By way of my friend Roko, I came across the following video:
It's good to watch things like this from time to time so that we remember why the rest of what we do matters. This is what "Reducing Suffering" is really all about.
Sunday, January 3, 2010
Friday, December 25, 2009
SIAI Matching Challenge: Choose Your Own Research Project
Between now and 28 Feb. 2010, SIAI is offering a matching-funds challenge up to $100,000. Intriguingly, donors can choose particular grant proposals to fund -- including, e.g., papers on the following topics:
Each paper has an associated expected cost figure, like this one for the anthropics article:
- "The Coherence of Human Goals"
- "AI Risks Philanthropy: How Many Lives Can We Save per Dollar?"
- "Digital Intelligences and the Evolution of Superorganisms"
Each paper has an associated expected cost figure, like this one for the anthropics article:
Total budget: $5,960, including:
- Costs for researcher time: $4,560
How research costs are estimated:
- Dollars required to support one skilled full time researcher-month[2]: $2,400
Excellent Introduction to SIAI
I quite enjoyed Anna Salamon's talk, "Shaping the Intelligence Explosion," from the Singularity Summit 2009. Unlike many futurist speakers and authors, Salamon presented basic statements about what motivates the Singularity Institute (SIAI) in a fashion free from a lot of the unecessary transhumanist baggage (pet concerns like life extension or multiple-universe hypotheses) that can turn away people from other backgrounds who fundamentally care no less about these issues.
Salamon presented (~1:17 in the video) "Four Key Claims":
Of course, SIAI is fundamentally an academic organization, and most of its research is highly valuable whether or not an "intelligence explosion" ever occurs. Indeed, I encourage donations to SIAI mainly to fund projects that will help us better understand how to reduce massive amounts of suffering in our multiverse. SIAI explores fundamental questions about physics, Bayesian statistics, anthropics, decision theory, infinitarian consequentialism, consciousness, and cognitive science need to be studied regardless of what happens with AI.
Finally, readers may be interested in this other post on SIAI's matching-grant challenge, in which donors can choose their own research projects to support.
Salamon presented (~1:17 in the video) "Four Key Claims":
1. Intelligence can radically transform the world.I'm personally rather skeptical that an intelligence explosion will ever occur -- indeed, I may assign the scenario a very low probability. On the other hand, if one did occur, the magnitude of its impact on our region of the cosmos would be so profound that I think focusing our efforts preparing for such possibilities has high expected value. (Think about why you wear a seat belt the next time you drive to your friend's house down the street.) I liked the way Salamon explained SIAI's core mission as something that almost anyone, even skeptics like me, ought to care about -- not just computer geeks and sci-fi aficionados. (As far as the potential plausibility of intelligence explosion itself, I do think the discussion around 18:00 of whole-brain emulation and the Hansonian takeoff scenario was well done.)
2. An intelligence explosion may be sudden.
3. An uncontrolled intelligence explosion would kill us and destroy practically everything we care about.
4. A controlled intelligence explosion could save us, and protect practically everything else we care about. It is difficult, but worth the attempt.
Of course, SIAI is fundamentally an academic organization, and most of its research is highly valuable whether or not an "intelligence explosion" ever occurs. Indeed, I encourage donations to SIAI mainly to fund projects that will help us better understand how to reduce massive amounts of suffering in our multiverse. SIAI explores fundamental questions about physics, Bayesian statistics, anthropics, decision theory, infinitarian consequentialism, consciousness, and cognitive science need to be studied regardless of what happens with AI.
Finally, readers may be interested in this other post on SIAI's matching-grant challenge, in which donors can choose their own research projects to support.
Saturday, December 5, 2009
Procrastination: "Being in the Mood"
Feeling Good by David Burns has a nice discussion of why people procrastinate. I particularly enjoyed this piece of advice:
Motivation does not come first, action does! You have to prime the pump. Then you will begin to get motivated, and the fluids will flow spontaneously. [...] Individuals who procrastinate frequently confuse motivation and action. You foolishly wait until you feel in the mood to do something. Since you don't feel like doing it, you automatically put it off. (qtd. in Bonnie Runyan McCullough, Totally Organized: The Bonnie McCullough Way, p. 52)I proffer some additional notes. They're all pretty obvious, but I find that I benefit from reminding myself of them frequently.
- Decide on goals and tasks; then act. The point of avoiding procrastination is to get important things done. This requires that you know (1) what you consider important (your objective function) and (2) how best to achieve your goals (what your tasks are). Decide those first; then use Burns's anti-procrastination technique to do the highest-value tasks.
- Update your to-do list over time. There's no need expending willpower to accomplish unimportant tasks, even if they're included on a to-do list. As you learn more and as priorities change, update the ordering of the to-do list. Drop old tasks that you once found important but now do not.
- Don't "save work for later" unless you're sure you'll get it done later. This is the old "never do tomorrow what you can do today" maxim. There are times when I'm tempted to put off a high-value task for later (like checking emails) because I know it'll be fun. This is sometimes a good idea, but not if it causes a backlog of tasks to build up over time. Then finishing them all becomes a chore. And in general, I've found "there's plenty more where that came from," i.e., I can pretty much always find some high-value task for which I'm in the mood, and I don't need to save particular fun tasks for that purpose.
- Avoiding procrastination allows for more time when you don't need to override your mood. In many cases, if there's no hard deadline or stark difference in productivity value between several actions, you ought to do the one that you most want to do, knowing that you'll probably want to do others later on. And if not, you can expend some willpower to get yourself started on them at a later point. Such is the luxury afforded by not being late in finishing time-sensitive tasks: You don't need to constantly expend willpower in forcing yourself to do the next put-out-the-fire item on your list.
Sunday, September 20, 2009
Reflecting on Your Cognitive Algorithms
This post is largely a personal musing; the substantive content has been discussed elsewhere by many other authors.
One of the things that has most transformed the way I look at the world has been cognitive science, specifically the philosophical understanding that grounds it: Seeing the brain as a collection of cognitive algorithms running on biological hardware. This focus on not just what the brain does but how it might do it is fundamentally transformative.
For as long as I can remember, I had known about the types of psychological facts commonly reported in the news: For instance, that this particular region of the brain controls this particular function, or that certain drugs can treat certain brain disorders by acting in certain ways. And it's basic knowledge to almost everyone on the planet that operations inside the head are somehow important for cognitive function, because when people damage their brains, they lose certain abilities.
While I knew all of this abstractly, I never thought much about what it implied philosophically. I saw myself largely as a homunculus, a black box that performed various behaviors and had various emotions over time. Psychology, then, was like macroeconomics or population biology: What sort of trends do these black boxes tend to exhibit in given circumstances? I didn't think about the fact that my behaviors could be reduced further to particular cognitive-processing steps inside my brain.
Yet it seems pretty clear that such a reduction is possible. Think about computers, for instance. Like a human, a computer exhibits particular behaviors in particular circumstances, and certain types of damage cause certain, predictable malfunctions. Yet I don't think I ever pictured a computer as a distinct inner self that might potentially have free will; there were no ghosts or phantoms inside the machine. Once I had some exposure to computer architecture and software design, I could imagine what kinds of operations might be going on behind, say, my text-editor program. So why I did I picture other people and myself differently? My conceptions reflected how an algorithm feels from inside; I simply stopped at the basic homunculus intuition without breaking it apart.
Picturing yourself as a (really complicated and kludgey) computer program casts life in a new light. Rather than simply doing a particular, habitual action in a particular situation, I like to reflect upon, What sort of cognitive algorithm might be causing this behavior? Of course, I rarely have good answers -- studying that is what cognitive science is for -- but the fact that there is an answer soluble in principle gives a new angle on my own psychology. It's perhaps like the Buddhist notion of looking at yourself from the outside, distanced from the in-the-trenches raw experience of an emotion. And, optimistically, such a perspective might suggest ways to improve your psychology, perhaps by adopting new cognitive rituals. That is, of course, what self-help books have done for ages; the computer analogy (e.g., "brain hacks" or "mind hacks," as they're sometimes called) is just one more metaphor for describing the same thing.
Related is the realization that thought isn't a magical, instantaneous operation but, rather, requires physical work. Planning, envisioning scenarios, calculating the results of possible actions, acquiring information, debating different hypotheses about the way the world works, proving theorems, and so on are not -- as, say, logicians or economists often imagine them -- immediate and obvious; they involve computational effort that requires moving atoms around in the real world. For instance, the fact that you considered an option and then disregarded it is not a "wasted effort," because there's no other way to figure out the right answer than actually to do the calculation. Similarly, you're not at fault for failing to know something or for temporarily holding a misconception; the process of acquiring correct (or at least "less wrong") beliefs about the world requires substantive computation and physical interaction with other people. Changing your opinions when you discover you're in error isn't something to be embarrassed about -- it's an intrinsic step in the algorithm of acquiring better opinions itself.
One of the things that has most transformed the way I look at the world has been cognitive science, specifically the philosophical understanding that grounds it: Seeing the brain as a collection of cognitive algorithms running on biological hardware. This focus on not just what the brain does but how it might do it is fundamentally transformative.
For as long as I can remember, I had known about the types of psychological facts commonly reported in the news: For instance, that this particular region of the brain controls this particular function, or that certain drugs can treat certain brain disorders by acting in certain ways. And it's basic knowledge to almost everyone on the planet that operations inside the head are somehow important for cognitive function, because when people damage their brains, they lose certain abilities.
While I knew all of this abstractly, I never thought much about what it implied philosophically. I saw myself largely as a homunculus, a black box that performed various behaviors and had various emotions over time. Psychology, then, was like macroeconomics or population biology: What sort of trends do these black boxes tend to exhibit in given circumstances? I didn't think about the fact that my behaviors could be reduced further to particular cognitive-processing steps inside my brain.
Yet it seems pretty clear that such a reduction is possible. Think about computers, for instance. Like a human, a computer exhibits particular behaviors in particular circumstances, and certain types of damage cause certain, predictable malfunctions. Yet I don't think I ever pictured a computer as a distinct inner self that might potentially have free will; there were no ghosts or phantoms inside the machine. Once I had some exposure to computer architecture and software design, I could imagine what kinds of operations might be going on behind, say, my text-editor program. So why I did I picture other people and myself differently? My conceptions reflected how an algorithm feels from inside; I simply stopped at the basic homunculus intuition without breaking it apart.
Picturing yourself as a (really complicated and kludgey) computer program casts life in a new light. Rather than simply doing a particular, habitual action in a particular situation, I like to reflect upon, What sort of cognitive algorithm might be causing this behavior? Of course, I rarely have good answers -- studying that is what cognitive science is for -- but the fact that there is an answer soluble in principle gives a new angle on my own psychology. It's perhaps like the Buddhist notion of looking at yourself from the outside, distanced from the in-the-trenches raw experience of an emotion. And, optimistically, such a perspective might suggest ways to improve your psychology, perhaps by adopting new cognitive rituals. That is, of course, what self-help books have done for ages; the computer analogy (e.g., "brain hacks" or "mind hacks," as they're sometimes called) is just one more metaphor for describing the same thing.
Related is the realization that thought isn't a magical, instantaneous operation but, rather, requires physical work. Planning, envisioning scenarios, calculating the results of possible actions, acquiring information, debating different hypotheses about the way the world works, proving theorems, and so on are not -- as, say, logicians or economists often imagine them -- immediate and obvious; they involve computational effort that requires moving atoms around in the real world. For instance, the fact that you considered an option and then disregarded it is not a "wasted effort," because there's no other way to figure out the right answer than actually to do the calculation. Similarly, you're not at fault for failing to know something or for temporarily holding a misconception; the process of acquiring correct (or at least "less wrong") beliefs about the world requires substantive computation and physical interaction with other people. Changing your opinions when you discover you're in error isn't something to be embarrassed about -- it's an intrinsic step in the algorithm of acquiring better opinions itself.
Saturday, September 12, 2009
Pain-free Animals?
The current Vegan Outreach newsletter contains a link to a New Scientist piece (as well as an unfortunate editorial) based on a fascinating article: "Knocking Out Pain in Livestock: Can Technology Succeed Where Morality has Stalled?" by Adam Shriver. The moral urgency of such a proposal seems to me obvious, so I was most interested in the discussion of its scientific plausibility.
Shriver presents two example proposals for what might be done. First, we might
I mentioned that Shriver's proposal seems obviously valuable from my perspective, but unfortunately this isn't necessarily the case among the general public. As the New Scientist article notes:
Shriver presents two example proposals for what might be done. First, we might
create knockouts of other mammals (cows and pigs for starters) lacking the AC1 and AC8 enzymes. Interfering with the cAMP cycle in the brain reduces the affective dimension of chronic or persistent pain, rather than pain full stop, but this would still be an improvement over current circumstances. If we could eliminate the sensitization that occurs as a result of painful or traumatic experiences, the animals would still be better off than they are now.Secondly,
Zhou-Feng Chen and colleagues searched the Allen Brain Atlas to find genes that were highly expressed in the ACC but not other areas of the brain [29]. One strong candidate was the peptide P311. The researchers created knockout mice lacking the expression of P311 and found that heat and mechanical sensitivity were normal in the animals. However, they then performed a conditioned place aversion test on the animals and found that the knockouts no longer demonstrated the conditioned place aversion caused by formalin injections, in stark contrast to control rats. Thus, at first glance, it appears that knocking out P311 in mice strongly diminishes the affective dimension of pain while keeping acute responses intact.Since I'm even more interested in wild-animal suffering than farm-animal suffering, in view of the vast difference in numbers of animals involved, my immediate question was whether similar techniques might one day be applicable there. Doing so is a lot trickier, because evolution produced the badness of pain for a reason. Shriver mentions this concern:
Furthermore, P311 is likely to play a similar role in all mammals (Chen, personal communication), so one presumably could engineer other mammals that have a reduced affective dimension of pain while maintaining the sensory dimension of pain.
Since it seems likely that the affective dimension of pain played some role in determining the evolutionary fitness of organisms, we might question whether knockout livestock could really survive up through the point where they are normally slaughtered. However, it appears that the experimental rats were able to survive without complication at least in their cages (Chen, personal communication). This would be a good model for sows or veal calves who spend most of their lives confined in small pens where they can’t do much of anything that would injure or otherwise harm themselves.Producing genetically fit wildlife without pain might require not just knocking out pain but replacing the "pain" - "pleasure" axis with a "less pleasure" - "more pleasure" axis, which could be much more difficult.
I mentioned that Shriver's proposal seems obviously valuable from my perspective, but unfortunately this isn't necessarily the case among the general public. As the New Scientist article notes:
[Alan] Goldberg also contends that public attitudes may make pain-free livestock a non-starter. He and colleague Renee Gardner conducted an online survey on the use of pain-free animals in research and found little public support, even among researchers who experiment on animals (Alternatives to Animal Testing and Experimentation, vol 14, p 145).This underscores the importance of public outreach to change hearts and minds about wild-animal suffering and how it could be prevented.
Thursday, July 16, 2009
Ham and Eggonomics, Part 2
Below are some quotes from and comments on Ch. 8 of the Ham and Eggonomics book introduced in Part 1.
The authors begin with a discussion of the fallacy that "my individual purchases don't matter." They give a nice illustration:
Of course, the analogy to food purchases isn't quite accurate. In practice, as discussed here, an individual's purchasing choice is extremely unlikely to change the number of animals raised, because food is produced and sold in bulk units. However, in the event that a consumer does have an effect, that effect will be huge. Thus, in ignorance of whether a particular purchase is the one that "breaks the camel's back," the expected values of each purchase do add in the same way as the rulers. (To the extent that this reality may be de-motivating for potential vegetarians, perhaps it's better not to mention it too much?)
Pages 3-4 contain a nice discussion of the relevance of elasticities to the question of how an individual's purchases affect the quantity supplied by the market. The authors argue that the supply curves for beef, and to a lesser extent milk, are likely inelastic, while those for pork, and probably also chicken and eggs, are probably relatively elastic. More elastic supply means a bigger change in production when consumer behavior changes. Thus, for instance, abstaining from eating 1 kilogram of chicken has a bigger expected impact on the kilograms of chicken produced than abstaining from 1 kilogram of beef has on the kilograms of beef produced, other things being equal. As far as demand elasticity, the studies that the authors have done suggest a slightly bigger kilogram-for-kilogram impact of abstaining from chicken, pork, veal, and milk relative to beef or eggs. The total results--combining information about supply elasticities and demand elasticities--are shown in Figure 8.2 (see this document for the Chapter 8 figures), which I've reproduced below in sorted order:
If [someone] gives up Total Consumption of ... the Product Falls By ...
One Pound of Milk 0.56 lbs
One Pound of Beef 0.68 lbs
One Pound of Veal 0.69 lbs
One Pound of Pork 0.74 lbs
One Pound of Chicken 0.76 lbs
One Egg 0.91 egg.
Of course, this is not the end of the story. Other (often more important) factors to consider when deciding on dietary purchases include the quality of the lives of animals of different types, and the number of animals required to produce a given quantity of meat, counting both the animals themselves and their parents. Pages 5-6 explain Bailey's own views on the quality of life of various farm animals on a scale of -10 to 10 (see Figure 8.4).
In particular, Bailey thinks some farm animals have lives worth living. Looking at only the non-breeder animals, these are cows (+6), AWA-certified pork (+4), broiler chickens (+3), and cage-free hens (+2). On broiler chickens, Bailey says they "have a life worth living, but because of their leg problems and confined environment, do not fare as well as beef cattle" (p. 5). I'm more skeptical that broilers on average enjoy their lives, but even if they do, I would still be wary of giving them positive welfare because the painfulness of slaughter has to be considered. I personally wouldn't want to live even a mildly pleasant life for only 45 days if it meant that I would afterwards endure slaughter. This is probably true even if I were given electrical stunning and definitely true if I were one of the birds for which the stunning was not effective.
I assume Bailey has included the painfulness of death in his numbers, but it would be good to make this explicit. Otherwise, many readers will just imagine what a broiler chicken looks like during a typical moment of its life, multiply that by ~42 days of life, and conclude that the total experience is positive. An explicit mention of the relevance of lengths of lives would be helpful as well; indeed, this consideration makes Bailey's numbers seem a little odd. How can a beef cow, which lives for 402 days (see the "Beef" section here) have only twice the total happiness (+6 instead of +3) of a broiler chicken that lives 42 days? If Bailey's calculations do involve multiplication of his welfare numbers by lifespan, I missed that part of the text. In any event, doing straight multiplication in that way would still be misleading because it ignores the painfulness of death at the end of a life, unless stress during transport and slaughter has been implicitly incorporated into the per-day average.
Pages 6-7 discuss the impacts of farming on wild animals. In my view, this is the most important part of the calculation, especially if we give more than vanishingly small probability to insect sentience. Of course, if insects' short lives aren't worth living, then it's not clear that pesticide use in crop production represents a net harm (though whether it is or not, the chemicals could still potentially be made less painful).
As they did in Chapter 6, the book authors comment on the possibility that bigger wild animals also suffer enormously:
The authors continue with a discussion of the consideration, How many animals does it take to produce a given quantity of meat? This is the primary variable of interest in my own calculations of suffering per kilogram of meat, but the book authors do a more thorough job, by including numbers of parent animals that need to be raised, as well as the efficiency of production under various conditions. An example of the latter is that cage-free hens produce fewer eggs per week than caged hens.
In fact, this last point is rather important to the question of whether to purchase cage-free eggs (or, at least, whether to encourage others to do so). As the authors explain (p. 11), if you believe that both caged and cage-free hens suffer and that cage-free hens suffer at least ~2/3 times as much as caged hens, then for efficiency reasons, caged-hen eggs entail less total suffering than cage-free-hen eggs. However, Bailey's personal opinion (see Figure 8.4) is that cage-free hens have net happy lives, in which case cage-free eggs would clearly be preferable.
The chapter continues with interesting discussions of public attitudes toward factory farming as assessed by a nationwide telephone survey, as well as how one could compute willingness-to-pay for animal welfare by different consumers. The Appendix describes the mechanics of how elasticities can be used when assessing changes in the quantity of a good supplied, as well as the detailed calculations of how many animals need to be raised to produce a given amount of meat.
Toward the end of the main chapter, the authors make a disturbing comment, though perhaps not one that comes as a surprise:
I hope to get a chance to read more of the book at some point; it contains lots of high-quality and thoughtful discussion. Thanks to the authors for writing it!
The authors begin with a discussion of the fallacy that "my individual purchases don't matter." They give a nice illustration:
Suppose that we take 5,280 [one foot] rulers and placed them in a straight line, end to end. This line of rulers would then be one mile long. It would appear as one long line, and if you could view the entire mile of rulers from above, you would not be able to see one single ruler. If you removed one ruler, the line would grow shorter; there is no doubt as to that. Viewed from above, removing one ruler would not appear to have any effect on the line—but again, it does.
Of course, the analogy to food purchases isn't quite accurate. In practice, as discussed here, an individual's purchasing choice is extremely unlikely to change the number of animals raised, because food is produced and sold in bulk units. However, in the event that a consumer does have an effect, that effect will be huge. Thus, in ignorance of whether a particular purchase is the one that "breaks the camel's back," the expected values of each purchase do add in the same way as the rulers. (To the extent that this reality may be de-motivating for potential vegetarians, perhaps it's better not to mention it too much?)
Pages 3-4 contain a nice discussion of the relevance of elasticities to the question of how an individual's purchases affect the quantity supplied by the market. The authors argue that the supply curves for beef, and to a lesser extent milk, are likely inelastic, while those for pork, and probably also chicken and eggs, are probably relatively elastic. More elastic supply means a bigger change in production when consumer behavior changes. Thus, for instance, abstaining from eating 1 kilogram of chicken has a bigger expected impact on the kilograms of chicken produced than abstaining from 1 kilogram of beef has on the kilograms of beef produced, other things being equal. As far as demand elasticity, the studies that the authors have done suggest a slightly bigger kilogram-for-kilogram impact of abstaining from chicken, pork, veal, and milk relative to beef or eggs. The total results--combining information about supply elasticities and demand elasticities--are shown in Figure 8.2 (see this document for the Chapter 8 figures), which I've reproduced below in sorted order:
If [someone] gives up Total Consumption of ... the Product Falls By ...
One Pound of Milk 0.56 lbs
One Pound of Beef 0.68 lbs
One Pound of Veal 0.69 lbs
One Pound of Pork 0.74 lbs
One Pound of Chicken 0.76 lbs
One Egg 0.91 egg.
Of course, this is not the end of the story. Other (often more important) factors to consider when deciding on dietary purchases include the quality of the lives of animals of different types, and the number of animals required to produce a given quantity of meat, counting both the animals themselves and their parents. Pages 5-6 explain Bailey's own views on the quality of life of various farm animals on a scale of -10 to 10 (see Figure 8.4).
In particular, Bailey thinks some farm animals have lives worth living. Looking at only the non-breeder animals, these are cows (+6), AWA-certified pork (+4), broiler chickens (+3), and cage-free hens (+2). On broiler chickens, Bailey says they "have a life worth living, but because of their leg problems and confined environment, do not fare as well as beef cattle" (p. 5). I'm more skeptical that broilers on average enjoy their lives, but even if they do, I would still be wary of giving them positive welfare because the painfulness of slaughter has to be considered. I personally wouldn't want to live even a mildly pleasant life for only 45 days if it meant that I would afterwards endure slaughter. This is probably true even if I were given electrical stunning and definitely true if I were one of the birds for which the stunning was not effective.
I assume Bailey has included the painfulness of death in his numbers, but it would be good to make this explicit. Otherwise, many readers will just imagine what a broiler chicken looks like during a typical moment of its life, multiply that by ~42 days of life, and conclude that the total experience is positive. An explicit mention of the relevance of lengths of lives would be helpful as well; indeed, this consideration makes Bailey's numbers seem a little odd. How can a beef cow, which lives for 402 days (see the "Beef" section here) have only twice the total happiness (+6 instead of +3) of a broiler chicken that lives 42 days? If Bailey's calculations do involve multiplication of his welfare numbers by lifespan, I missed that part of the text. In any event, doing straight multiplication in that way would still be misleading because it ignores the painfulness of death at the end of a life, unless stress during transport and slaughter has been implicitly incorporated into the per-day average.
Pages 6-7 discuss the impacts of farming on wild animals. In my view, this is the most important part of the calculation, especially if we give more than vanishingly small probability to insect sentience. Of course, if insects' short lives aren't worth living, then it's not clear that pesticide use in crop production represents a net harm (though whether it is or not, the chemicals could still potentially be made less painful).
As they did in Chapter 6, the book authors comment on the possibility that bigger wild animals also suffer enormously:
Animal rights groups tend to romanticize the life of animals in the wild, but anyone who has watched wildlife documentaries can attest to the cruelty of nature. We ask you, the reader, would you rather be a Wildebeest in Africa who must constantly roam for food, always in pursuit by lions and crocodiles, or would you rather be a cow in the U.S., or a hog in the U.S.? (pp. 6-7)
The authors continue with a discussion of the consideration, How many animals does it take to produce a given quantity of meat? This is the primary variable of interest in my own calculations of suffering per kilogram of meat, but the book authors do a more thorough job, by including numbers of parent animals that need to be raised, as well as the efficiency of production under various conditions. An example of the latter is that cage-free hens produce fewer eggs per week than caged hens.
In fact, this last point is rather important to the question of whether to purchase cage-free eggs (or, at least, whether to encourage others to do so). As the authors explain (p. 11), if you believe that both caged and cage-free hens suffer and that cage-free hens suffer at least ~2/3 times as much as caged hens, then for efficiency reasons, caged-hen eggs entail less total suffering than cage-free-hen eggs. However, Bailey's personal opinion (see Figure 8.4) is that cage-free hens have net happy lives, in which case cage-free eggs would clearly be preferable.
The chapter continues with interesting discussions of public attitudes toward factory farming as assessed by a nationwide telephone survey, as well as how one could compute willingness-to-pay for animal welfare by different consumers. The Appendix describes the mechanics of how elasticities can be used when assessing changes in the quantity of a good supplied, as well as the detailed calculations of how many animals need to be raised to produce a given amount of meat.
Toward the end of the main chapter, the authors make a disturbing comment, though perhaps not one that comes as a surprise:
There is evidence to believe that many Americans simply do not care very much about the well-being of farm animals. In our conversations with 300 individuals from three cities in the U.S., one-third told us that they would rather not know how farm animals are raised. They simply want to continue consuming their delicious, safe, and inexpensive food without worrying about whether the animals that provide that food suffer. (p. 17)
I hope to get a chance to read more of the book at some point; it contains lots of high-quality and thoughtful discussion. Thanks to the authors for writing it!
Subscribe to:
Posts (Atom)
