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ag4000

165 karmaJoined Jul 2020

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 I haven't yet looked at the papers cited, but aren't they probably hopelessly confounded?  This seems to be one of the areas where it's hardest to measure causal effects.

Undoubtedly these are interesting questions, and I don't have much to contribute now.  Your thought experiment reminds me of Timmerman's Drowning Children case from "Sometimes there is nothing wrong with letting a child drown".  Timmerman argues with this case that we should reject the strong conclusion from "Famine, Affluence, and Morality".

I agree that the simple story of a producer reacting to changing demand directly is oversimplified.  I think we differ in that I think that absent specific information, we should assume that any commonly consumed animal product's supply response to changing demand should be similar to the ones from Compassion, by the Pound. In other words, we should have our prior on impact centered around some of the numbers from there, and update from there.  I can explain why I think this in more detail if we disagree on this.

Leather example:

Sure, I chose this example to show how one's impact can be diluted, but I also think that decreasing leather consumption is unusually low-impact.  I don't think the stories for other animal products are as convincing.  To take your examples:

  • Eggs for human consumption are unfertilized, so I'm not sure how they are useful for hatching.  Perhaps you are thinking that producers could fertilize the eggs, but that seems expensive and wouldn't make sense if demand for eggs is decreasing.
  • Perhaps I am uncreative, but I'm not sure how one would redirect unused animal products in a way that would replace the demand from human consumption.  Raising an animal seems pretty expensive, so I'm not sure in what scenario this would be so profitable.
  • If we are taking into account the sort of "meta" effects of consuming fewer animal products (such as your example of causing people to innovate new ways of using animal products), then I agree that these increase the variance of impact but I suspect that they strongly skew the distribution of impact towards greater rather than lesser impact.  Some specific, and straightforward, examples: companies research more alternatives to meat; society has to accommodate more vegans and vegan food ends up more widespread and appealing, making more people interested in the transition; people are influenced by their reducetarian friends to eat less meat.

Voting:

I'll need to think about it more, but as with two-candidate votes, I think that petitions can often have better than 1:1 impact.

Not an expert, but I think your impression is correct.  See this post, for example (I recommend the whole sequence).

Late to the party here but I'd check out Räuker et al. (2023), which provides one taxonomy of AI interpretability work.

Thanks, this makes things much clearer to me.

I agree that this style of reasoning depends heavily on the context studied (in particular, the mechanism at play), and that we can't automatically use numbers from one situation for another.  I also agree with what I take to be your main point: In many situations, the impact is less than 1:1 due to feedback loops and so on.

I'm still not sure I understand the specific examples you provide:

  • Animal products used as food: For commonly-consumed food animal products, I would be surprised if the numbers were much lower than those in the table from Compassion by the Pound (assuming that those numbers are roughly correct).  This is because the mechanism used to change levels of production is similar in these cases.  (The previous sentence is probably naive, so I'm open to corrections.)  However, your point about substitution across goods (e.g., from beef to chicken) is well taken.
  • Other animal products: Not one of the examples you gave, but one material that's interested me is cow leather.  I'm guessing that (1) much of leather is a byproduct* of beef production and (2) demand for leather is relatively elastic.  Both of these suggest that abstaining from buying leather goods has a fairly small impact on farmed animal welfare suffering.** 
  • Voting: I am unsure what you mean here by "1:1".  Let me provide a concrete example, which I take to be the situation you're talking about.  We have an election with n voters and 2 candidates, with the net benefit of the better candidate winning U.  If all voters were to vote for the better candidate, then each person's average impact is U / n.  I assume that this is what you mean by the "1" in "1:1": if someone has expected counterfactual impact U / n, then their impact is 1:1.  If this is what you mean by 1:1, then actually one's impact can easily be greater than U / n, going against your claim.  For example, if your credence on the better candidate winning is exactly 50%, then U / n is a lower bound; see Ord (2023), some of whose references show that in real-world situations, the probability of swaying the election can be much greater than 1 / n.

* Not exactly a byproduct, since sales of leather increases the revenue from raising a cow.
** This is not accounting for less direct impacts on demand, like influencing others around oneself.

This position is commonly defended for consequentialist arguments for vegetarianism and veganism; see, e.g., Section 2 here, Section 2 here, and especially Day 2 here.  The argument usually goes something like: if you stop buying one person's worth of eggs, then in expectation, the industry will not produce something like one pound of eggs that they would've produced otherwise.  Even if you are not the tipping point to cause them to cause production, due to uncertainty you still have positive expected impact.  (I'm being a bit vague here, but I recommend reading at least one of the above readings -- especially the third one -- because they make the argument better than I can.)  

In the case of animal product consumption, I'm confused what you mean by "the expected impact still remains negligible in most scenarios" -- are you referring to different situations?  I agree in principle that if the expected impact is tiny, then we don't have much reason on consequentialist grounds to avoid the behavior, but do you have a particular situation in mind?  Can you give concrete examples of where your shift in views applies/where you think the reasoning doesn't apply well? 

Thanks for the posts so far, I've briefly thought about trying some of these ideas but haven't had the courage to really go for them.

One thing I'm wondering: What "sample size" are you basing the takeaways of your posts on intro fellowships on?  That is, how many semesters, and how many people participated?  

Why is this post being downvoted?  I seriously doubt that EAs working to prevent school shootings would be cost-effective, but I don't get why there are downvotes here -- it's a fair question.

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