks are nonetheless still common.108 However, CDC and MedlinePlus recommend getting routine general health checks. The cited no studies to support their claims.104, 106 When I contacted CDC about it, it responded, “Regular health exams and tests can help find problems before they start. They also can help find problems early, when your chances for treatment and cure are better. By getting the right health services, screenings, and treatments, you are taking steps that help your chances for living a longer, healthier life,” a claim that doesn’t seem supported by evidence. It also stated, “Although CDC understands you are concerned, the agency does not comment on information from unofficial or non-CDC sources.” I never heard back from MedlinePlus.

 

Cryonics

Cryonics is the freezing of legally dead humans with the purpose preserving their bodies so they can be brought back to life in the future once technology makes it possible. Human tissue have been cryopreserved and then brought back to life, although this has never been done on full humans.59 The price of Cryonics at least ranges from $28,000 to $200,000.60 More information on cryonics is on LessWrong Wiki.

 

Money

Cryonics, medical care, safe housing, and basic needs all take money. Rejuvenation therapy may also be very expensive. It seems valuable to have a reasonable amount of money and income.

 

Future advancements

Keeping updated on further advancements in technology seems like a good idea, as not doing so would prevent one from making use of future technologies. Keeping updated on advancements on curing aging seems especially important, due to the massive number of casualties it inflicts and the current work being done to stop it. Updates on mind-uploading seem important as well. I don’t know of any very efficient method of keeping updated on new advancements, but periodically googling for articles about curing aging or Calico and searching for new scientific articles on topics in this guide seems reasonable. As knb suggested, it seems beneficial to periodically check on Fight Aging, a website advocating anti-aging therapies. I’ll try to do this and update this guide with any new relevant information I find.

There is much uncertainty ahead, but if we’re clever enough, we just might make it though alive.

 

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Bill Gates: problem of strong AI with conflicting goals "very worthy of study and time"

50 ciphergoth 22 January 2015 08:21PM

Steven Levy: Let me ask an unrelated question about the raging debate over whether artificial intelligence poses a threat to society, or even the survival of humanity. Where do you stand?

Bill Gates: I think it’s definitely important to worry about. There are two AI threats that are worth distinguishing. One is that AI does enough labor substitution fast enough to change work policies, or [affect] the creation of new jobs that humans are uniquely adapted to — the jobs that give you a sense of purpose and worth. We haven’t run into that yet. I don’t think it’s a dramatic problem in the next ten years but if you take the next 20 to 30 it could be. Then there’s the longer-term problem of so-called strong AI, where it controls resources, so its goals are somehow conflicting with the goals of human systems. Both of those things are very worthy of study and time. I am certainly not in the camp that believes we ought to stop things or slow things down because of that. But you can definitely put me more in the Elon Musk, Bill Joy camp than, let’s say, the Google camp on that one.

"Bill Gates on Mobile Banking, Connecting the World and AI", Medium, 2015-01-21

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