Yeah I made versions of this argument to BB before, both in writing (see eg this footnote)[1] and in conversation. This is his response in the article.
Mathematical models show that under certain assumptions, animals in nature live good lives.
In an early paper, Ng produced a mathematical model showing animals lived mostly net-negative lives. Zach Groff updated this model, showing that when one does the math correctly, whether animals live good lives or not depends on various factual assumptions. Thus, he concludes we should be uncertain about net animal welfare.
I don’t think that highly oversimplified models tell us very much about animal life, particularly given how assumption dependent they are. If I’m trying to figure out if a baby who lives a week and then starves to death had an overall positive life, the way I should do that isn’t by constructing a model of the evolutionary function of pleasure and pain. Instead, it’s by seeing what happened in its life and making an assessment. If you know that nearly every animal ever born lives a week or so of constant struggle and then dies painfully, your judgment of whether they had a nice life shouldn’t be much affected by your assessment of context-sensitive formal models.
In addition, Groff’s model suggests that under some assumptions, animals with shorter lives will generally have less evolutionary effort spent making them feel intense pain. But we don’t have to speculate: we can just look at how intensely animals seem, based on their behavior, to suffer before death. The answer is: quite a lot! Behaviorally, even simple animals like fish behave like they’re in very intense pain shortly before death!
For the record, I think Groff agrees with this. He says in a comment:
I agree that this sort of argument deserves relatively low epistemic weight and that the argument is very speculative, as I tried to emphasize in the paper but am worried that not everybody picked up.
The core intuition behind the argument seems to be that if most creatures will die shortly after birth, then it makes less sense to spend a lot of resources making sure they feel lots of pain. If you are going to make 100,000 model cars, you won’t invest too many resources in any one of them. But this on its own doesn’t blunt the core argument because:
It might be very evolutionarily cheap to produce pain. It may be that even simple organisms can feel lots of pain (see above for reasons to think that). Even simple creatures can have pretty robust abilities to see and hear. To give an analogy from Bjorn Merker, even simple DNA structures can self-replicate—it’s plausible that pain can be aptly sustained in simple creatures. Especially because there’s strong empirical evidence that neuron count doesn’t correlate robustly with intensity of experience.
It may be that more complicated brains produce more muted responses to pain. A more complicated brain might be able to richly modulate pain, to make pain signals less intense and more calibrated. Just as a defective radio might make a loud and hideous sound, it might be that a simple animal has less well-calibrated pain signals, and instead just feels unfiltered very intense pain. On this assumption, simpler animals might feel more pain than more complicated animals.
The same factors that lead to diminished pain should also, it seems, lead to diminished pleasure. If animals don’t evolve much pain capacity, because most pain signals are wasted, then it would also be inefficient for them to derive much pleasure capacity (because most pleasure is wasted). My understanding is that the response to this is that if pain and pleasure signals are costly, then they’ll be developed later—but as far as I can tell, there isn’t evidence that vastly greater ability to experience pleasure develops later in life.
Overall, I just don’t think it makes sense to put much weight in a model as speculative as this, when the thing it implies seems to run directly contrary to behavior in various organisms. The best evidence concerning how much pain fish feel when they die is not broad, evolutionary considerations, but behavioral and physiological evidence for profound stress and panic in fish who die.
I think his response is unsatisfactory, and at least overemphasizes a specific subset of the evolutionary arguments against the more intuitive evolutionary arguments. I think he also overestimates the validity and representativeness of the empirical evidence we have.
- ^
For convenience, I’ll reproduce it here:
K-selected species (like humans and elephants) invest heavily in few offspring; each death represents massive lost parental investment. Things that increase evolutionary success for K-selected species(eg, good food, sex) are much smaller evolutionary goods than death is bad. r-selected species (including most insects, though confusingly, perhaps not honeybees) in contrast, produce many offspring with minimal investment, expecting most to die quickly. This creates fundamentally different evolutionary pressures on their experience of suffering and pleasure.For r-selected species, evolution should likely favor: (1) immediate and relatively small per-instance amounts of negative reinforcement/suffering (since e.g. the benefits of second-order pain are muted if an insect can’t learn from pain in its lifetime), (2) strong positive reinforcement for successful behaviors that lead to survival/reproduction, since so few individuals make it. An insect that reaches adulthood has “won” against tremendous odds—its accumulated positive experiences likely outweigh the brief suffering of its many dead siblings. Tomasik et. al’s inference that “most insect life is dying, therefore insects have net negative lives” (which I believe Mr. Bulldog’s opinions implicitly draws from) incorrectly applies K-selected intuitions where individual death is catastrophic to r-selected species where it’s statistically normal.
If you’re interested in learning more, Zach Freitas-Groff gives a more detailed argument including other theoretical considerations (paper, talk).
I expect it to be causation in the other direction. Slamming on the brakes might be correlated with accidents, but it’s neither correct to say brake-slams cause accidents nor that the correlation is spurious and has no causal element.
(My comment is only about that specific point and not about anything else you said)