I am a Senior Research Manager in the Animal Welfare department at Rethink Priorities. The views I express here do not represent Rethink Priorities unless stated otherwise.
Before working in effective altruism, I completed a Ph.D. in psychology studying the evolution of cooperation in humans, with a concentration in quantitative psychology. After that, I was a postdoctoral fellow studying public health. My main interests now are animal welfare and social science methodology/statistics.
I am not familiar with the authors you cite so I will refrain from commenting on their specific proposals until I have read them. I speculate that my comment below is not particularly sensitive to their views; I am a realist about morality and phenomenal consciousness but nevertheless believe that what you are suggesting is a constructive way forward.
So long as it is transparent, I definitely think it would be reasonable to assign relative numerical weights to Welfare Footprint’s categories according to how much you yourself value preventing them. The weights you use might be entirely based on moral commitments, or might partly be based on empirical beliefs about their relative cardinal intensities (if you believe they exist), or even animals’ preferences (if you believe the cardinal intensities do not exist or believe that preferences are what really matter). Unless one assigns lexical priority to the most severe categories, we have to make a prioritization decision somehow, and assigning weights at least makes the process legible.
Joel Michell argues that the theory of conjoint measurement provides indirect tests for whether psychological constructs are quantitative. I do not yet understand the approach in much detail or the arguments for alternative approaches.
I like your summary. I feel (slightly) less hopeless because I think…
Comparisons that involve multiple dimensions of pain are, in principle, possible. I think I would only regard them as impossible if I came upon evidence that pain severity is, in reality, an ordinal construct.
In one sense, I might be more pessimistic about this topic than many because I think it is plausible that many psychological constructs are ordinal.
Behavioral evidence could in theory license cardinal comparisons among different pains. Practical issues of feasibility (and permission from institutions) stand in the way, and I would grant that these will probably never be overcome.
Possibly, cardinal differences in severity are explicitly represented in the brain. If so, then in principle we could measure these representations, though I do not think that we ever will.
We may be able to prioritize between relieving severe pain and long-lasting pain without making direct cardinal comparisons, so long as we have a sense of just how many orders of magnitude pain severity can span. Many aspects of pain experience appear conserved across a large number of species. If we find that pain in humans or laboratory animals have a wide range of pain severity, then there is an above-chance possibility that farmed animals do too. There is also an above-chance possibility that the most severe pains on factory farms are close to the end of the negative side of the range, given that it is difficult to see the adaptive value of being able to represent threats more extreme than, say, being boiled alive.
I would agree that the point above is partly grounded in intuition that has only a vague relationship to a well-established theory of the evolution of pain. Hopefully, advances in this area will reduce our reliance on intuitions that are not grounded by a plausible scientific theory.
Strongly agreed. For those who want exposition on this point, see Ashford’s article on demandingness in contractualism vs. utilitarianism https://doi.org/10.1086/342853
FiveThirtyEight podcast scrutinizes this poll (segment starts 30 minutes in)
https://fivethirtyeight.com/features/politics-podcast-the-politics-of-ai/
Disappointingly shallow analysis, though.
This survey item may represent a circumstance under which YouGov estimates would be biased upwards. My understanding is that YouGov uses quota samples of respondents who have opted-in to panel membership through non-random means, such as responses to advertisements and referrals. They do not have access to respondents without internet access, and those who do but are not internet-savvy are also less likely to opt in. If internet savviness is correlated with item response, then we should expect a bias in the point estimate. I would speculate that internet savviness is positively correlated with worrying about AI risk because they understand the issue better (though I could imagine arguments in the opposite direction—e.g., people who are afraid of computers don’t use them).
To give a concrete example, Sturgis and Kuha (2022) report that YouGov’s estimate of problem gambling in the U.K. was far higher than estimates from firms that used probability sampling that can reach people who don’t use the internet, especially when the interviews were conducted in person. The presumed reasons are that online gambling is more addictive and that people at higher risk of problem gambling prefer online gambling to in-person gambling.
Thanks for this passionate post. Because of it I also donated to the White Helmets. For other readers I would suggest also considering Doctors Without Borders, but in general I have a lot of uncertainty about how best to help.
That was beautifully put, Saulius.
Thanks for your work on this, Tessa! I have some similar follow-up questions:
”Thanks for your support and comment. Unfortunately, it appears as though the environmental permitting regarding this specific farm is being allowed to proceed.”
To clarify, do you mean that Nueva Pescanova has in fact received its environmental permit?
”How likely do you think it is that the farm will succeed in creating a commercially viable product, apart from public pressure? Sounds like there are significant biological and ecological barriers.”
I am also interested in ALI’s take on this. Nueva Pescanova claims it will be able to raise 3k tonnes of farmed octopus starting in 2023. Has ALI been able to verify that this scale is actually feasible right now?
Finally, is an outright, blanket ban on octopus legally possible in Spain or the EU (or even narrowly within the Canary Islands)? Or is a “ban” shorthand for “convince legislators that, in practice, octopus farming won’t meet existing minimal environmental and animal welfare standards”? And what existing farmed animal welfare standards could be invoked, given that octopuses are invertebrates, not vertebrates?
Agreed re: other measures of well-being.
I think the standard approach here would be a two-way fixed effects models with whatever time-varying covariates you can get access to. It makes strong assumptions though:
https://doi.org/10.1017/pan.2020.33
The cutting edge here is probably the general cross-lagged panel model, which in the tutorial below could not distinguish the long-run effect of national income on national well-being from zero.
I do not know of such evidence. I would note the Gallup world data suggesting that the very down and out are the exception to the “most people are happy most of the time” generalization.
“We can’t decisively rule out scale shifts. Obviously, it’s in the nature of something subjective that we can’t objectively check it. As with assessing validity, we have to reason about what’s likely—the fact something is possible doesn’t mean it’s likely.”
There is an objective way to test for scale shifts across countries and over time: Measurement invariance testing (or testing for “differential item functioning,” to use the item response theory vocabulary). Though I agree “we have to reason about what’s likely,” as the test makes strong statistical and substantive assumptions.
There is evidence that subjective well-being measures violate invariance across countries. I do not know of studies examining invariance of well-being across generations off the top of my head, but there is evidence that scale-shifts do occur across generations for other traits, such as narcissism.
“The other part of the explanation appeals to hedonic adaptation and the fact that we do get used to lots of things”
Without taking a stance on the broader thesis of this report, I think the evidence of hedonic adaptation is easy to overstate. Latent state-trait models show that changes in circumstances have detectable changes on well-being at least 10 years later, especially for affective measures. Winning the lottery also has long-term effects of well-being (though more so on life satisfaction), contra the Brickman study that played a role in popularizing hedonic adaptation.
More supportive of your thesis is evidence that the relationship between wealth and happiness is mostly driven by stable factors .
”Also in this context, the research by my own organisation, the Happier Lives Institute, finds that cash transfers to the very poor — those on the global poverty line — actually do have a small but significant effect on subjective wellbeing, one that continues over several years (McGuire, Kaiser, Bach-Mortensen, 2022).”
I would suggest also citing the evidence that this result may be an artifact of publication bias.
“More generally, I think what underlies these ideas of using lower salaries as a costly signal of value-alignment is the tacit assumption that value-alignment is a relatively cohesive, unidimensional trait. But I think that assumption isn’t quite right—as stated, our factor analyses rather suggested there are two core psychological traits defining positive inclinations to effective altruism (expansive altruism and effectiveness-focus), which aren’t that strongly related. (And I wouldn’t be surprised if we found further sub-facets if we did more extensive research on this.)”
I agree with the last sentence of this—there are probably at least as many sub-facets as there are distinct tenets of effective altruism, and only most or all of them coming together in the same person is sufficient for making someone aligned. Two facets is too few, and, echoing David, I do not think that the effectiveness-focus and expansive altruism measures are valid measures of actual psychological constructs (though these constructs may nevertheless exist). My view is that these measures should only be used for prediction, or reconstructed from scratch.
I am less sure the final part of the following:
“I think it’s better for EA recruiters to try to gauge, e.g. inclinations towards cause-neutrality, willingness to overcome motivated reasoning, and other important effective altruist traits, directly, rather than to try to infer them via their willingness to accept a lower salary—since those inferences will typically not have a high degree of accuracy.”
This depends, I think, on how difficult it is to ape effective altruism. As effective altruism becomes more popular and more materials are available to figure out the sorts of things walking-talking EAs say and think, I would speculate that aping effective altruism becomes easier. In this case, if you care about selecting for alignment, a willingness to take on a lower salary could be an important independent source of complimentary evidence.
Interesting idea! I will have to look into whether it has been tried on farmed animals or laboratory animals. I would have a concern similar to the concern I have with the classical conditioning experiments: aversion to the more intense pain might reflect reduced volition rather than welfare maximization. But it does seem plausible that volition is not as much of an issue when the pain is only administered with a low probability.