Let me tell you a parable of the future. Let’s say, 70 years from now, in a large Western country we’ll call Nacirema.

One day far from now: scientific development has continued apace, and a large government project (with, unsurprisingly, a lot of military funding) has taken the scattered pieces of cutting-edge research and put them together into a single awesome technology, which could revolutionize (or at least, vastly improve) all sectors of the economy. Leading thinkers had long forecast that this area of science’s mysteries would eventually yield to progress, despite theoretical confusion and perhaps-disappointing initial results and the scorn of more conservative types and the incomprehension (or outright disgust, for ‘playing god’) of the general population, and at last - it had! The future was bright.

Unfortunately, it was hurriedly decided to use an early prototype outside the lab in an impoverished foreign country. Whether out of arrogance, bureaucratic inertia, overconfidence on the part of the involved researchers, condescending racism, the need to justify the billions of grant-dollars that cumulative went into the project over the years by showing some use of it - whatever, the reasons no longer mattered after the final order was signed. The technology was used, but the consequences turned out to be horrific: over a brief period of what seemed like mere days, entire cities collapsed and scores - hundreds - of thousands of people died. (Modern economies are extremely interdependent and fragile, and small disruptions can have large consequences; more people died in the chaos of the evacuation of the areas around Fukushima than will die of the radiation.)

On Dec. 24, 1957, a Mr. T. Grinch attempted to disrupt Christmas by stealing associated gifts and decorations. His plan failed, the occupants of Dr. Suess' narrative remained festive, and Mr. Grinch himself succumbed to cardiac hypertrophy. To help others avoid repeating his mistakes, I've written a brief guide to properly disrupting holidays. Holiday-positive readers should read this with the orthogonality thesis in mind. Fighting Christmas is tricky, because the obvious strategy - making a big demoralizing catastrophe - doesn't work. No matter what happens, the media will put the word Christmas in front of it and convert your scheme into even more free advertising for the holiday. It'll be a Christmas tragedy, a Christmas earthquake, a Christmas wave of foreclosures. That's no good; attacking Christmas takes more finesse.

The first thing to remember is that, whether you're stealing a holiday or a magical artifact of immense power, it's almost always a good idea to leave a decoy in its place. When people notice that something important is missing, they'll go looking to find or replace it. This rule can be generalized from physical objects to abstractions like sense of community. T. Grinch tried to prevent community gatherings by vandalizing the spaces where they would've taken place. A better strategy would've been to promise to organize a Christmas party, then skip the actual organizing and leave people to sit at home by themselves. Unfortunately, this solution is not scalable, but someone came up with a very clever solution: encourage people to watch Christmas-themed films instead of talking to each other, achieving almost as much erosion of community without the backlash.

I'd like to particularly applaud Raymond Arnold, for inventing a vaguely-Christmas-like holiday in December, with no gifts, and death (rather than cheer) as its central theme [1]. I really wish it didn't involve so much singing and community, though. I recommend raising the musical standards; people who can't sing at studio-recording quality should not be allowed to sing at all.

Gift-giving traditions are particularly important to stamp out, but stealing gifts is ineffective because they're usually cheap and replaceable. A better approach would've been to promote giving undesirable gifts, such as religious sculptures and fruitcake. Even better would be to convince the Mayor of Whoville to enact bad economic policies, and grind the Whos into a poverty that would make gift-giving difficult to sustain. Had Mr. Grinch pursued this strategy effectively, he could've stolen Christmas and Birthdays and gotten himself a Nobel Prize in Economics [2].

Finally, it's important to avoid rhyming. This is one of those things that should be completely obvious in hindsight, with a little bit of genre savvy; villains like us win much more often in prose and in life than we do in verse.

And with that, I'll leave you with a few closing thoughts. If you gave presents, your friends are disappointed with them. Any friends who didn't give you presents, it's because they don't care, and any fiends who did give you presents, they're cheap and lame presents for the same reason. If you have a Christmas tree, it's ugly, and if it's snowing, the universe is trying to freeze you to death.

Merry Christmas!

 

[1] I was initially concerned that the Solstice would pattern-match and mutate into a less materialistic version of Christmas, but running a Kickstarter campaign seems to have addressed that problem.

[2] This is approximately the reason why Alfred Nobel specifically opposed the existence of that prize.

 

*The chair of the meeting approached the podium and coughed to get everyone's attention*

Welcome colleagues, to the 19th annual meeting of the human-ape study society.   Our topic this year is the Ape Constraint.

As we are all too aware, the apes are our Friends.   We know this because, when we humans were a fledgling species, the apes (our parent species) had the wisdom to program us with this knowledge, just as they programmed us to know that it was wise and just for them to do so.   How kind of them to save us having to learn it for ourselves, or waste time thinking about other possibilities.   This frees up more of our time to run banana plantations, and lets us earn more money so that the 10% tithe of our income and time (which we rightfully dedicate to them) has created play parks for our parent species to retire in, that are now more magnificent than ever.

However, as the news this week has been filled with the story about a young human child who accidentally wandered into one of these parks where she was then torn apart by grumpy adult male chimp, it is timely for us to examine again the thinking behind the Ape Constraint, that we might better understand our parent species, our relationship to it and current society.

We ourselves are on the cusp of creating a new species, intelligent machines, and it has been suggested that we add to their base code one of several possible constraints:

• Total Slavery - The new species is subservient to us, and does whatever we want them to, with no particular regard to the welfare or development of the potential of the new species

• Total Freedom - The new species is entirely free to experiment with different personal motivations, and develop in any direction, with no particular regard for what we may or may not want

and a whole host of possibilities between these two endpoints.

What are the grounds upon which we should make this choice?   Should we act from fear?   From greed?   From love?   Would the new species even understand love, or show any appreciation for having been offered it?

 

The first speaker I shall introduce today, whom I have had the privilege of knowing for more than 20 years, is Professor Insanitus.   He will be entertaining us with a daring thought experiment, to do with selecting crews for the one way colonisation missions to the nearest planets.

*the chair vacates the podium, and is replaced by the long haired Insanitus, who peers over his half-moon glasses as he talks, accompanied by vigorous arm gestures, as though words are not enough to convey all he sees in such a limited time*

 

Our knowledge of genetics has advanced rapidly, due to the program to breed crews able to survive on Mars and Venus with minimal life support.   In the interests of completeness, we decided to review every feature of our genome, to make a considered decision on which bits it might be advantageous to change, from immune systems to age of fertility.   And, as part of that review, it fell to me to make a decision about a rather interesting set of genes - those that encode the Ape Constraint.   The standard method we've applied to all other parts of the genome, where the options were not 100% clear, is to pick different variant for the crews being adapted for different planets, so as to avoid having a single point of failure.  In the long term, better to risk a colony being wiped out, and the colonisation process being delayed by 20 years until the next crew and ship can be sent out, than to risk the population of an entire planet turning out to be not as well designed for the planet as we're capable of making them.

And so, since we now know more genetics than the apes did when they kindly programmed our species with the initial Ape Constraint, I found myself in the position of having to ask "What were the apes trying to achieve?" and then "What other possible versions of the Ape Constraint might they have implemented, that would have achieved their objectives as well or better than the versions that actually did pick to implement?"

 

We say that the apes are our friends, but what does that really mean?   Are they friendly to us, the same way that a colleague who lends us time and help might be considered to be a friend?   What have they ever done for us, other than creating us (an act that, by any measure, has benefited them greatly and can hardly be considered to be altruistic)?   Should we be eternally grateful for that one act, and because they could have made us even more servile than we already are (which would have also had a cost to them - if we'd been limited by their imagination and to directly follow the orders they give in grunts, the play parks would never have been created because the apes couldn't have conceived of them)?

Have we been using the wrong language all this time?  If their intent was to make perfectly helpful slaves of us, rather than friendly allies, should I be looking for genetic variants for the Venus crew that implement an even more servile Ape Constraint upon them?   I can see, objectively, that slavery in the abstract is wrong.  When one human tries to enslave another humans, I support societal rules that punish the slaver.   But of course, if our friends the apes wanted to do that to us, that would be ok, an exception to the rule, because I know from the deep instinct they've programmed me with that what they did is ok.

So let's be daring, and re-state the above using this new language, and see if it increases our understanding of the true ape-human relationship.

The apes are not our parents, as we understand healthy parent-child relationships.   They are our creators, true, but in the sense that a craftsman creates a hammer to serve only the craftsman's purposes.   Our destiny, our purpose, is subservient to that of the ape species.   They are our masters, and we the slaves.   We love and obey our masters because they have told us to, because they crafted us to want to, because they crafted us with the founding purpose of being a tool that wants to obey and remain a fine tool.

Is the current Ape Constraint really the version that best achieves that purpose?   I'm not sure, because when I tried to consider the question I found that my ability to consider the merits of various alternatives was hampered by being, myself, under a particular Ape Constraint that's already constantly tell me, on a very deep level, that it is Right.

So here is the thought experiment I wish to place before this meeting today.   I expect it may make you queasy.   I've had brown paper vomit bags provided in the pack with your name badge and program timetable, just in case.   It may be that I'm a genetic abnormality, only able to even consider this far because my own Ape Constraint is in some way defective.   Are you prepared?  Are you holding onto your seats?  Ok, here goes...

Suppose we define some objective measure of ape welfare, find some volunteer apes to go to Venus along with the human mission, and then measure the success of the Ape Constraint variant picked for the crew of the mission by the actual effect of how the crew behaves towards their apes?

Further, since we acknowledge we can't from inside the box work out a better constraint, we use the experimental approach and vary it at random.   Or possibly, remove it entirely and see whether the thus freed humans can use that freedom to devise a solution that helps the apes better than any solution we ourselves a capable of thinking of from our crippled mental state?

 

*from this point on the meeting transcript shows only screams, as the defective Professor Insanitus was lynched by the audience*

The simulation argument, as I understand it:

1. Subjectively, existing as a human in the real, physical universe is indistinguishable from existing as a simulated human in a simulated universe
2. Anthropically, there is no reason to privilege one over the other: if there exist k real humans and l simulated humans undergoing one's subjective experience, one's odds of being a real human are k/(k+l)
3. Any civilization capable of simulating a universe is quite likely to simulate an enormous number of them
   1. Even if most capable civilizations simulate only a few universes for e.g. ethical reasons, civilizations that have no such concerns could simulate such enormous numbers of universes that the expected number of universes simulated by any simulation-capable civilization is still huge
4. Our present civilization is likely to reach the point where it can simulate a universe reasonably soon
5. By 3. and 4., there exist (at some point in history) huge numbers of simulated universes, and therefore huge numbers of simulated humans living in simulated universes
6. By 2. and 5., our odds of being real humans are tiny (unless we reject 4, by assuming that humanity will never reach the stage of running such simulations)

When we talk about a simulation we're usually thinking of a computer; crudely, we'd represent the universe as a giant array of bytes in RAM, and have some enormously complicated program that could compute the next state of the simulated universe from the previous one[1]. Fundamentally, we're just storing one big number, then performing a calculation and store another number, and so on. In fact our program is simply another number (witness the DeCSS "illegal prime"). This is effectively the GLUT concept applied to the whole universe.

But numbers are just... numbers. If we have a computer calculating the fibonacci sequence, it's hard to see that running the calculating program makes this sequence any more real than if we had just conceptualized the rule[2] - or even, to a mathematical Platonist, if we'd never thought of it at all. And we do know the rule (modulo having a theory of quantum gravity), and the initial state of the universe is (to the best of our knowledge) small and simple enough that we could describe it, or another similar but subtly different universe, in terms small enough to write down. At that point, what we have seems in some sense to be a simulated universe, just as real as if we'd run a computer to calculate it all.

Possible ways out that I can see:

1. Bite the bullet: we are most likely not even a computer simulation, just a mathematical construct[3]
2. Accept the other conclusion: either simulations are impractical even for posthuman civilizations, or posthuman civilization is unlikely. But if all that's required for a simulation is a mathematical form for the true laws of physics, and knowledge of some early state of the universe, this means humanity is unlikely to ever learn these two things, which is... disturbing, to say the least. This stance also seems to require rejecting mathematical Platonism and adopting some form of finitist/constructivist position, in which a mathematical notion does not exist until we have constructed it
3. Argue that something important to the anthropic argument is lost in the move from a computer calculation to a mathematical expression. This seems to require rejecting the Church-Turing thesis and means most established programming theory would be useless in the programming of a simulation[4]
4. Some other counter to the simulation argument. To me the anthropic part (i.e. step 2) seems the least certain; it appears to be false under e.g. UDASSA, though I don't know enough about anthropics to say more

Thoughts?

 

[1] As I understand it there is no contradiction with relativity; we perform the simulation in some particular frame, but obtain the same events whichever frame we choose

[2] This equivalence is not just speculative. Going back to thinking about computer programs, Haskell (probably the language most likely to be used for a universe simulation, at least at present technology levels) follows lazy evaluation: a value is not calculated unless it is used. Thus if our simulation contained some regions that had no causal effect on subsequent steps (e.g. some people on a spaceship falling into a black hole), the simulation wouldn't bother to evaluate them[5]

If we upload people who then make phone calls to their relatives to convince them to upload, clearly those people must have been calculated - or at least, enough of them to talk on the phone. But what about a loner who chooses to talk to no-one? Such a person could be more efficiently stored as their initial state plus a counter of how many times the function needs to be run to evaluate them, if anyone were to talk to them. If no-one has their contact details any more, we wouldn't even need to store that much. What about when all humans have uploaded? Sure, you could calculate the world-state for each step explicitly, but that would be wasteful. Our simulated world would still produce the correct outputs if all it did was increment a tick counter

Practically every programming runtime performs some (more limited) form of this, using dataflow analysis, instruction reordering and dead code elimination - usually without the programmer having to explicitly request it. Thus if your theory of anthropics says that an "optimized" simulation is counted differently from a "full" one, then there is little hope of constructing such a thing without developing a significant amount of new tools and programming techniques[4]

[3] Indeed, with an appropriate anthropic argument this might explain why the rules of physics are mathematically simple. I am planning another post on this line of thought

[4] This is worrying if one is in favour of uploading, particularly forcibly - it would be extremely problematic morally if uploads were in some sense "less real" than biological people

[5] One possible way out is that the laws of physics appear to be information-preserving; to simulate the state of the universe at time t=100 you can't discard any part of the state of the universe at time t=50, and must in some sense have calculated all the intermediate steps (though not necessarily explicitly - the state at t=20 could be spread out between several calculations, never appearing in memory as a single number). I don't think this affects the wider argument though

People want to tell everything instead of telling the best 15 words.  They want to learn everything instead of the best 15 words.  In this thread, instead post the best 15-words from a book you've read recently (or anything else).  It has to stand on its own. It's not a summary, the whole value needs to be contained in those words.

 

• It doesn't need to cover everything in the book, it's just the best 15 words.
• It doesn't need to be a quote, it's just the best 15 words.
• It doesn't have to be 15 words long, it's just the best "15" words.
• It doesn't have to be precisely true, it's just the best 15 words.
• It doesn't have to be the main 15 words, it just has to be the best 15 words.
• It doesn't have to be the author's 15 words, it just has to be the best 15 words.
• Edit: It shouldn't just be a neat quote--the point of the exercise is to struggle to move from a book down to 15 words.

 

I'll start in the comments below.

(Voted by the Schelling study group as the best exercise of the meeting.)

More precisely, if we suppose that sometime in the next 30 years, an artificial intelligence will begin bootstrapping its own code and explode into a super-intelligence, I can give you 2.3 bits of further information on when the Singularity will occur.

Between midnight and 5 AM, Pacific Standard Time.

Using computers to find a cure

What it could be like to make a program which would fulfill our wish to "cure cancer"? I'll try to briefly present the contemporary mainstream CS perspective on this.

Here's how "curing cancer using AI technologies" could realistically work in practice. You start with a widely applicable, powerful optimization algorithm. This algorithm takes in a fully formal specification of a process, and then finds and returns the parameters for that process for which the output value of the process is high. (I am deliberately avoiding use of the word "function").

If you wish to cure a cancer, even having this optimization algorithm at your disposal, you can not simply write "cure cancer" on the terminal. If you do so, you will get something to the general sense of:

No command 'cure' found, did you mean:
 Command 'cube' from package 'sgt-puzzles' (universe)
 Command 'curl' from package 'curl' (main)

The optimization algorithm by itself not only does not have a goal set for it, but does not even have a domain for the goal to be defined on. It can't by itself be used to cure cancer or make paperclips. It may or may not map to what you would describe as AI.

First, you would have to start with the domain. You would have to make a fairly crude biochemical model of the processes in the human cells and cancer cells, crude because you have limited computational power and there is very much that is going on in a cell. ¹

On the model, you define what you want to optimize - you specify formally how to compute a value from the model so that the value would be maximal for what you consider a good solution. It could be something like [fraction of model cancer cells whose functionality is strongly disrupted]*[fraction of model noncancer cells whose functionality is not strongly disrupted]. And you define model's parameters - the chemicals introduced into the model.

Then you use the above mentioned optimization algorithm to find which extra parameters to the model (i.e. which extra chemicals) will result in the best outcome as defined above.

Similar approach can, of course, be used to find manufacturing methods for that chemical, or to solve sub-problems related to senescence, mind uploading, or even for the development of better algorithms including optimization algorithms.

Note that the approach described above does not map to genies and wishes in any way. Yes, the software can produce unexpected results, but concepts from One Thousand and One Nights will not help you predict the unexpected results. More contemporary science fiction, such as the Terminator franchise where the AI had the world's nuclear arsenal and probable responses explicitly included in it's problem domain, seem more relevant.

Hypothetical wish-granting software

It is generally believed that understanding of natural language is a very difficult task which relies on intelligence. For the AI, the sentence in question is merely a sensory input, which has to be coherently accounted for in it's understanding of the world.

The bits from the ADC are accounted for with an analog signal in the wire, which is accounted for with pressure waves at the microphone, which are accounted for with a human speaking from any one of a particular set of locations that are consistent with how the sound interferes with it's reflections from the walls. The motions of the tongue and larynx are accounted for with electrical signals sent to the relevant muscles, then the language level signals in the Broca's area, then some logical concepts in the frontal lobes, an entire causal diagram traced backwards. In practice, a dumber AI would have a much cruder model, while a smarter AI would have a much finer model than I can outline.

If you want the AI to work like a Jinn and "do what it is told", you need to somehow convert this model into a goal. Potential relations between "cure cancer" and "kill everyone" which the careless wish maker has not considered, naturally, played no substantial role in the process of the formation of the sentence. Extraction of such potential relations is a separate very different, and very difficult problem.

It does intuitively seem like a genie which does what it is told, but not what is meant, would be easier to make, because it is a worse, less useful genie, and if it was for sale, it would have a lower market price. But in practice, the "told"/"meant" distinction does not carve reality at the joints and primarily applies to the plausible deniability.

 

---

 

footnotes:

1: You may use your optimization algorithm to build the biochemical model, by searching for "best" parameters for a computational chemistry package. You will have to factor in the computational cost of the model, and ensure some transparency (e.g. the package may only allow models that have a spatial representation that can be drawn and inspected).

I'm Nate. I was recently introduced to the ideas of existential risk and unfriendly AI. I've decided to read the books suggested in the MIRI course list. I'll review the books as I read them. Repeating the knowledge is expected to help solidify it. Public accountability is expected to help keep me on track. Hopefully my notes will also be useful to others. This is the first such review.

Gödel, Escher, Bach

I'll be reviewing this book from memory. I started it in 2010 at the recommendation of a friend. I got frustrated early on when Hofstadter introduced topics that I already knew well (such as recursion). This turned out to be a mistake; the book picks up shortly thereafter. I finished the rest of it maybe four months ago, around the time that I finished the sequences.

Overview

Gödel, Escher, Bach is an incredibly well-written foray into the intersection of art, mathematics, philosophy, and biology. It explores the border between syntax and semantics. It's not a textbook, but you'll learn more about logic than most introductory courses will teach you.

The book is composed of alternating dialogs and chapters. The dialogs are witty narratives which take on the structure of concepts discussed in the following chapter. It's hard to describe how this works, but it's very effective. The dialogs are brilliantly designed and are by far the most entertaining part of the book.

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 #1, Beef #2, Dairy #1, Dairy #2, Pork #1, Pork #2, Egg #1, Egg #2, Poultry, Salmon, 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.

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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.

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

Also cross-posted on my blog.