Well, first of all, we should be very uncertain that species sufficiently far from us are even capable of suffering at all. I take it as self-evident that suffering is in the brain, a property of neurons; however, I also think that small machine learning models clearly donāt experience suffering, so āhaving something thatās kinda maybe like neuronsā is not sufficient.
Bees have fewer than a million neurons and likely fewer āparametersā than even small LLMs like BERT-base. Moreover, a lot of those neurons are likely used for controlling the wings and for implementing hardcoded algorithms like ābuild a hex-tiled beehiveā.
I agree with all of this, although I think this bears primarily on whether theyāre sentient at all, not really on their hedonic welfare range conditional on sentience. I donāt think bees are extremely unlikely to be sentient based on the evidence I have seen and my intuitions about consciousness.
I donāt believe a single neuron, by itself, can experience pain. Itās an emergent phenomenon. But the fact that itās emergent suggests it might even scale super-linearly with the number of neurons (e.g. perhaps quadratically, for the number of possible interactions between neurons, though thatās far from certain). I find the assumption of sub-linear scaling (or no scaling at all) to be particularly weird.
I used to believe that hedonic welfare ranges should very probably scale (sublinearly) with neuron counts, but Iāve become pretty skeptical that they should scale with neuron counts at all based on RPās work:
Iād recommend those posts. I also have some more thoughts against superlinear scaling in particular relative to sublinear scaling not covered directly in those two posts, but Iāll put them in a reply to this comment, which is already very long.
Itās not clear that āhas subjective feelingsā dates back to such early brain designs. If it arose later, then bees are either not conscious or have independently-evolved consciousness, which would be nearly impossible to reason about.
I would guess that it did arise independently after our last common ancestor if bees are conscious (similarly for cephalopods). I agree that it makes it much harder to reason about, but I donāt think this gives us more reason to believe that bees have (much) narrower ranges than that they have (much) larger ranges, conditional on their capacity to suffer or experience pleasure at all. Incomparability is another possibility.
Also, you can be guided by more general accounts of or intuitions about consciousness and suffering, or even rough candidate functionalist definitions of hedonic intensity, e.g. trying to generalize Welfare Footprint Projectās.
I donāt see why ājuvenile bees sometimes roll a ballā (which gets translated into ābees playā) should weigh so significantly into our considerations, here. Itās kind of ridiculous. Either you think bees should be weighted highly, or you think they should be given little weight, but why is ājuveniles roll a ball!ā such strong evidence of the amount of pain or pleasure they feel?
Yet āroll a ballā (and a few similar proxies) is the only thing the OP is going by. Thereās nothing else in the model!
Iām pretty sympathetic to this, and Iām not very sympathetic to most of the models, other than the neuron count model, the JND model and the equality model. Itās hard for me to see why most of the proxies used would matter, conditional on sentience.
I could imagine āplay behaviorā mattering if we could code its intensity, either absolutely or relatively, similar to Welfare Footprint Project definitions for pain levels, but this isnāt really what the models here do, and Iād imagine displaying play behavior not really telling us much about intensity anyway. I think panic-like behavior could be a decent indicator for pretty intense suffering (disabling and maybe even excruciating according to WFP) conditional on sentience, so Iād probably give animals without it much narrower welfare ranges.
PTSD-like behavior could be another, but Iād give it less weight, since it seems more likely to be biased either way.
Thanks for your reply. I agree with much of what you write. Below are some disagreements.
I agree with all of this, although I think this bears primarily on whether theyāre sentient at all, not really on their hedonic welfare range conditional on sentience. I donāt think bees are extremely unlikely to be sentient based on the evidence I have seen and my intuitions about consciousness.
This seems to be framing consciousness as a binary, a yes/āno. That sounds wrong; many people view it as a sliding scale, and some of your links talk about āmore valenced consciousnessā etc.
In any event, I understood the 14 bees = 1 human to be after accounting for the low chance of bee sentience. Did I misunderstand? The summary figure lists various disclaimers, but it notably does NOT say āconditioned on sentienceā.
I used to believe that hedonic welfare ranges should very probably scale (sublinearly) with neuron counts, but Iāve become pretty skeptical that they should scale with neuron counts at all based on RPās work:
One could write equally convincing arguments against ādo juveniles roll a ballā as a proxy. Neuron counts are bad and have many flaws; ādo they roll a ballā is WORSE and has MORE flaws. That remains the case if you add 100 other subjective proxies, all wishy-washy things, all published by bee researchers eager to tell you bees are amazing.
It remains the case that neuron counts are more objective than any of the other proxies. It also is the case that NOT using neuron counts is a guarantee of not getting tiny estimates: thereās no clear way to combine 100 yes/āno proxies and get an answer like āone-millionth of a humanā. Only with neuron counts can you get this. I could tell you that even before looking at your results: your methodology eliminates a whole range of answers a priori.
(Also, the argument that bees are amazing is used in Shriverās post, which makes this discussion circular: he doesnāt want to use neuron counts because it underestimates bees (according to intuition, I guess).)
Humans donāt seem to have many times more synapses per neuron than bees (1,000 to 7,000 in human brains vs ~1,000 in honeybee brains, based on data in [1] and [2]), so the number of direct connections between neurons is close-ish to proportional with neuron counts between humans and bees. We could have many times more indirect connections per neuron through paths of connections, but the influence from one neuron on another itās only indirectly connected to should decrease with the lengths of paths from the first to the second, because the signal has to make it farther and compete with more signals. This doesnāt rule out superlinear scaling, but can limit it.
Compare: if each server on the internet is connected to only 10 other servers on average, does it hold that each user of the internet can only reach a constant number of websites?
No: the graph is an expander, and if there are n nodes, the distance between any two nodes may be as little as O(log n), even if the degree of each node is constant. Hence, via a few hops on the graph, a node may talk to many other nodes (potentially even all of them).
Neural networks (whether artificial or natural) can certainly cause interaction between far away neurons, and the O(log n) distance does not necessarily mean the signal dies. This is similar to how my words reach you despite the packets passing through many servers along the way.
I donāt know for sure that this is how the brain works. However, I find it plausible. I also note that the human brain achieves an incredible amount of intelligence, so certain impressive interactions between neurons are definitely taking place.
I definitely do think welfare ranges can vary across beings, so Iām not thinking in binary terms.
~14 bees to 1 human is indeed after adjusting for the probability of sentience.
Neuron counts are plausibly worse than all of the other proxies precisely because of how large the gaps in welfare range they imply are. The justifications could be bad for most or all proxies, and maybe even worse for others than neuron counts (although I do think some of the proxies are far more justified), but neuron counts could introduce the most bias the way theyāre likely to be used. Whether or not they have a heart or literally no proxies at all would give more plausible ranges than neuron counts, conditional on sentience (having a nonzero welfare range at all).
The kinds of proxies for the functions of valence and how they vary with hedonic intensity Iād use would probably give results more similar to any of the non-neuron count models than to the neuron count model (or models with larger gaps). A decent approximation (a lower bound) of the expected welfare range ratio over humans would be the probability that the animal has states of similar hedonic intensity to the most intense in humans, based on behavioural markers of intensity and whether they have the right kinds of cognitive mechanisms. And I canāt imagine assigning tiny probabilities to that, conditional on sentience, based on current evidence (which is mostly missing either way). For bees, they had an estimated 42.5% probability of sentience in this report, so a 16.7% chance of having similarly intense hedonic states conditional on sentience would give you 14 bees per human. I wouldnāt go lower than 1% or higher than 80% based on current evidence, so 16.7% wouldnāt be that badly off. (This is all assuming the expected number of conscious/āvalenced systems in any brain is close to 1 or lower, or their correlation is very low or we can ignore that possibility for other reasons.)
Wrt packets sent along servers, servers are designed to be very reliable, have buffers in case of multiple or large packets received within a short period, and so on. Iād guess neural signals would compete much more with each other, and at each neuron they reach have a non-tiny chance of not being passed along, so you get decaying signal strength. Many things donāt make it to your conscious awareness. On the other side, there may be multiple similar signals through multiple paths in a brain, but that means more competition between distinct signals, too. Similar signals being sent across multiple paths may also be in part because of more neurons directly connected to periphery firing, not just few neurons influencing a superlinear number of neurons each on average.
Neuron counts are plausibly worse than all of the other proxies precisely because of how large the gaps in welfare range they imply are.
If Iām reading this right, you are dismissing neuron counts because of your intuition. You correctly realize that intuitions trump all other considerations, and the game is just to pick proxies that agree with your intuitions and allow you to make them more systematic.
I agree with this approach but strongly disagree with your intuitions. ā14 bees = 1 human, after adjusting for probability of sentienceā is so CLEARLY wrong that it is almost insulting. Thatās my intuition speaking. Iām doing the same thing youāre doing when you dismiss neuron counts, just with a different starting intuition than you.
I think it would be better if the OP was more upfront about this bias.
Iām not dismissing neuron counts because of my direct intuitions about welfare ranges across species. That would be circular, motivated reasoning and an exercise in curve fitting. Iām dismissing them because the basis for their use seems weak, for reasons explained in posts RP has written and my own (vague) understanding of what plausibly determines welfare ranges in functionalist terms. When RP started this project and for most of the time I spent working on the conscious subsystems report, I actually thought we should use neuron counts by default. I didnāt change my mind about neuron counts because my direct intuitions about relative welfare ranges between specific species changed; I changed my mind because of the arguments against neuron counts.
What I meant in what you quoted is that neuron counts seem especially biased, where the biases are measured relative to the results of quantitative models roughly capturing my current understanding of how consciousness and welfare ranges actually work, like the one I described in the comment you quoted from. Narrow range proxies give less biased results (relative to my modelsā results) than neuron counts, including such proxies with little or no plausible connection to welfare ranges. But Iād just try to build my actual model directly.
How exactly are you thinking neuron counts contribute to hedonic welfare ranges, and how does this relate to your views on consciousness? What theories of consciousness seem closest to your views?
Why do you think 14 bees per human is so implausible?
(All this being said, the conscious subsystems hypothesis might still support the use of neuron counts as a proxy for expected welfare ranges, even if the hypothesis seems very unlikely to me. Iām not sure how unlikely; I have deep uncertainty.)
Some thoughts against superlinear scaling in particular relative to sublinear scaling not covered directly in those two posts:
If we count multiple conscious subsystems in a brain even allowing substantial overlap between multiple of them to get to superlinear scaling (thatās substantially faster than linear scaling), that seems likely to imply ādouble countingā valenced experiences, and my guess is that this would get badly out of hand, e.g. in exponential territory, which would also have counterintuitive implications. I discuss this here.
Humans donāt seem to have many times more synapses per neuron than bees (1,000 to 7,000 in human brains vs ~1,000 in honeybee brains, based on data in [1] and [2]), so the number of direct connections between neurons is close-ish to proportional with neuron counts between humans and bees. We could have many times more indirect connections per neuron through paths of connections, but the influence from one neuron on another itās only indirectly connected to should decrease with the lengths of paths from the first to the second, because the signal has to make it farther and compete with more signals. This doesnāt rule out superlinear scaling, but can limit it.
Ah, Iād also recommend Bobās Donāt Balk at Animal-friendly Results in this series.
I agree with all of this, although I think this bears primarily on whether theyāre sentient at all, not really on their hedonic welfare range conditional on sentience. I donāt think bees are extremely unlikely to be sentient based on the evidence I have seen and my intuitions about consciousness.
I used to believe that hedonic welfare ranges should very probably scale (sublinearly) with neuron counts, but Iāve become pretty skeptical that they should scale with neuron counts at all based on RPās work:
Adam Shriverās post on (mostly against) neuron counts.
Our post on (mostly against) conscious subsystems.
Iād recommend those posts. I also have some more thoughts against superlinear scaling in particular relative to sublinear scaling not covered directly in those two posts, but Iāll put them in a reply to this comment, which is already very long.
I would guess that it did arise independently after our last common ancestor if bees are conscious (similarly for cephalopods). I agree that it makes it much harder to reason about, but I donāt think this gives us more reason to believe that bees have (much) narrower ranges than that they have (much) larger ranges, conditional on their capacity to suffer or experience pleasure at all. Incomparability is another possibility.
Also, you can be guided by more general accounts of or intuitions about consciousness and suffering, or even rough candidate functionalist definitions of hedonic intensity, e.g. trying to generalize Welfare Footprint Projectās.
Iām pretty sympathetic to this, and Iām not very sympathetic to most of the models, other than the neuron count model, the JND model and the equality model. Itās hard for me to see why most of the proxies used would matter, conditional on sentience.
I could imagine āplay behaviorā mattering if we could code its intensity, either absolutely or relatively, similar to Welfare Footprint Project definitions for pain levels, but this isnāt really what the models here do, and Iād imagine displaying play behavior not really telling us much about intensity anyway. I think panic-like behavior could be a decent indicator for pretty intense suffering (disabling and maybe even excruciating according to WFP) conditional on sentience, so Iād probably give animals without it much narrower welfare ranges.
PTSD-like behavior could be another, but Iād give it less weight, since it seems more likely to be biased either way.
Thanks for your reply. I agree with much of what you write. Below are some disagreements.
This seems to be framing consciousness as a binary, a yes/āno. That sounds wrong; many people view it as a sliding scale, and some of your links talk about āmore valenced consciousnessā etc.
In any event, I understood the 14 bees = 1 human to be after accounting for the low chance of bee sentience. Did I misunderstand? The summary figure lists various disclaimers, but it notably does NOT say āconditioned on sentienceā.
One could write equally convincing arguments against ādo juveniles roll a ballā as a proxy. Neuron counts are bad and have many flaws; ādo they roll a ballā is WORSE and has MORE flaws. That remains the case if you add 100 other subjective proxies, all wishy-washy things, all published by bee researchers eager to tell you bees are amazing.
It remains the case that neuron counts are more objective than any of the other proxies. It also is the case that NOT using neuron counts is a guarantee of not getting tiny estimates: thereās no clear way to combine 100 yes/āno proxies and get an answer like āone-millionth of a humanā. Only with neuron counts can you get this. I could tell you that even before looking at your results: your methodology eliminates a whole range of answers a priori.
(Also, the argument that bees are amazing is used in Shriverās post, which makes this discussion circular: he doesnāt want to use neuron counts because it underestimates bees (according to intuition, I guess).)
Compare: if each server on the internet is connected to only 10 other servers on average, does it hold that each user of the internet can only reach a constant number of websites?
No: the graph is an expander, and if there are n nodes, the distance between any two nodes may be as little as O(log n), even if the degree of each node is constant. Hence, via a few hops on the graph, a node may talk to many other nodes (potentially even all of them).
Neural networks (whether artificial or natural) can certainly cause interaction between far away neurons, and the O(log n) distance does not necessarily mean the signal dies. This is similar to how my words reach you despite the packets passing through many servers along the way.
I donāt know for sure that this is how the brain works. However, I find it plausible. I also note that the human brain achieves an incredible amount of intelligence, so certain impressive interactions between neurons are definitely taking place.
I definitely do think welfare ranges can vary across beings, so Iām not thinking in binary terms.
~14 bees to 1 human is indeed after adjusting for the probability of sentience.
Neuron counts are plausibly worse than all of the other proxies precisely because of how large the gaps in welfare range they imply are. The justifications could be bad for most or all proxies, and maybe even worse for others than neuron counts (although I do think some of the proxies are far more justified), but neuron counts could introduce the most bias the way theyāre likely to be used. Whether or not they have a heart or literally no proxies at all would give more plausible ranges than neuron counts, conditional on sentience (having a nonzero welfare range at all).
The kinds of proxies for the functions of valence and how they vary with hedonic intensity Iād use would probably give results more similar to any of the non-neuron count models than to the neuron count model (or models with larger gaps). A decent approximation (a lower bound) of the expected welfare range ratio over humans would be the probability that the animal has states of similar hedonic intensity to the most intense in humans, based on behavioural markers of intensity and whether they have the right kinds of cognitive mechanisms. And I canāt imagine assigning tiny probabilities to that, conditional on sentience, based on current evidence (which is mostly missing either way). For bees, they had an estimated 42.5% probability of sentience in this report, so a 16.7% chance of having similarly intense hedonic states conditional on sentience would give you 14 bees per human. I wouldnāt go lower than 1% or higher than 80% based on current evidence, so 16.7% wouldnāt be that badly off. (This is all assuming the expected number of conscious/āvalenced systems in any brain is close to 1 or lower, or their correlation is very low or we can ignore that possibility for other reasons.)
Wrt packets sent along servers, servers are designed to be very reliable, have buffers in case of multiple or large packets received within a short period, and so on. Iād guess neural signals would compete much more with each other, and at each neuron they reach have a non-tiny chance of not being passed along, so you get decaying signal strength. Many things donāt make it to your conscious awareness. On the other side, there may be multiple similar signals through multiple paths in a brain, but that means more competition between distinct signals, too. Similar signals being sent across multiple paths may also be in part because of more neurons directly connected to periphery firing, not just few neurons influencing a superlinear number of neurons each on average.
If Iām reading this right, you are dismissing neuron counts because of your intuition. You correctly realize that intuitions trump all other considerations, and the game is just to pick proxies that agree with your intuitions and allow you to make them more systematic.
I agree with this approach but strongly disagree with your intuitions. ā14 bees = 1 human, after adjusting for probability of sentienceā is so CLEARLY wrong that it is almost insulting. Thatās my intuition speaking. Iām doing the same thing youāre doing when you dismiss neuron counts, just with a different starting intuition than you.
I think it would be better if the OP was more upfront about this bias.
Thatās not what I meant.
Iām not dismissing neuron counts because of my direct intuitions about welfare ranges across species. That would be circular, motivated reasoning and an exercise in curve fitting. Iām dismissing them because the basis for their use seems weak, for reasons explained in posts RP has written and my own (vague) understanding of what plausibly determines welfare ranges in functionalist terms. When RP started this project and for most of the time I spent working on the conscious subsystems report, I actually thought we should use neuron counts by default. I didnāt change my mind about neuron counts because my direct intuitions about relative welfare ranges between specific species changed; I changed my mind because of the arguments against neuron counts.
What I meant in what you quoted is that neuron counts seem especially biased, where the biases are measured relative to the results of quantitative models roughly capturing my current understanding of how consciousness and welfare ranges actually work, like the one I described in the comment you quoted from. Narrow range proxies give less biased results (relative to my modelsā results) than neuron counts, including such proxies with little or no plausible connection to welfare ranges. But Iād just try to build my actual model directly.
How exactly are you thinking neuron counts contribute to hedonic welfare ranges, and how does this relate to your views on consciousness? What theories of consciousness seem closest to your views?
Why do you think 14 bees per human is so implausible?
(All this being said, the conscious subsystems hypothesis might still support the use of neuron counts as a proxy for expected welfare ranges, even if the hypothesis seems very unlikely to me. Iām not sure how unlikely; I have deep uncertainty.)
Some thoughts against superlinear scaling in particular relative to sublinear scaling not covered directly in those two posts:
If we count multiple conscious subsystems in a brain even allowing substantial overlap between multiple of them to get to superlinear scaling (thatās substantially faster than linear scaling), that seems likely to imply ādouble countingā valenced experiences, and my guess is that this would get badly out of hand, e.g. in exponential territory, which would also have counterintuitive implications. I discuss this here.
Humans donāt seem to have many times more synapses per neuron than bees (1,000 to 7,000 in human brains vs ~1,000 in honeybee brains, based on data in [1] and [2]), so the number of direct connections between neurons is close-ish to proportional with neuron counts between humans and bees. We could have many times more indirect connections per neuron through paths of connections, but the influence from one neuron on another itās only indirectly connected to should decrease with the lengths of paths from the first to the second, because the signal has to make it farther and compete with more signals. This doesnāt rule out superlinear scaling, but can limit it.
A brain duplication thought experiment here.
Multiple other arguments here.