A Gamification Of Education: a modest proposal based on the Universal Decimal Classification and RPG skill trees

13 Ritalin 07 July 2013 06:27PM

While making the inventory of my personal library and applying the Universal Decimal System to its classification, I found myself discovering a systematized classification of fields of knowledge, nested and organized and intricate, many of which I didn't even know existed. I couldn't help but compare how information was therein classified, and how it was imparted to me in engineering school. I also thought about how, often, software engineers and computer scientists were mostly self-thought, with even college mostly consisting of "here's a problem: go forth and figure out a way to solve it". This made me wonder whether another way of certified and certifiable education couldn't be achieved, and a couple of ideas sort of came to me.

It's pretty nebulous in my mind so far, but the crux of the concept would be a modular structure of education, where the academic institution essentially established what information precisely you need from each module, and lets you get on with the activity of learning, with periodic exams that you can sign up for, which will certify your level and area of proficiency in each module.

A recommended tree of learning can be established, but it should be possible to not take every intermediate test, if passing the final test proves that you've passed all the others behind it (this would allow people coming from different academic systems to certify their knowledge quickly and easily, thus avoiding the classic "Doctor in Physics from Former Soviet Union, current Taxi Driver in New York" scenario).

Thus, a universal standard of how much you have proven to know about what topics can be established.

Employers would then be free to request profiles in the format of such a tree. It need not be a binary "you need to have done all these courses and only these courses to work for us", they could be free to write their utility function for this or that job however they would see fit, with whichever weights and restrictions they would need.

Students and other learners would be free to advance in whichever tree they required, depending on what kind of profile they want to end up with at what age or point in time. One would determine what to learn based on statistical studies of what elements are, by and large, most desired by employers of/predictors of professional success in a certain field you want to work in.

One would find, for example, that mastering the peculiar field of railway engineering is great to be a proficient railway engineer, but also that having studied, say, things involved with people skills (from rhetoric to psychology to management), correlates positively with success in that field.

Conversely, a painter may find that learning about statistics, market predictions, web design, or cognitive biases correlates with a more successful career (whether it be on terms of income, or in terms of copies sold, or of public exposure... each one may optimize their own learning according to their own criteria).

One might even be able to calculate whether such complimentary education is actually worth their time, and which of them are the most cost-efficient.

I would predict that such a system would help society overall optimize how many people know what skills, and facilitate the learning of new skills and the updating of old ones for everyone, thus reducing structural unemployment, and preventing pigeonholing and other forms of professional arthritis.

I would even dare to predict that, given the vague, statistical, cluster-ish nature of this system, people would be encouraged to learn quite a lot more, and on a quite wider range of fields, than they do now, when one must jump through a great many hoops and endure a great many constraints in space and time and coin to get access to some types of educations (and to the acknowledgement of their acquisition thereof).

Acquiring access to the actual sources of knowledge, a library (virtual or otherwise), lectures (virtual or otherwise), and so on, would be a private matter, up to the learner:

  • some of them already have the knowledge and just need to get it certified,
  • others can actually buy the books they want/need, especially if keeping them around as reference will be useful to them in the future,
  • others can subscribe to one or many libraries, of the on-site sort or by correspondence
  • others can buy access to pre-recorded lectures, peruse lectures that are available for free, or enroll in academic institutions whose ostensible purpose is to give lectures and/or otherwise guide students through learning, more or less closely
  • the same applies to finding study groups with whom you can work on a topic together: I can easily imagine dedicated social networks could be created for that purpose, helping people pair up with each other based on mutual distance, predicted personal affinity, mutual goals, backgrounds, and so on. Who knows what amazing research teams might be borne of the intellectual equivalent of OK!Cupid.

A thing that I would like very much about this system is that it would free up the strange conflicts of interest that hamper the function of traditional educational institutions.

When the ones who teach you are also the ones who grade you, the effort they invest in you can feel like a zero-sum game, especially if they are only allowed to let a percentage of you pass.

When the ones who teach you have priorities other than teach (usually research, but some teachers are also involved in administrative functions, or even private interests completely outside of the university's ivory tower1), this can and often does reduce the energy and dedication they can/will allocate to the actual function of teaching, as opposed to the others.

By separating these functions, and the contradictory incentives they provide, the organizations performing them are free to optimize for each: 

  • Testing is optimized for predicting current and future competence in a subject: the testers whose tests are the most reliable have more employers requiring their certificates, and thus more people requesting that they test them
  • Teaching is optimized for getting the knowledge through whatever the heck the students want, whether it be to succeed at the tests or to simply master the subject (I don't know much game theory, but I'd naively guess that the spontaneous equilibrium between the teaching and testing institutions would lead to both goals becoming identical).
  • Researching is optimized for research (researchers are not teachers. dang it, those are very different skill-sets!). However researchers and other experts get to have a pretty big say in what the tests test for and how, because their involvement makes the tests more trustworthy for employers, and because they, too, are employers.
  • And of course entire meta-institutions can spring from this, whose role is to statistically verify, over the long term,
    • how good a predictor of professional success in this or that field is passing the corresponding test, and
    • how good a predictor of passing the test is to be taught by this or that teaching institution.
    • how good a predictor of the test being reliable is the input of these or those researchers and experts
  • It occurs to me now that, if one wished to be really nitpicky about who watches the watchmen, I suspect that there would be institutions testing the reliability of those meta-institutions, and so on and so forth... When does it stop? How to avoid vested interests and little cheats and manipulations pulling an academic equivalent of the AAA certification of sub-prime junk debt in 2008?

Another discrepancy I'd like to see solved is the difference between the official time it is supposed to take to obtain this or that degree, to learn this or that subject, and the actual statistical distribution of that time. Nowadays, a degree that's supposed to take you five years ends up taking up eight or ten years of your life. You find yourself having to go through the most difficult subjects again and again, because they are explained in an extremely rushed way, the materials crammed into a pre-formatted time. Other subjects are so exceedingly easy and thinly-spread that you find that going to class is a waste of time, and that you're better off preparing for it one week before finals. Now, after having written all of the above, my mind is quite spent, and I don't feel capable of either anticipating the effect of my proposed idea on this particular, nor of offering any solutions. Nevertheless, I wish to draw attention to this, so I'm leaving this paragraph in until I can amend it to something more useful/promising.

I hereby submit this idea to the LW community for screening and sound-boarding. I apologize in advance for your time, just in case this idea appears to be flawed enough to be unsalvageable. If you deem the concept good but flawed, we could perhaps work on ironing those kinks together. If, afterwards, this seems to you like a good enough idea to implement, know that good proposals are a dime a dozen; if there is any interest in seeing something like this happen, we can need to move on to proprely understanding the current state of secondary/superior/higher education, and figuring out of what incentives/powers/leverages are needed to actually get it implemented.

 



 

1By ivory tower I simply mean the protected environment where professors teach, researchers research, and students study, with multiple buffers between it and the ebb and flow of political, economical, and social turmoil. No value judgement is intended.

 


 

EDIT: And now I look upon the title of this article and realize that, though I had comparisons to games in mind, I never got around to writing them down. My inspirations here were mostly Civilization's Research Trees, RPG Skill Scores and Perks, and, in particular, Skyrim's skills and perks tree.

Basically, your level at whatever skill improves by studying and by practising it rather than merely by levelling up, and, when you need to perform a task that's outside your profile, you can go and learn it without having to commit to a class. Knowing the right combination of skills at the right level lets you unlock perks or access previously-unavailable skills and applications. What I like the most about it is that there's a lot of freedom to learn what you want and be who you want to be according to your own tastes and wishes, but, overall, it sounds sensible and is relatively well-balanced. And of course there's the fact that it allows you to keep a careful tally of how good you are at what things, and the sense of accomplishment is so motivating and encouraging!

Speaking of which, several netwroks and consoles' Achievement systems also strike me as motivators for keeping track of what one has achieved so far, to look back and be able to say "I've come a long way" (in an effect similar to that of gratitude journals), and also to accomplish a task and have this immediate and universal acknowledgement that you did it dammit (and, for those who care about that kind of thing, the chance to rub it the face of those who haven't).

I would think our educational systems could benefit from this kind of modularity and from this ability to keep track of things in a systematic way. What do you guys think?

Effective Altruism Through Advertising Vegetarianism?

20 peter_hurford 12 June 2013 06:50PM

Abstract: If you value the welfare of nonhuman animals from a consequentialist perspective, there is a lot of potential for reducing suffering by funding the persuasion of people to go vegetarian through either online ads or pamphlets.  In this essay, I develop a calculator for people to come up with their own estimates, and I personally come up with a cost-effectiveness estimate of $0.02 to $65.92 needed to avert a year of suffering in a factory farm.  I then discuss the methodological criticism that merits skepticism of this estimate and conclude by suggesting (1) a guarded approach of putting in just enough money to help the organizations learn and (2) the need for more studies should be developed that explore advertising vegetarianism in a wide variety of media in a wide variety of ways, that include decent control groups.

-

Introduction

I start with the claim that it's good for people to eat less meat, whether they become vegetarian -- or, better yet, vegan -- because this means less nonhuman animals are being painfully factory farmed.  I've defended this claim previously in my essay "Why Eat Less Meat?".  I recognize that some people, even those who consider themselves effective altruists, do not value the well-being of nonhuman animals.  For them, I hope this essay is interesting, but I admit it will be a lot less relevant.

The second idea is that it shouldn't matter who is eating less meat.  As long as less meat is being eaten, less animals will be farmed, and this is a good thing.  Therefore, we should try to get other people to also try and eat less meat.

The third idea is that it also doesn't matter who is doing the convincing.  Therefore, instead of convincing our own friends and family, we can pay other people to convince people to eat less meat.  And this is exactly what organizations like Vegan Outreach and The Humane League are doing.  With a certain amount of money, one can hire someone to distribute pamphlets to other people or put advertisements on the internet, and some percentage of people who receive the pamphlets or see the ads will go on to eat less meat.  This idea and the previous one should be uncontroversial for consequentialists.

But the fourth idea is the complication.  I want my philanthropic dollars to go as far as possible, so as to help as much as possible.  Therefore, it becomes very important to try and figure out how much money it takes to get people to eat less meat, so I can compare this to other estimations and see what gets me the best "bang for my buck".


Other Estimations

I have seen other estimates floating around the internet that try to estimate the cost of distributing pamphlets, how many conversions each pamphlet produces, and how much less meat is ate via each conversion.  Brian Tomasik calculates $0.02 to $3.65 [PDF] per year of nonhuman animal suffering prevented, later $2.97 per year, and then later $0.55 to $3.65 per year.

Jess Whittlestone provides statistics that reveal an estimate of less than a penny per year[1]. 

Effective Animal Activism, a non-profit evaluator for animal welfare charities, came up with an estimate [Excel Document] of $0.04 to $16.60 per year of suffering averted, that also takes into account a variety of additional variables, like product elasticity.

Jeff Kaufman uses a different line of reasoning, by estimating how many vegetarians there are and guessing how many of them came via pamphlets, estimates it would take $4.29 to $536 to make someone vegetarian for one year.  Extrapolating from that using at a rate of 255 animals saved per year and a weighted average of 329.6 days lived per animal (see below for justification of both assumptions), would give $0.02 to $1.90 per year of suffering averted[2].

A third line of reasoning, also by Jeff Kaufman, was to measure the amount of comments on the pro-vegetarian websites advertised in these campaigns and found that 2-22% of them were about an intended behavior change (eating less meat, going vegetarian, or going vegan), depending on the website.  I don't think we can draw any conclusions from this, but it's interesting.

To make my calculations, I decided to make a calculator.  Unfortunately, I can't embed it here, so you'd have to open it in a new tab as a companion piece.

I'm going to start by using the following formula: Years of Suffering Averted per Dollar = (Pamphlets / dollar) * (Conversions / pamphlet) * (Veg years / conversion) * (Animals saved / veg year) * (Days lived / animal)

Now, to get estimations for these variables.


Pamphlets Per Dollar

How much does it cost to place the advertisement, whether it be the paper pamphlet or a Facebook advertisement?  Nick Cooney, head of the Humane League, says the cost-per-click of Facebook ads is 20 cents.

But what about the cost per pamphlet?  This is more of a guess, but I'm going to go with <a href="">Vegan Outreach's suggested donation of $0.13 per "Compassionate choices" booklet.

However, it's important to note that this cost must also include opportunity cost -- leafleters must forego the ability to use that time to work a job.  This means I must include an opportunity cost of say $8/hr on top of that, making the actual cost $0.27 assuming a pamphlet is given out each minute of volunteer time, meaning 3.7 people are reached per dollar from pamphlets.  For Facebook advertisements, the opportunity cost is trivial.


Conversions Per Pamphlet

This is the estimate with the biggest target on it's head, so to speak.  How many people do we get to actually change their behavior with a simple pamphlet or Facebook advertisement?  Right now, we have three lines of evidence:

Facebook Study

Humane League did A $5000 Facebook advertisement campaign.  They bought ads that look like this...

 

...and sent people to websites (like this one or this one) with auto-playing videos that start playing and show the horrors of factory farming.

Afterward, there was another advertisement run to people who "liked" the video page, offering a 1 in 10 chance of winning a free movie ticket in order to take a survey.  Everyone who emailed in asking for a free vegetarian starter kit were also emailed a survey.  104 people took the survey and there were 32 reported vegetarians[3] and 45 people reported, for example, that their chicken consumption decreased "slightly" or "significantly".

7% of visitors liked the page and 1.5% of visitors ordered a starter kit.  Assuming all the other people went away from the video not changing their consumption, this survey would lead us to (very tenuously) think about 2.6% of people seeing the video will become a vegetarian[4].

(Here's the results of the survey in PDF.)

Pamphlet Study

A second study discussed in "The Powerful Impact of College Leafleting (Part 1)" and "The Powerful Impact of College Leafleting: Additional Findings and Details (Part 2)" looked specifically at pamphlets.

Here, Humane League staff visited two large East Coast state schools and distributed leaflets.  They then returned two months later and surveyed people walking by.  Those who remember receiving a leaflet earlier were counted.  They found about 2% of those receiving a pamphlet went vegetarian.

Vegetarian Years Per Conversion

But once a pamphlet or Facebook advertisement captures someone, how long will they stay vegetarian?  One survey showed vegetarians refrain from eating meat for an average of 6 years or more.  Another study I found says 93% of vegetarians stay vegetarian for at least three years.

 

Animals Saved Per Vegetarian Year

And once you have a vegetarian, how many animals do they save per year?  CountingAnimals says 406 animals saved per year.

The Humane League suggests 28 chickens, 2 egg industry hens, 1/8 beef cow, 1/2 pig, 1 turkey, and 1/30 dairy cow per year (total = 31.66 animals), and does not provide statistics on fish.  This agrees with CountingAnimals on non-fish totals.

Days Lived Per Animal

One problem, however, is that saving a cow that could suffer for years is different from saving a chicken that suffers for only about a month.  Using data from Farm Sanctuary plus World Society for the Protection of Animals data on fish [PDF], I get this table:

Animal Number Days Alive
Chicken (Meat) 28 42
Chicken (Egg) 2 365
Cow (Beef) 0.125 365
Cow (Milk) 0.033 1460
Fish 225 365

This makes the weighted average 329.6 days[5].

 

Accounting For Biases

As I said before, our formula was Years of Suffering Averted = (Pamphlets / dollar) * (Conversions / pamphlet) * (Veg years / conversion) * (Animals saved / veg year) * (Days lived / animal).

Let's plug these values in... Years of Suffering Averted per Dollar = 5 * 0.02 * 3 * 255.16 * 329.6/365 = 69.12.

Or, assuming all this is right (and that's a big assumption), it would cost less than 2 cents to prevent a year of suffering on a factory farm by buying vegetarians.

I don't want to make it sound like I'm beholden to this cost estimate or that this estimate is the "end all, be all" of vegan outreach.  Indeed, I share many of the skepticisms that have been expressed by others.  The simple calculation is... well... simple, and it needs some "beefing up", no pun intended.  Therefore, I also built a "complex calculator" that works on a much more complex formula[6] that is hopefully correct[7] and will provide a more accurate estimation.

 

The big, big deal for the surveys is concern for bias.  The most frequently mentioned bias is social desirability bias, or people who say they reduced meat just because they want to please the surveyor or look like a good person, which actually happens a lot more on surveys than we'd like.

To account for this, we'll have to figure out how inflated answers are because of this bias and then scale the answers down by that amount.  Nick Cooney who says that he's been reading studies that about 25% to 50% of people who say they are vegetarian actually are, though I don't yet have the citations.  Thus, if we find out that an advertisement creates two meat reducers, we'd scale that down to one reducer if we're expecting a 50% desirability bias.

 

The second bias that will be a problem for us is non-response bias, as those who don't reduce their diet are less likely to take the survey and therefore less likely to be counted.  This is especially true in the Facebook study, which only measures people who "liked" or requested a starter kit, showing some pro-vegetarian affiliation.

We can balance this out by assuming everyone who didn't take the survey went on to have no behavior change whatsoever.  Nick Cooney's Facebook Ad Survey is for the 7% of people who liked the page (and then responded to the survey), and obviously those who liked the page are more likely to reduce their consumption.  I chose an optimistic value of 90% to consider the survey completely representative of the 7% who liked the page, and then a bit more for those who reduced their consumption but did not like the page.  My pessimistic value was 95%, assuming everyone who did not like the survey went unchanged and assuming a small response bias among those who liked the page but chose not to take the survey.

For the pamphlets, however, there should be no response bias since the entire population of college students was surveyed from randomly, and no one was said to reject taking the survey.

 

Additional People Are Being Reached

In the Facebook survey, those who said they reduced their meat consumption were also asked if they influenced any of their friends and family to also reduce eating meat, and found that they usually produced 0.86 additional reducers.

This figure seems very high, but I do strongly expect the figure to be positive -- people who reduce eating meat will talk about it sometimes, essentially becoming free advertisements.  I'd be very surprised if they ended up being a net negative.

 

Accounting for Product Elasticity

Another way to boost the effectiveness of the estimate is to be more accurate about what happens when someone stops eating meat.  The change isn't from the actual refusal to eat, but rather from the reduced demand for meat, which leads to a reduced supply.  Following the laws of economics, however, this reduction won't necessarially be one-for-one, but rather depend on the elasticity of product demand and supply.  By getting this number, we can find out how much meat is reduced for every meat not demanded.

My guesses in the calculator come from the following sources, some of which are PDFs: Beef #1Beef #2Dairy #1Dairy #2Pork #1, Pork #2Egg #1, Egg #2PoultrySalmon, and for all fish.

 

Putting It All Together

Implementing the formula on the calculator, we end up with an estimate of $0.03 to $36.52 to reduce one year of suffering on a factory farm based on the Facebook ad data and an estimate of $0.02 to $65.92 based on the pamphlet data.

Of course, many people are skeptical of these figures.  Perhaps surprisingly, so am I.  I'm trying to strike a balance between being an advocate of vegan outreach as a very promising path for making the world a better place, while not losing sight of the methodological hurdles that have not yet been met, and open to the possibility that I'm wrong about this.

The big methodological elephant in the room is that my entire cost estimate depends on having a plausible guess for how likely someone is to change their behavior based on seeing an advertisement.

I feel slightly reassured because:

  1. There are two surveys for two different media, and they both provide estimates of impact that agree with each other.
  2. These estimates also match anecdotes from leafleters about approximately how many people come back and say they went vegetarian because of a pamphlet.
  3. Even if we were to take the simple calculator and drop the "2% chance of getting four years of vegetarianism" assumption down to, say, a pessimistic "0.1% chance of getting one year" conversion rate, the estimate is still not too bad -- $0.91 to avert a year of suffering.
  4. More studies are on the way.  Nick Cooney is going to do a bunch more to study leaflets, and Xio Kikauka and Joey Savoie have publicly published some survey methodology [Google Docs].

That said, the possibility for desirability bias in the survey is a large concern as long as the surveys continue to be from overt animal welfare groups and continue to clearly state that they're looking for reductions in meat consumption.

Also, so long as surveys are only given to people that remember the leaflet or advertisement, there will be a strong possibility of response bias, as those who remember the ad are more likely to be the ones who changed their behavior.  We can attempt to compensate for these things, but we can only do so much.

Furthermore, and more worrying, there's a concern that the surveys are just measuring normal drift in vegetarianism, without any changes being attributable to the ads themselves.  For example, imagine that every year, 2% of people become vegetarians and 2% quit.  Surveying these people at random and not capturing those who quit will end up finding a 2% conversion rate.

How can we address these?  I think all three problems can be solved with a decent control group, whether it be a group of people that receive a leaflet not about vegetarianism, or no leaflet at all.  Luckily, Kikauka and Savoie's survey intend to do just that.

Jeff Kaufman has a good proposal for a survey design I'd like to see implemented in this area.

 

Market Saturation and Diminishing Marginal Returns?

Another concern is that there are diminishing marginal returns to these ads.  As the critique goes, there are only so many people that will be easily swayed by the advertisement, and once all of them are quickly reached by Facebook ads and pamphlets, things will dry up.

Unlike the others, I don't think this criticism works well.  After all, even if it were true, it still would be worthwhile to take the market as far as it will go, and we can keep monitoring for saturation and find the point where it's no longer cost-effective.

However, I don't think the market has been tapped up yet at all.  According to Nick Cooney [PDF], there are still many opportunities in foreign markets and outside the young, college kid demographic.

 

The Conjunction Fallacy?

The conjunction fallacy is a classic fallacy that reminds us that no matter what, the chance of event A happening can never be smaller than the chance of event A happening, followed by event B.  For example, the probability that Linda is a bank teller will always be larger than (or equal to) the probability that Linda is a bank teller and a feminist.

What does this mean for vegetarian outreach?  Well, for the simple calculator, we're estimating five factors.  In the complex calculator, we're estimating 90 factors.  Even if each factor is 99% likely to be correct, the chance that all five are right is 95%, and the chance that all 50 are right is only 60%.  If each factor is only 90% likely to be correct, the complex calculator will be right with a probability of 0.5%!

This is a cause for concern, but I don't think there's any way around this.  It's just an inherent problem with estimation.  Hopefully we'll be balanced by (1) using the different bounds and (2) hoping underestimates and overestimates will cancel each other out.

 

Conversion and The 100 Yard Line

Something we should take into account that helps the case for this outreach rather than hurts it is the idea that conversions aren't binary -- someone can be pushed by the ad to be more likely to reduce their meat intake as opposed to fully converted.  As Brian Tomasik puts it:

Yes, some of the people we convince were already on the border, but there might be lots of other people who get pushed further along and don’t get all the way to vegism by our influence. If we picture the path to vegism as a 100-yard line, then maybe we push everyone along by 20 yards. 1/5 of people cross the line, and this is what we see, but the other 4/5 get pushed closer too. (Obviously an overly simplistic model, but it illustrates the idea.)

This would be either very difficult or outright impossible to capture in a survey, but is something to take into account.

 

Three Places I Might Donate Before Donating to Vegan Outreach

When all is said and done, I like the case for funding this outreach.  However, I think there are three other possibilities along these lines that I find more promising:

Funding the research of vegan outreach: There needs to be more and higher-quality studies of this before one can feel confident enough in the cost-effectiveness of this outreach.  However, initial results are very promising, and the value of information of more studies is therefore very high.  Studies can also find ways to advertise more effectively, increasing the impact of each dollar spent.  Right now, however, it looks like all ongoing studies are fully funded, but if there were opportunities to fund more, I would jump on it.

Funding Effective Animal Activism: EAA is an organization pushing for more cost-effectiveness in the domain of nonhuman animal welfare and is working to further evaluate what opportunities are the best, Givewell-style.  Giving them more money can potentially attract a lot more attention to this outreach, and get it more scrutiny, research, and money down the line.

Funding Centre for Effective Altruism: Overall, it might just be better to get more people involved in the idea of giving effectively, and then getting them interested in vegan outreach, among other things.

 

Conclusion

Vegan outreach is a promising, though not fully studied, method of outreach that deserves both excitement and skepticism.  Should one put money into it?  Overall, I'd take a guarded approach of putting in just enough money to help the organizations learn, develop better cost-effective measurements and transparency, and become more effective.  It shouldn't be too long before this area will become studied well enough to have good confidence in how things are doing.

More studies should be developed that explore advertising vegetarianism in a wide variety of media in a wide variety of ways, with decent control groups.

I look forward to seeing how this develops.  Don't forget to play around with my calculator.

-

 

Footnotes

[1]: Cost effectiveness in years of suffering prevented per dollar = (Pamphlets / dollar) * (Conversions / pamphlet) * (Veg years / conversion) * (Animals saved / veg year) * (Years lived / animal).

Plugging in 80K's values... Cost effectiveness = (Pamphlets / dollar) * 0.01 to 0.03 * 25 * 100 * (Years lived / animal)

Filling in the gaps with my best guesses... Cost effectiveness = 5 * 0.01 to 0.03 * 25 * 100 * 0.90 = 112.5 to 337.5 years of suffering averted per dollar
I personally think 25 veg-years per conversion on average is possible but too high; I personally err from 4 to 7.
[2]: I feel like there's an error in this calculation or that Kaufman might disagree with my assumptions of number of animals or days per animal, because I've been told before that these estimates with this method are supposed to be about an order of magnitude higher than other estimates.  However, I emailed Kaufman and he seemed to not find any fault with the calculation, though he does think the methodology is bad and the calculation should not be taken at face value.
[3]: I calculated the number of vegetarians by eyeballing about how many people said they no longer eat fish, which I'd guess only a vegetarian would be willing to give up.
[4]: 32 vegetarians / 104 people = 30.7%.  That population is 8.5% (7% for likes + 1.5% for the starter kit) of the overall population, leading to 2.61% (30.7% * 8.5%).
[5]: Formula is [(Number Meat Chickens)(Days Alive) + (Number Egg Chickens)(Days Alive) + (Number Beef Cows)(Days Alive) + (Number Milk Cows)(Days Alive) + (Number Fish)(Days Alive)] / (Total Number Animals).  ...Plugging things in: [(28)(42) + (2)(365) + (0.125)(365) + (0.033)(1460) + (225)(365)] / 255.16] = 329.6 days

[6]:
Cost effectiveness in amount of days prevented per dollar = (People Reached / Dollar + (People Reached / Dollar * Additional People Reached / Direct Reach * Response Bias * Desirability Bias)) * Years Spent Reducing * (((Percent Increasing Beef * Increase Value) + (Percent Staying Same with Beef * Staying Same Value) + (Percent Decreasing Beef Slightly * Decrease Slightly Value) + (Percent Decreasing Beef Significantly * Decrease Significantly Value) + (Percent Eliminating Beef * Elimination Value) + (Percent Never Ate Beef * Never Ate Value)) * Normal Beef Consumption * Beef Elasticity * (Average Beef Lifespan + Days of Suffering from Beef Slaughter)) + (((Percent Increasing Dairy * Increase Value) + (Percent Staying Same with Dairy * Staying Same Value) + (Percent Decreasing Dairy Slightly * Decrease Slightly Value) + (Percent Decreasing Dairy Significantly * Decrease Significantly Value) + (Percent Eliminating Dairy * Elimination Value) + (Percent Never Ate Dairy * Never Ate Value)) * Normal Dairy Consumption * Dairy Elasticity * (Average Dairy Lifespan + Days of Suffering from Dairy Slaughter)) + (((Percent Increasing Pig * Increase Value) + (Percent Staying Same with Pig * Staying Same Value) + (Percent Decreasing Pig Slightly * Decrease Slightly Value) + (Percent Decreasing Pig Significantly * Decrease Significantly Value) + (Percent Eliminating Pig * Elimination Value) + (Percent Never Ate Pig * Never Ate Value)) * Normal Pig Consumption * Pig Elasticity * (Average Pig Lifespan + Days of Suffering from Pig Slaughter)) + (((Percent Increasing Broiler Chicken * Increase Value) + (Percent Staying Same with Broiler Chicken * Staying Same Value) + (Percent Decreasing Broiler Chicken Slightly * Decrease Slightly Value) + (Percent Decreasing Broiler Chicken Significantly * Decrease Significantly Value) + (Percent Eliminating Broiler Chicken * Elimination Value) + (Percent Never Ate Broiler Chicken * Never Ate Value)) * Normal Broiler Chicken Consumption * Broiler Chicken Elasticity * (Average Broiler Chicken Lifespan + Days of Suffering from Broiler Chicken Slaughter)) + (((Percent Increasing Egg * Increase Value) + (Percent Staying Same with Egg * Staying Same Value) + (Percent Decreasing Egg Slightly * Decrease Slightly Value) + (Percent Decreasing Egg Significantly * Decrease Significantly Value) + (Percent Eliminating Egg * Elimination Value) + (Percent Never Ate Egg * Never Ate Value)) * Normal Egg Consumption * Egg Elasticity * (Average Egg Lifespan + Days of Suffering from Egg Slaughter)) + (((Percent Increasing Turkey * Increase Value) + (Percent Staying Same with Turkey * Staying Same Value) + (Percent Decreasing Turkey Slightly * Decrease Slightly Value) + (Percent Decreasing Turkey Significantly * Decrease Significantly Value) + (Percent Eliminating Turkey * Elimination Value) + (Percent Never Ate Turkey * Never Ate Value)) * Normal Turkey Consumption * Turkey Elasticity * (Average Turkey Lifespan + Days of Suffering from Turkey Slaughter)) + (((Percent Increasing Farmed Fish * Increase Value) + (Percent Staying Same with Farmed Fish * Staying Same Value) + (Percent Decreasing Farmed Fish Slightly * Decrease Slightly Value) + (Percent Decreasing Farmed Fish Significantly * Decrease Significantly Value) + (Percent Eliminating Farmed Fish * Elimination Value) + (Percent Never Ate Farmed Fish * Never Ate Value)) * Normal Farmed Fish Consumption * Farmed Fish Elasticity * (Average Farmed Fish Lifespan + Days of Suffering from Farmed Fish Slaughter)) + (((Percent Increasing Sea Fish * Increase Value) + (Percent Staying Same with Sea Fish * Staying Same Value) + (Percent Decreasing Sea Fish Slightly * Decrease Slightly Value) + (Percent Decreasing Sea Fish Significantly * Decrease Significantly Value) + (Percent Eliminating Sea Fish * Elimination Value) + (Percent Never Ate Sea Fish * Never Ate Value)) * Normal Sea Fish Consumption * Sea Fish Elasticity * Days of Suffering from Sea Fish Slaughter) * Response Bias * Desirability Bias
[7]: Feel free to check the formula for accuracy and also check to make sure the calculator implements the formula correctly.  I worry that the added accuracy from the complex calculator is outweighed by the risk that the formula is wrong.

-

Edited 18 June to correct two typos and update footnote #2.

Also cross-posted on my blog.

Useful Concepts Repository

32 Qiaochu_Yuan 10 June 2013 06:12AM

See also: Boring Advice Repository, Solved Problems Repository, Grad Student Advice Repository

I often find that my understanding of the world is strongly informed by a few key concepts. For example, I've repeatedly found the concept of opportunity cost to be a useful frame. My previous post on privileging the question is in some sense about the opportunity cost of paying attention to certain kinds of questions (namely that you don't get to use that attention on other kinds of questions). Efficient charity can also be thought of in terms of the opportunity cost of donating inefficiently to charity. I've also found the concept of incentive structure very useful for thinking about the behavior of groups of people in aggregate (see perverse incentive). 

I'd like people to use this thread to post examples of concepts they've found particularly useful for understanding the world. I'm personally more interested in concepts that don't come from the Sequences, but comments describing a concept from the Sequences and explaining why you've found it useful may help people new to the Sequences. ("Useful" should be interpreted broadly: a concept specific to a particular field might be useful more generally as a metaphor.) 

Privileging the Question

102 Qiaochu_Yuan 29 April 2013 06:30PM

Related to: Privileging the Hypothesis

Remember the exercises in critical reading you did in school, where you had to look at a piece of writing and step back and ask whether the author was telling the whole truth? If you really want to be a critical reader, it turns out you have to step back one step further, and ask not just whether the author is telling the truth, but why he's writing about this subject at all.

-- Paul Graham

There's an old saying in the public opinion business: we can't tell people what to think, but we can tell them what to think about.

-- Doug Henwood

Many philosophers—particularly amateur philosophers, and ancient philosophers—share a dangerous instinct: If you give them a question, they try to answer it.

-- Eliezer Yudkowsky

Here are some political questions that seem to commonly get discussed in US media: should gay marriage be legal? Should Congress pass stricter gun control laws? Should immigration policy be tightened or relaxed? 

These are all examples of what I'll call privileged questions (if there's an existing term for this, let me know): questions that someone has unjustifiably brought to your attention in the same way that a privileged hypothesis unjustifiably gets brought to your attention. The questions above are probably not the most important questions we could be answering right now, even in politics (I'd guess that the economy is more important). Outside of politics, many LWers probably think "what can we do about existential risks?" is one of the most important questions to answer, or possibly "how do we optimize charity?" 

Why has the media privileged these questions? I'd guess that the media is incentivized to ask whatever questions will get them the most views. That's a very different goal from asking the most important questions, and is one reason to stop paying attention to the media. 

The problem with privileged questions is that you only have so much attention to spare. Attention paid to a question that has been privileged funges against attention you could be paying to better questions. Even worse, it may not feel from the inside like anything is wrong: you can apply all of the epistemic rationality in the world to answering a question like "should Congress pass stricter gun control laws?" and never once ask yourself where that question came from and whether there are better questions you could be answering instead.

I suspect this is a problem in academia too. Richard Hamming once gave a talk in which he related the following story:

Over on the other side of the dining hall was a chemistry table. I had worked with one of the fellows, Dave McCall; furthermore he was courting our secretary at the time. I went over and said, "Do you mind if I join you?" They can't say no, so I started eating with them for a while. And I started asking, "What are the important problems of your field?" And after a week or so, "What important problems are you working on?" And after some more time I came in one day and said, "If what you are doing is not important, and if you don't think it is going to lead to something important, why are you at Bell Labs working on it?" I wasn't welcomed after that; I had to find somebody else to eat with!

Academics answer questions that have been privileged in various ways: perhaps the questions their advisor was interested in, or the questions they'll most easily be able to publish papers on. Neither of these are necessarily well-correlated with the most important questions. 

So far I've found one tool that helps combat the worst privileged questions, which is to ask the following counter-question:

What do I plan on doing with an answer to this question?

With the worst privileged questions I frequently find that the answer is "nothing," sometimes with the follow-up answer "signaling?" That's a bad sign. (Edit: but "nothing" is different from "I'm just curious," say in the context of an interesting mathematical or scientific question that isn't motivated by a practical concern. Intellectual curiosity can be a useful heuristic.)

(I've also found the above counter-question generally useful for dealing with questions. For example, it's one way to notice when a question should be dissolved, and asked of someone else it's one way to help both of you clarify what they actually want to know.)

Overcoming bias guy meme | quickmeme

4 saliency 13 March 2013 04:56PM

Rationality Habits I Learned at the CFAR Workshop

37 elharo 10 March 2013 02:15PM

Recently Leah Libresco asked attendees at the January CFAR Workshop, "What habits have people installed after workshops?" and that got me thinking that now was a good time to write up and review what I learned (or learned and already forgot). I thought that might be of some interest to folks here, and this is what follows.

What I Learned and Implemented

The most immediately useful thing I learned was the Pomodoro Technique, as I've written about here before. In addition to that, there were a number of small items that I'm continuing to work on.

First, I've become quite fond of the question "Does future me have a comparative advantage?" Especially for small items, if the answer is "No" (and it's no far more often than it's yes) then just do it right now. The more trivial the task, the more useful it is. For instance, today I asked myself that while standing in the bedroom wondering whether to take 30 seconds to move my ExOfficio Bugproof socks from the dresser to the correct box in the closet. (Answer from a few minutes ago:  if I don't take my dog for a walk right now, he's going to pee all over the floor. Future me does have a comparative advantage of not having to clean up pee on the floor. The socks can wait.)

I've begun to notice my confusion and call it to conscious attention more often, though I suspect I learned this first from HpMOR and the sequences before the workshop. Example: when Leonard Susskind states that conservation of information is a fundamental principle of quantum mechanics, I notice that I am confused because A) I have never heard of any such fundamental law of physics as information conservation B) Every definition of information I have ever heard indicates that information most certainly can be destroyed. So just what the heck is he talking about anyway? I am now making a conscious effort to research this topic rather than letting it slide by.

The workshop introduced me to the concepts of System 1 and System 2. System 1 is the faster, reactive, intuitive mind that uses heuristics and experience to react quickly. System 2 is the slower, analytical, logical, mathematical mind. I didn't immediately grok this or see how to apply it. However the workshop did convince me to read Daniel Kahneman's Thinking Fast and Slow, and I'm beginning to follow this. It could be useful going forward. I particularly like the examples given at the end of each chapter.

Similarly I completely did not understand the concepts of inside view vs. outside view at the workshop; and worse yet I don't think that I even realized that I didn't understand these. However now that I've read Thinking Fast and Slow, the lightbulb has gone on. Inside view is simply me deciding how likely I (or my team) is likely to accomplish something based on my judgement of the problem and our capabilities. Outside view is a statistical question about how people and teams like us have done when confronted with similar problems in the past. As long as there are similar teams and similar problems to compare with, the outside view is likely to be much more accurate.

During conversation, Julia Galef and I came up with the idea of *********.  It turned out it already exists, and I'm planning to start attending these events locally soon. I've also joined my local LessWrong meetup group.

Stare into Ugh fields. Difficult conversations are an Ugh field for me. Recognizing this and bringing it to conscious attention has made it somewhat easier to manage these conversations. Example: when I went to the workshop I had been putting off contacting my dentist for months, not because of the usual reasons people don't like going to the dentist, but simply because I was uncomfortable telling her that the second (and third) opinion I had gotten on a dental issue disagreed with her about the proper course of treatment. Post-workshop, I finally called her (though it still took me two more weeks to do this. Clearly I have a lot of work left to do here.)

Consider whether the sources of my information may be correlated and by how much. I.e. Evaluating Advice. For instance, if two dentists who share an office give me the same advice, even assuming no prior disposition to agree with each other simply out of friendship, how likely is it that they share the same background and information that dentists in a different office do not?

COZE (Comfort Zone Expansion) exercises have pushed me to talk more to "strangers" and be intentionally more extroverted. On a recent trip to Latin America, I even made an effort to use what little Spanish I possess. I've had some small success, though this has led to no obvious major improvements in my life yet.

Thought experiments conducted at the workshop were very helpful in untangling some of my goals and plans. Going forward though this hasn't made a huge difference in my day-to-day life. That is, it hasn't led me to seek different paths than what I'm on right now.

What I Learned and Forgot

Going over my notes now, there was a lot of material; some of it potentially useful, that has fallen by the wayside; and may be worth a second look. This includes:

  • Geoff Anders introduced us to yEd, a nice open source diagram editor. I still prefer StencilIt or Omnigraffle though. He also used it to show us a really neat way of graphing, well, something. Goals maybe? I remember it seemed really useful and significant at the time, but for the life of me I can't remember exactly what it was or what it was supposed to show us. I'll have to go back to my notes. This is why we write things down. (Update: I suspect this was about Goal Factoring.)
  • Anticipation vs. Profession (though from time to time I do find myself asking what odds I'd be willing to bet on certain beliefs)
  • The Planning Kata.

What I Learned But Didn't Implement

Value of Information calculations seem too meta and too wishy-washy to be of much use. They attempt to put quantitative numbers based on information that's far too imprecise to allow even order of magnitude accuracy. I'm better off just keeping things I need to consider in my GTD system, and periodically reviewing it.

Similarly opportunities for Bayesian Strength of Evidence calculations, just don't seem to come up in my day-to-day life. The question for me is more commonly "Given that the situation is what it is, what actions should I take to accomplish my goals?" The outside view is useful for this. Figuring out why the situation is what it is rarely seems to be especially helpful.

Turbocharging Training may be helpful but the evidence seems to me to be lacking. I'd like to see some strong proof that this works in particular areas; e.g. foreign languages, sports, or mathematics.  Furthermore, it's not clear that it's applicable to anything I'm working on learning at this time. It seems very System 1 focused, and not especially helpful with the sort of fundamentally System 2 tasks I take on.

I have begun to declare "Victory!" at the end of a meeting/discussion. it's a bit of fun, but has limited effect. Beyond that I don't seem to reward myself for noticing things, or as a means of installing habits.

What I Didn't Learn

Getting Things Done (GTD), Remember the Milk, BeeMinder, Anki, Cultivating Curiosity, Overcoming Procrastination, and Winning at Arguments.

GTD I didn't learn because I've used it for years now or at least the parts of it that really work for me (lists and calendars mostly, and to a lesser extent filing).

Remember the Milk because my employer's security policy prohibits us from using it, and too much of my life happens at my day job to make maintaining two separate systems worthwhile.

BeeMinder and Anki because I just don't have anything that seems it could benefit from being stored in those systems right now. All of these might be more beneficial to someone in different circumstances.

Cultivating Curiosity because I am already a very naturally curious person, and have been for as long as I can remember. I don't need help with this. Indeed if anything I need to tamp down on this tendency and focus more on accomplishing things rather than merely learning them.

Similarly, Overcoming Procrastination didn't help a lot because I don't have a big procrastination problem, at least not compared to what I had when I was younger. Of course, I do say that in full knowledge that right this minute writing this article is a form of structured procrastination to avoid doing my taxes. :-)

Winning at Arguments, I am already very, very good at when I want to be, which is rare these days. It took me many years too realize that even though I "won" almost every argument I cared about, winning the argument wasn't usually all that useful. Winning an argument is the wrong goal to have for almost any purpose, and rarely leads to the outcomes I desire.

Unofficial ideas from fellow attendees:

Polyphasic sleep: I'm going to let the younger, more pioneering attendees experiment with this one. Even if it does work (which seems far from obvious) I don't see how one could integrate it into a conventional day job and family.

At breakfast one morning, a fellow attendee (Hunter?) suggested putting unsalted butter in my coffee to add more fat to my diet. It's not as crazy as it sounds. After all butter is little more than clarified cream, which I do like in my coffee. I tried this once and I still prefer cream, but I may give it another shot.

Finally, I've referred two workshop attendees to my employer as potential hires. If anyone else from the workshop is looking for a job, especially in tech, sales, or legal, drop me a line privately. For that matter if any Less Wronger is looking for a job, drop me a line privately. We have hundreds of open positions in major cities around the world. Quite a few LessWrongers already work there, and there's room for many more.

What the workshop didn't teach

There were a few techniques that were conspicuous by their absence. In particular I think the CFAR/LessWrong and Agile/XP communities have a lot to teach each other. I was surprised that no one at the workshop seemed to have heard of Kanban or Scrum, much less practice it. Burndown charts and point-based estimation are a really interesting modification of the outside view by comparing your team to your team in the past, rather than to other teams.

Pairing is also a useful technique beyond programming as at least Eliezer (not present at the workshop) has discovered. Pairing is an incredibly effective way to overcome akrasia and procrastination.

In reverse, I am considering what the craft of software development has to learn from CFAR style rationality, more specifically epistemic rationality. I have begun to notice my confusion during conversations with users, product managers, and tech leads and call it to conscious attention. I less frequently let unclear specs and goals pass without comment. Rather, I ask for examples and drill down into them until I feel my confusion has been conquered.

So far these techniques seem very useful in analysis and requirements gathering. I've found them less obviously useful (though certainly not harmful in any way) during coding, debugging, and testing. In these stages there's simply too much to be confused by to address it all, and whatever I'm confused by that's relevant to the task at hand rapidly calls itself to my attention. For instance, when a bug shows up in a production system, the very first and natural question to ask  is "How the hell did the system do that?!" On the other hand, the planning kata may be very helpful with the early stages of system design, though I haven't yet had an opportunity to try that out.

Was it Worth $3900?

Overall, I found the workshop to be a worthwhile experience, if an expensive one; and I recommend it to you if you have the opportunity and resources to attend. There are a lot of practical techniques to be learned, and you only need one or two of them to pay off to cover the cost and time. Even if the primary value is simply introducing you to books and techniques you explore further after the workshop such as Getting Things Done or Thinking Fast and Slow, that may be enough. Most knowledge workers are operating far below the level of which we're capable, and expanding our effectiveness can pay for itself.

Before attending, it is worth asking yourself whether there's an opportunity to learn this material at lower cost. For instance, did I really need to spend $3900 and 4 days to learn about Pomodoro? Apparently so, since I'd heard about Pomodoro for years and paid no attention to it until January. On the other hand, a $20 book I read on the subway was fully sufficient for me to learn and implement Getting Things Done. You'll have to judge this one for yourself.

MetaMed: Evidence-Based Healthcare

83 Eliezer_Yudkowsky 05 March 2013 01:16PM

In a world where 85% of doctors can't solve simple Bayesian word problems...

In a world where only 20.9% of reported results that a pharmaceutical company tries to investigate for development purposes, fully replicate...

In a world where "p-values" are anything the author wants them to be...

...and where there are all sorts of amazing technologies and techniques which nobody at your hospital has ever heard of...

...there's also MetaMed.  Instead of just having “evidence-based medicine” in journals that doctors don't actually read, MetaMed will provide you with actual evidence-based healthcare.  Their Chairman and CTO is Jaan Tallinn (cofounder of Skype, major funder of xrisk-related endeavors), one of their major VCs is Peter Thiel (major funder of MIRI), their management includes some names LWers will find familiar, and their researchers know math and stats and in many cases have also read LessWrong.  If you have a sufficiently serious problem and can afford their service, MetaMed will (a) put someone on reading the relevant research literature who understands real statistics and can tell whether the paper is trustworthy; and (b) refer you to a cooperative doctor in their network who can carry out the therapies they find.

MetaMed was partially inspired by the case of a woman who had her fingertip chopped off, was told by the hospital that she was screwed, and then read through an awful lot of literature on her own until she found someone working on an advanced regenerative therapy that let her actually grow the fingertip back.  The idea behind MetaMed isn't just that they will scour the literature to find how the best experimentally supported treatment differs from the average wisdom - people who regularly read LW will be aware that this is often a pretty large divergence - but that they will also look for this sort of very recent technology that most hospitals won't have heard about.

This is a new service and it has to interact with the existing medical system, so they are currently expensive, starting at $5,000 for a research report.  (Keeping in mind that a basic report involves a lot of work by people who must be good at math.)  If you have a sick friend who can afford it - especially if the regular system is failing them, and they want (or you want) their next step to be more science instead of "alternative medicine" or whatever - please do refer them to MetaMed immediately.  We can’t all have nice things like this someday unless somebody pays for it while it’s still new and expensive.  And the regular healthcare system really is bad enough at science (especially in the US, but science is difficult everywhere) that there's no point in condemning anyone to it when they can afford better.


I also got my hands on a copy of MetaMed's standard list of citations that they use to support points to reporters.  What follows isn't nearly everything on MetaMed's list, just the items I found most interesting.

continue reading »

Decision Theory FAQ

52 lukeprog 28 February 2013 02:15PM

Co-authored with crazy88. Please let us know when you find mistakes, and we'll fix them. Last updated 03-27-2013.

Contents:


1. What is decision theory?

Decision theory, also known as rational choice theory, concerns the study of preferences, uncertainties, and other issues related to making "optimal" or "rational" choices. It has been discussed by economists, psychologists, philosophers, mathematicians, statisticians, and computer scientists.

We can divide decision theory into three parts (Grant & Zandt 2009; Baron 2008). Normative decision theory studies what an ideal agent (a perfectly rational agent, with infinite computing power, etc.) would choose. Descriptive decision theory studies how non-ideal agents (e.g. humans) actually choose. Prescriptive decision theory studies how non-ideal agents can improve their decision-making (relative to the normative model) despite their imperfections.

For example, one's normative model might be expected utility theory, which says that a rational agent chooses the action with the highest expected utility. Replicated results in psychology describe humans repeatedly failing to maximize expected utility in particular, predictable ways: for example, they make some choices based not on potential future benefits but on irrelevant past efforts (the "sunk cost fallacy"). To help people avoid this error, some theorists prescribe some basic training in microeconomics, which has been shown to reduce the likelihood that humans will commit the sunk costs fallacy (Larrick et al. 1990). Thus, through a coordination of normative, descriptive, and prescriptive research we can help agents to succeed in life by acting more in accordance with the normative model than they otherwise would.

This FAQ focuses on normative decision theory. Good sources on descriptive and prescriptive decision theory include Stanovich (2010) and Hastie & Dawes (2009).

Two related fields beyond the scope of this FAQ are game theory and social choice theory. Game theory is the study of conflict and cooperation among multiple decision makers, and is thus sometimes called "interactive decision theory." Social choice theory is the study of making a collective decision by combining the preferences of multiple decision makers in various ways.

This FAQ draws heavily from two textbooks on decision theory: Resnik (1987) and Peterson (2009). It also draws from more recent results in decision theory, published in journals such as Synthese and Theory and Decision.

continue reading »

Learning critical thinking: a personal example

37 Swimmer963 14 February 2013 08:43PM

Related to: Is Rationality Teachable

“Critical care nursing isn’t about having critically ill patients,” my preceptor likes to say, “it’s about critical thinking.”

I doubt she's talking about the same kind of critical thinking that philosophers are, and I find that definition abstract anyway. There’s been a lot of talk about critical thinking during our four years of nursing school, but our profs seem to have a hard time defining it. So I’ll go with a definition from Google.

Critical thinking can be seen as having two components: 1) a set of information and belief generating and processing skills, and 2) the habit, based on intellectual commitment, of using those skills to guide behaviour. It is thus to be contrasted with: 1) the mere acquisition and retention of information alone, because it involves a particular way in which information is sought and treated; 2) the mere possession of a set of skills, because it involves the continual use of them; and 3) the mere use of those skills ("as an exercise") without acceptance of their results.1

That’s basically rationality–epistemic, i.e. generating true beliefs, and instrumental, i.e. knowing how to use them to achieve what you want. Maybe part of me expected, implicitly, to have an easier time learning this skill because of my Less Wrong knowledge. And maybe I am more consciously aware of my mistakes, and the cognitive factors that caused them, than most of my classmates. When it’s forty-five minutes past the end of my shift and I’m still charting, I’m also calling myself out on succumbing to the planning fallacy. I once went through the first half hour of a shift during my pediatrics rotation thinking that one of my patients had cerebral palsy, when he actually had cystic fibrosis–all because I misread my prof’s handwriting as ‘CP’ when she’d written ‘CF’. I was totally confused by all the enzyme supplements on his list of meds, but it still took me a while to figure it out–a combination of priming and confirmation bias, taken to the next level. 

But, overall, even if I know what I'm doing wrong, it hasn’t been easier to do things right. I have a hard time with the hospital environment, possibly because I’m the kind of person who ended up reading and posting on Less Wrong. My cognitive style leans towards Type 2 reasoning, in Keith Stanovich’s taxonomy–thorough, but slow. I like to understand things, on a deep level. I like knowing why I’m doing something, and I don’t trust my intuitions, the fast-and-dirty product of Type 1 reasoning. But Type 2 reasoning requires a lot of working memory, and humans aren’t known for that, which is the source of most of my frustration and nearly all of my errors–when working memory overload forces me to be a cognitive miser.

Still, for all the frustration, I’m pretty sure I’ve ended up in the perfect environment to learn this skill called ‘critical thinking.’ I’m way out of my depth–which I expected. No fourth year student is ready to work independently in a trauma ICU, but I decided to finish my schooling here in the name of tsuyoku naritai, and for all the days when I’ve gone home crying, it’s still worth it. I’m learning.

 

The skills

 1.     A set of information and belief generating and processing skills.

Medicine, and nursing, are a bit like physics, in that you need to generate true beliefs about systems that exist outside of you, and predict how they’re going to behave. This involves knowing a lot of abstract theory, which I’m good at, and a lot of heuristics and pattern-matching for applying the right bits of theory to particular patients, which I’m less good at. That’s partly an experience thing; my brain needs patterns to match to. But in general, I have decent mental models of my patients. I’m curious and I like to understand things. If I don’t know what part of the theories applies, I ask.

2.     The habit, based on intellectual commitment, of using those skills to guide behaviour.

So you’ve got your mental model of your patient, your best understand of what’s actually going on, on a physiological and biochemical level, down under the skin where you can’t see it. You know what “normal” is for a variety of measures: vital signs, lung sounds, lab values, etc. Given that your patient is in the ICU, you know something’s abnormal, or they wouldn’t be there. Their diagnosis tells you what to expect, and you look at the results of your assessments and ask a couple of questions. One: is this what I expect, for this patient? Two: what do I need to do about it?

I’m not going to be surprised if a post-op patient has low hemoglobin. It’s information of a kind, telling the doctor whether or not the patient needs a transfusion, and how many units, but it’s not really new information, and a moderately abnormal value wouldn’t worry me or anyone else. If their hemoglobin keeps dropping; okay, they’re actively bleeding somewhere, that’s irritating, and possibly dangerous, and needs dealing with, but it’s not surprising.

But if a patient here for an abdominal surgery suddenly has decreased level of consciousness and their pupils aren’t reacting normally to light, I’m worried. There’s nothing in my mental model that says I should expect it. I notice I’m confused, and that confusion guides my behaviour; I call the doctor right away, because we need more information to update our collective mental model, information you can’t get just from observation, like a CT scan of the head. (Even this is optimistic–plenty of patients are admitted to the ICU because we have no idea what’s wrong with them, and are hoping to keep them alive long enough to find out.)

The basics of ICU nursing come down to treating numbers. Heart rate, blood pressure, oxygen saturations, urine output, etc; know the acceptable range, notice if they change, and use Treatment X to get them back where they’re supposed to be. Which doesn’t sound that hard. But implicit in ‘notice if they change’ is ‘figure out why they changed’, because that affects how you treat them, and implicit in that is a lot of background knowledge, which has to be put in context.

I’m, honestly, fairly terrible at this. It’s a compartmentalization thing. I don’t like using my knowledge as input arguments to generate new conclusions and then relying on those conclusions to treat human beings. It feels like guessing. Even though, back in high school, I never really needed to study for physics tests–if I understood what we’d learned, I could re-derive forgotten details from first principles. But hospital patients ended up in a non-overlapping magisterium in my head. In order for me to trust my knowledge, it has to have come directly from the lips of a teacher or experienced nurse.

My preceptor, who  hates this.  “She needs to continue to work on her critical thinking when it comes to caring for critically ill patients,” she wrote on my evaluation. “She knows the theory, and is now working to apply it to ICU nursing.” Shorthand for, she knows the theory, but getting her to apply it to ICU nursing is like pulling teethA number of our conversations have gone like this:

Me: “Our patient’s blood pressure dropped a bit.”

Her: “Yeah, it did. What do you want to do about it?”

Me: “I, uh, I don’t know... Should I increase the vasopressors?”

Her: “I don’t know, should you?”

Me: “Uh, maybe I should increase the phenylephrine to 40 mcg/min and see what happens. How long should I wait to see?”

Her: “You tell me.”

Me: “Well, let’s say it’ll take a few minutes for what’s in the tubing now to get pushed through, and it should take effect pretty quickly because it’s IV, like a minute... So if his blood pressure’s not up enough in five minutes, I’ll increase the phenyl to 60. Does that sound okay?”

Her: “It’s your decision to make." 

Needless to say, I find this teaching method extremely stressful and scary, and I’m learning about ten times more than I would if she answered the questions I asked. Because “the mere acquisition and retention of information alone” isn’t my problem. I have a brain like an encyclopaedia. My problem, in the critical care nursing context, is the “particular way in which information is sought and treated.” I need to know the right time to notice something is wrong, the right place to look in my encyclopaedia, and the right way to take the information I just looked up and figure out what to do with it.

 

The mistakes

Some of my errors, unsurprisingly, boil down to a failure to override inappropriate Type 1 responses with Type 2 responses–in other words, not thinking about what I’m doing. But most of them are more of a mindware gap–I don’t yet have the “domain-specific knowledge sets” that the nurses around me have. Not just theory knowledge; I do have most of that; but the procedural habits of how to stay organized and prioritize and dump the contents of my working memory onto paper in a way that I can read them back later. Usually, when I make a mistake, I knew better, but the part of my brain that knew better was doing something else at the time, that small note of confusion getting lost in the general chaos. 

Pretty much all nurses keep a “feuille de route”–I have yet to find a satisfactory English word for this, but it’s a personal sheet of paper, not legal charting, usually kept in a pocket, and used as an extended working memory. In med/surg, when I had four patients, I made a chart with four columns; name and personal information, medications, treatments/general plan for the day, and medical history; and as many rows as I had patients. If something was important, I circled it in red ink. This system doesn’t work in the ICU, so my current feuille de route has several aspects. I fold a piece of blank paper into four, and take notes from the previous shift report on one quarter of one side, or two quarters if it’s a long report. Across from that, I draw a vertical column of times, from 8:00 am to 6:00 pm (or 8:00 pm to 6:00 am). 7:00 pm and 7:00 am are shift change, so nothing else really gets done for that hour. I use this to scribble down what I need to get down during my twelve hours, and approximately when I want to do it, and I prioritize, i.e. from 1 to 5 most to least important. Once it’s done, I cross it off–then I can forget about it. On the other side of the paper, I make a cheat sheet for giving report to the next nurse, or presenting my patient to the doctors at rounds.  

This might be low-tech and simple, but it takes a huge load off my working memory, and reduces my most frequent error, which is to get so overwhelmed and frazzled that my brain goes on strike. In other words, the failure to override Type 1 responses due to the lack of cognitive capacity to run a Type 2 process. It’s drastically cut down on the frequency of this mental conversation:

Me: “I turned off the sedation, and my patient isn’t waking up as fast as I expected. I notice I’m confused–”

My brain: “You’re always confused! Everything around here is intensely confusing! How am I supposed to use that as information?” 

Odd as it might sound, I often don’t notice when my brain starts edging towards a meltdown. The feeling itself is quite recognizable, but the circumstances that lead to it, i.e. overloaded working memory, mean that I’m not usually paying attention to my own feelings.

“You need to stop and take a breath,” my preceptor says about fifty times a day. Easier said than done–but it’s more efficient, overall, to have a tiny part of my mind permanently on standby, keeping an eye on my emotions, noticing when the gears start to overheat. Then stop, take a breath, and let go of everything except the task at hand, trusting myself to have created enough cues in my environment to retrieve the other tasks, once I’m done. Humans don’t multitask well. Doing one thing while trying to remember a list of five others is intense multitasking, and it’s no wonder it’s exhausting.

 

The implications

“You can’t teach critical thinking,” my preceptor says, but I’m pretty sure that’s exactly what she’s doing right now. A great deal of what I already know is domain-specific to nursing, but most of what I’m learning right now is generally applicable. I’m learning the procedural skills to work through difficult problems, under what Keith Stanovich would call average rather than optimal conditions. Sitting in my own little bubble in front of a multiple choice exam–that’s optimal conditions. Trying to figure out if I should be surprised or worried about my patient’s increased heart rate, while simultaneously deciding whether or not I can ignore the ventilator alarm and whether I can finish giving my twelve o’clock antibiotic before I need to do twelve o’clock vitals–that’s not just average conditions, it’s under-duress conditions.

I’m hoping that after a few more weeks, or maybe a few more years, I’ll be able to perform comfortably in this intensely terrifying environment. And I’m hoping that some of the skills I learn will be general-purpose, for me at least. It’d be nice if they were teachable to others, too, but I think my preceptor might be right about one thing–you can’t teach this kind of critical thinking in the classroom. It's about moulding my brain into the right shape, and everyone's brain starts out in a different shape, so the mould has to be personalized. 

But the habits are general ones. Notice when you're faced with a difficult problem, or making an important decision. Notice that you're doing this while distracted. Stop and take a breath. Get out a piece of paper. Figure out how the problem is formatted in your mind, and format it that way on the paper. (This is probably the hardest part). Dump your working memory and give yourself space to think. Prioritize from 1 to n. Keep an eye on the evolving situation, sure, but find that moment of concentration in the midst of chaos, and solve the problem. 

Of course, it's far from guaranteed that this will work. I'm making an empirical prediction; that the skills I'm currently learning will be transferable to non-nursing areas, and that they'll make a difference in my life outside of work. I'll be on the lookout for examples, either of success or failure.

 

References

Scriven, Michael; Paul, Richard. Defining critical thinking. (2011). The critical thinking community. http://www.criticalthinking.org/pages/defining-critical-thinking/410

 

Pinpointing Utility

57 [deleted] 01 February 2013 03:58AM

Following Morality is Awesome. Related: Logical Pinpointing, VNM.

The eternal question, with a quantitative edge: A wizard has turned you into a whale, how awesome is this?

"10.3 Awesomes"

Meditate on this: What does that mean? Does that mean it's desirable? What does that tell us about how awesome it is to be turned into a whale? Explain. Take a crack at it for real. What does it mean for something to be labeled as a certain amount of "awesome" or "good" or "utility"?

What is This Utility Stuff?

Most of agree that the VNM axioms are reasonable, and that they imply that we should be maximizing this stuff called "expected utility". We know that expectation is just a weighted average, but what's this "utility" stuff?

Well, to start with, it's a logical concept, which means we need to pin it down with the axioms that define it. For the moment, I'm going to conflate utility and expected utility for simplicity's sake. Bear with me. Here are the conditions that are necessary and sufficient to be talking about utility:

  1. Utility can be represented as a single real number.
  2. Each outcome has a utility.
  3. The utility of a probability distribution over outcomes is the expected utility.
  4. The action that results in the highest utility is preferred.
  5. No other operations are defined.

I hope that wasn't too esoteric. The rest of this post will be explaining the implications of those statements. Let's see how they apply to the awesomeness of being turned into a whale:

  1. "10.3 Awesomes" is a real number.
  2. We are talking about the outcome where "A wizard has turned you into a whale".
  3. There are no other outcomes to aggregate with, but that's OK.
  4. There are no actions under consideration, but that's OK.
  5. Oh. Not even taking the value?

Note 5 especially. You can probably look at the number without causing trouble, but if you try to treat it as meaningful for something other than condition 3 and 4, even accidentally, that's a type error.

Unfortunately, you do not have a finicky compiler that will halt and warn you if you break the rules. Instead, your error will be silently ignored, and you will go on, blissfully unaware that the invariants in your decision system no longer pinpoint VNM utility. (Uh oh.)

Unshielded Utilities, and Cautions for Utility-Users

Let's imagine that utilities are radioactive; If we are careful with out containment procedures, we can safely combine and compare them, but if we interact with an unshielded utility, it's over, we've committed a type error.

To even get a utility to manifest itself in this plane, we have to do a little ritual. We have to take the ratio between two utility differences. For example, if we want to get a number for the utility of being turned into a whale for a day, we might take the difference between that scenario and what we would otherwise expect to do, and then take the ratio between that difference and the difference between a normal day and a day where we also get a tasty sandwich. (Make sure you take the absolute value of your unit, or you will reverse your utility function, which is a bad idea.)

So the form that the utility of being a whale manifests as might be "500 tasty sandwiches better than a normal day". We have chosen "a normal day" for our datum, and "tasty sandwiches" for our units. Of course we could have just as easily chosen something else, like "being turned into a whale" as our datum, and "orgasms" for our units. Then it would be "0 orgasms better than being turned into a whale", and a normal day would be "-400 orgasms from the whale-day".

You say: "But you shouldn't define your utility like that, because then you are experiencing huge disutility in the normal case."

Wrong, and radiation poisoning, and type error. You tried to "experience" a utility, which is not in the defined operations. Also, you looked directly at the value of an unshielded utility (also known as numerology).

We summoned the utilities into the real numbers, but they are still utilities, and we still can only compare and aggregate them. The summoning only gives us a number that we can numerically do those operations on, which is why we did it. This is the same situation as time, position, velocity, etc, where we have to select units and datums to get actual quantities that mathematically behave like their ideal counterparts.

Sometimes people refer to this relativity of utilities as "positive affine structure" or "invariant up to a scale and shift", which confuses me by making me think of an equivalence class of utility functions with numbers coming out, which don't agree on the actual numbers, but can be made to agree with a linear transform, rather than making me think of a utility function as a space I can measure distances in. I'm an engineer, not a mathematician, so I find it much more intuitive and less confusing to think of it in terms of units and datums, even though it's basically the same thing. This way, the utility function can scale and shift all it wants, and my numbers will always be the same. Equivalently, all agents that share my preferences will always agree that a day as a whale is "400 orgasms better than a normal day", even if they use another basis themselves.

So what does it mean that being a whale for a day is 400 orgasms better than a normal day? Does it mean I would prefer 400 orgasms to a day as a whale? Nope. Orgasms don't add up like that; I'd probably be quite tired of it by 15. (remember that "orgasms" were defined as the difference between a day without an orgasm and a day with one, not as the utility of a marginal orgasm in general.) What it means is that I'd be indifferent between a normal day with a 1/400 chance of being a whale, and a normal day with guaranteed extra orgasm.

That is, utilities are fundamentally about how your preferences react to uncertainty. For example, You don't have to think that each marginal year of life is as valuable as the last, if you don't think you should take a gamble that will double your remaining lifespan with 60% certainty and kill you otherwise. After all, all that such a utility assignment even means is that you would take such a gamble. In the words of VNM:

We have practically defined numerical utility as being that thing for which the calculus of mathematical expectations is legitimate.

But suppose there are very good arguments that have nothing to do with uncertainty for why you should value each marginal life-year as much as the last. What then?

Well, "what then" is that we spend a few weeks in the hospital dying of radiation poisoning, because we tried to interact with an unshielded utility again (utilities are radioactive, remember? The specific error is that we tried to manipulate the utility function with something other than comparison and aggregation. Touching a utility directly is just as much an error as observing it directly.

But if the only way to define your utility function is with thought experiments about what gambles you would take, and the only use for it is deciding what gambles you would take, then isn't it doing no work as a concept?

The answer is no, but this is a good question because it gets us closer to what exactly this utility function stuff is about. The utility of utility is that defining how you would behave in one gamble puts a constraint on how you would behave in some other related gambles. As with all math, we put in some known facts, and then use the rules to derive some interesting but unknown facts.

For example, if we have decided that we would be indifferent between a tasty sandwich and a 1/500 chance of being a whale for tomorrow, and that we'd be indifferent between a tasty sandwich and a 30% chance of sun instead of the usual rain, then we should also be indifferent between a certain sunny day and a 1/150 chance of being a whale.

Monolithicness and Marginal (In)Dependence

If you are really paying attention, you may be a bit confused, because it seems to you that money or time or some other consumable resource can force you to assign utilities even if there is no uncertainty in the system. That issue is complex enough to deserve its own post, so I'd like to delay it for now.

Part of the solution is that as we defined them, utilities are monolithic. This is the implication of "each outcome has a utility". What this means is that you can't add and recombine utilities by decomposing and recombining outcomes. Being specific, you can't take a marginal whale from one outcome and staple it onto another outcome, and expect the marginal utilities to be the same. For example, maybe the other outcome has no oceans for your marginal whale.

For a bigger example, what we have said so far about the relative value of sandwiches and sunny days and whale-days does not necessarily imply that we are indifferent between a 1/250 chance of being a whale and any of the following:

  • A day with two tasty sandwiches. (Remember that a tasty sandwich was defined as a specific difference, not a marginal sandwich in general, which has no reason to have a consistent marginal value.)

  • A day with a 30% chance of sun and a certain tasty sandwich. (Maybe the tasty sandwich and the sun at the same time is horrifying for some reason. Maybe someone drilled into you as a child that "bread in the sun" was bad bad bad.)

  • etc. You get the idea. Utilities are monolithic and fundamentally associated with particular outcomes, not marginal outcome-pieces.

However, as in probability theory, where each possible outcome technically has its very own probability, in practice it is useful to talk about a concept of independence.

So for example, even though the axioms don't guarantee in general that it will ever be the case, it may work out in practice that given some conditions, like there being nothing special about bread in the sun, and my happiness not being near saturation, the utility of a marginal tasty sandwich is independent of a marginal sunny day, meaning that sun+sandwich is as much better than just sun as just a sandwich is better than baseline, ultimately meaning that I am indifferent between {50%: sunny+sandwich; 50% baseline} and {50%: sunny; 50%: sandwich}, and other such bets. (We need a better solution for rendering probability distributions in prose).

Notice that the independence of marginal utilities can depend on conditions and that independence is with respect to some other variable, not a general property. The utility of a marginal tasty sandwich is not independent of whether I am hungry, for example.

There is a lot more to this independence thing (and linearity, and risk aversion, and so on), so it deserves its own post. For now, the point is that the monolithicness thing is fundamental, but in practice we can sometimes look inside the black box and talk about independent marginal utilities.

Dimensionless Utility

I liked this quote from the comments of Morality is Awesome:

Morality needs a concept of awfulness as well as awesomeness. In the depths of hell, good things are not an option and therefore not a consideration, but there are still choices to be made.

Let's develop that second sentence a bit more. If all your options suck, what do you do? You still have to choose. So let's imagine we are in the depths of hell and see what our theories have to say about it:

Day 78045. Satan has presented me with three options:

  1. Go on a date with Satan Himself. This will involve romantically torturing souls together, subtly steering mortals towards self-destruction, watching people get thrown into the lake of fire, and some very unsafe, very nonconsensual sex with the Adversary himself.

  2. Paperclip the universe.

  3. Satan's court wizard will turn me into a whale and release me into the lake of fire, to roast slowly for the next month, kept alive by twisted black magic.

Wat do?

They all seem pretty bad, but "pretty bad" is not a utility. We could quantify paperclipping as a couple hundred billion lives lost. Being a whale in the lake of fire would be awful, but a bounded sort of awful. A month of endless horrible torture. The "date" is having to be on the giving end of what would more or less happen anyway, and then getting savaged by Satan. Still none of these are utilities.

Coming up with actual utility numbers for these in terms of tasty sandwiches and normal days is hard; it would be like measuring the microkelvin temperatures of your physics experiment with a Fahrenheit kitchen thermometer; in principle it might work, but it isn't the best tool for the job. Instead, we'll use a different scheme this time.

Engineers (and physicists?) sometimes transform problems into a dimensionless form that removes all redundant information from the problem. For example, for a heat conduction problem, we might define an isomorphic dimensionless temperature so that real temperatures between 78 and 305 C become dimensionless temperatures between 0 and 1. Transforming a problem into dimensionless form is nearly always helpful, often in really surprising ways. We can do this with utility too.

Back to depths of hell. The date with Satan is clearly the best option, so it gets dimensionless utility 1. The paperclipper gets 0. On that scale, I'd say roasting in the lake of fire is like 0.999 or so, but that might just be scope insensitivity. We'll take it for now.

The advantages with this approach are:

  1. The numbers are more intuitive. -5e12 QALYs, -1 QALY, and -50 QALYs from a normal day, or the equivalent in tasty sandwiches, just doesn't have the same feeling of clarity as 0, 1 and .999. (For me at least. And yes I know those numbers don't quite match.)

  2. Not having to relate the problem quantities to far-away datums or drastically misappropriate units (tasty sandwiches for this problem) makes the numbers easier and more direct to come up with. Also we have to come up with less of them. The problem is self-contained.

  3. If defined right, the connection between probability and utility becomes extra-clear. For example: What chance between a Satan-date and a paperclipper would make me indifferent with a lake-of-fire-whale-month? 0.999! Unitless magic!

  4. All confusing redundant information (like negative signs) are removed, which makes it harder to accidentally do numerology or commit a type error.

  5. All redundant information is removed, which means you find many more similarities between problems. The value of this in general cannot be understated. Just look at the generalizations made about Reynolds number! "[vortex shedding] occurs for any fluid, size, and speed, provided that Re between ~40 and 10^3". What! You can just say that in general? Magic! I haven't actually done enough utility problems to know that we'll find stuff like that but I trust dimensionless form.

Anyways, it seems that going on that date is what I ought to do. So did we need a concept of awfulness? Did it matter that all the options sucked? Nope; the decision was isomorphic in every way to choosing lunch between a BLT, a turkey club, and a handful of dirt.

There are some assumptions in that lunch bit, and it's worth discussing. It seems counterintuitive or even wrong, to say that your decision-process faced with lunch should be the same as when faced with a decision in involving torture, rape, and paperclips. The latter seems somehow more important. Where does that come from? Is it right?

This may deserve a bigger discussion, but basically, if you have finite resources (thought-power, money, energy, stress) that are conserved or even related across decisions, you get coupling of "different" decisions in a way that we didn't have here. Your intuitions are calibrated for that case. Once you have decoupled the decision by coming up with the actual candidate options. The depths-of-hell decision and the lunch decision really are totally isomorphic. I'll probably address this properly later, if I discuss instrumental utility of resources.

Anyways, once you put the problem in dimensionless form, a lot of decisions that seemed very different become almost the same, and a lot of details that seemed important or confusing just disappear. Bask in the clarifying power of a good abstraction.

Utility is Personal

So far we haven't touched the issue of interpersonal utility. That's because that topic isn't actually about VNM utility! There was nothing in the axioms above about there being a utility for each {person, outcome} pair, only for each outcome.

It turns out that if you try to compare utilities between agents, you have to touch unshielded utilities, which means you get radiation poisoning and go to type-theory hell. Don't try it.

And yet, it seems like we ought to care about what others prefer, and not just our own self-interest. But it seems like that inside the utility function, in moral philosophy, not out here in decision theory.

VNM has nothing to say on the issue of utilitarianism besides the usual preference-uncertainty interaction constraints, because VNM is about the preferences of a single agent. If that single agent cares about the preferences of other agents, that goes inside the utility function.

Conversely, because VNM utility is out here, axiomized for the sovereign preferences of a single agent, we don't much expect it to show up in there, in a discussion if utilitarian preference aggregation. In fact, if we do encounter it in there, it's probably a sign of a failed abstraction.

Living with Utility

Let's go back to how much work utility does as a concept. I've spent the last few sections hammering on the work that utility does not do, so you may ask "It's nice that utility theory can constrain our bets a bit, but do I really have to define my utility function by pinning down the relative utilities of every single possible outcome?".

Sort of. You can take shortcuts. We can, for example, wonder all at once whether, for all possible worlds where such is possible, you are indifferent between saving n lives and {50%: saving 2*n; 50%: saving 0}.

If that seems reasonable and doesn't break in any case you can think of, you might keep it around as heuristic in your ad-hoc utility function. But then maybe you find a counterexample where you don't actually prefer the implications of such a rule. So you have to refine it a bit to respond to this new argument. This is OK; the math doesn't want you to do things you don't want to.

So you can save a lot of small thought experiments by doing the right big ones, like above, but the more sweeping of a generalization you make, the more probable it is that it contains an error. In fact, conceptspace is pretty huge, so trying to construct a utility function without inside information is going to take a while no matter how you approach it. Something like disassembling the algorithms that produce your intuitions would be much more efficient, but that's probably beyond science right now.

In any case, in the current term before we figure out how to formally reason the whole thing out in advance, we have to get by with some good heuristics and our current intuitions with a pinch of last minute sanity checking against the VNM rules. Ugly, but better than nothing.

The whole project is made quite a bit harder in that we are not just trying to reconstruct an explicit utility function from revealed preference; we are trying to construct a utility function for a system that doesn't even currently have consistent preferences.

At some point, either the concept of utility isn't really improving our decisions, or it will come in conflict with our intuitive preferences. In some cases it's obvious how to resolve the conflict, in others, not so much.

But if VNM contradicts our current preferences, why do we think it's a good idea at all? Surely it's not wise to be tampering with our very values?

The reason we like VNM is that we have a strong meta-intuition that our preferences ought to be internally consistent, and VNM seems to be the only way to satisfy that. But it's good to remember that this is just another intuition, to be weighed against the rest. Are we ironing out garbage inconsistencies, or losing valuable information?

At this point I'm dangerously out of my depth. As far as I can tell, the great project of moral philosophy is an adult problem, not suited for mere mortals like me. Besides, I've rambled long enough.

Conclusions

What a slog! Let's review:

  • Maximize expected utility, where utility is just an encoding of your preferences that ensures a sane reaction to uncertainty.

  • Don't try to do anything else with utilities, or demons may fly out of your nose. This especially includes looking at the sign or magnitude, and comparing between agents. I call these things "numerology" or "interacting with an unshielded utility".

  • The default for utilities is that utilities are monolithic and inseparable from the entire outcome they are associated with. It takes special structure in your utility function to be able to talk about the marginal utility of something independently of particular outcomes.

  • We have to use the difference-and-ratio ritual to summon the utilities into the real numbers. Record utilities using explicit units and datum, and use dimensionless form for your calculations, which will make many things much clearer and more robust.

  • If you use a VNM basis, you don't need a concept of awfulness, just awesomeness.

  • If you want to do philosophy about the shape of your utility function, make sure you phrase it in terms of lotteries, because that's what utility is about.

  • The desire to use VNM is just another moral intuition in the great project of moral philosophy. It is conceivable that you will have to throw it out if it causes too much trouble.

  • VNM says nothing about your utility function. Consequentialism, hedonism, utilitarianism, etc are up to you.

View more: Prev | Next