I’ve always found the functionalist view more intuitively compelling. The idea that experiential intensity simply scales down with the number of neurons seems hard to accept: it implies that simpler organisms live something like a barely-there flicker of experience, which also places us humans at the apex of perceived intensity in the universe. That seems to me like a sort of anthropocentrism, which could be a little suspicious.
I also think there’s a distinction worth drawing between the “dimensionality” of an experience (how many qualitative states a mind can occupy) and its intensity. A simple mind might have very few “keys,” but still hit each of them hard. A shrimp might have a very narrow experiential range, with little going on beyond basic valenced states, but that needn’t make those states less intense. If that’s right, “simpler brain” doesn’t automatically mean “smaller welfare range.”
The idea that experiential intensity simply scales down with the number of neurons seems hard to accept: it implies that simpler organisms live something like a barely-there flicker of experience, which also places us humans at the apex of perceived intensity in the universe.
Very simple organisms could still matter a lot despite having much less intense experiences. I estimatefarmed animals and soil invertebrateshave 1.87 and 253 times as many neurons as humans. The graph below has more detail. Nematodes are the animals with the least neurons, with an adult caenorhabditis elegans having 302 neurons, but I estimate soil nematodes have 169 times as many neurons in total as humans.
humans at the apex of perceived intensity in the universe
There are animals with more neurons than humans. Short-finned pilot whales and african elephants have 128 billion and 257 billion neurons, 1.49 (= 128⁄86) and 2.99 (= 257⁄86) times as many as humans.
I also think there’s a distinction worth drawing between the “dimensionality” of an experience (how many qualitative states a mind can occupy) and its intensity. A simple mind might have very few “keys,” but still hit each of them hard.
Very simple organisms could still matter a lot despite having much less intense experiences.
I agree, assuming they are conscious.
I think the case of elephants and whales actually highlights why using total neuron count as a proxy for welfare range can be a little tricky. If we look at the African elephant’s 257 billion neurons, it’s a staggering number. But most of those neurons are located in the cerebellum, primarily dedicated to motor control of their large bodies. This suggests that neuron count alone is too crude a metric (though perhaps useful when comparing organisms with very different brains). Parameters like encephalization quotient or cortical neuron density might do better, though I’m not sure any of them cleanly captures intensity of experience rather than cognitive complexity. That said, these would be really only meaningful for vertebrates, which perhaps just underlines how hard the welfare range question actually is for organisms very different from us.
This suggests that neuron count alone is too crude a metric (though perhaps useful when comparing organisms with very different brains).
I like to compare the sentience-adjusted welfare ranges (probability of sentience times the welfare range conditional on sentience) of organisms with neurons assuming they are proportional to “individual number of neurons”^”exponent”. I consider exponents from 0 to 2 reasonable best guesses. An exponent of 0.188 explains very well the sentience-adjusted welfare ranges presented in Bob’s book (which rely on much more than the individual number of neurons). Below is a graph illustrating this.
For comparisons involving organisms with and without neurons, I would assume sentience-adjusted welfare ranges proportional to “individual mass”^”exponent”, or “metabolic rate”^”exponent”. I do not think the specific proxy matters that much. In allometry, “the study of the relationship of body size to shape,[1]anatomy, physiology and behaviour”, “The relationship between the two measured quantities is often expressed as a power law equation (allometric equation)”. If the sentience-adjusted welfare range is proportional to “proxy 1“^”exponent 1”, and “proxy 1” is proportional to “proxy 2“^”exponent 2”, the sentience-adjusted welfare range is proportional to “proxy 1”^(“exponent 1“*”exponent 2”). So the results for “proxy 1” and exponent “exponent 1“*”exponent 2” are the same as those for “proxy 2” and “exponent 2″.
I’ve always found the functionalist view more intuitively compelling. The idea that experiential intensity simply scales down with the number of neurons seems hard to accept: it implies that simpler organisms live something like a barely-there flicker of experience, which also places us humans at the apex of perceived intensity in the universe. That seems to me like a sort of anthropocentrism, which could be a little suspicious.
I also think there’s a distinction worth drawing between the “dimensionality” of an experience (how many qualitative states a mind can occupy) and its intensity. A simple mind might have very few “keys,” but still hit each of them hard. A shrimp might have a very narrow experiential range, with little going on beyond basic valenced states, but that needn’t make those states less intense. If that’s right, “simpler brain” doesn’t automatically mean “smaller welfare range.”
Hi Riccardo.
Very simple organisms could still matter a lot despite having much less intense experiences. I estimate farmed animals and soil invertebrates have 1.87 and 253 times as many neurons as humans. The graph below has more detail. Nematodes are the animals with the least neurons, with an adult caenorhabditis elegans having 302 neurons, but I estimate soil nematodes have 169 times as many neurons in total as humans.
There are animals with more neurons than humans. Short-finned pilot whales and african elephants have 128 billion and 257 billion neurons, 1.49 (= 128⁄86) and 2.99 (= 257⁄86) times as many as humans.
I agree.
Hi Vasco, thanks for the useful data!
I agree, assuming they are conscious.
I think the case of elephants and whales actually highlights why using total neuron count as a proxy for welfare range can be a little tricky. If we look at the African elephant’s 257 billion neurons, it’s a staggering number. But most of those neurons are located in the cerebellum, primarily dedicated to motor control of their large bodies. This suggests that neuron count alone is too crude a metric (though perhaps useful when comparing organisms with very different brains). Parameters like encephalization quotient or cortical neuron density might do better, though I’m not sure any of them cleanly captures intensity of experience rather than cognitive complexity. That said, these would be really only meaningful for vertebrates, which perhaps just underlines how hard the welfare range question actually is for organisms very different from us.
You may be interested in these posts:
What If We Assumed That All Animals Are Conscious?.
The Conscious Nematode: Exploring Hallmarks of Minimal Phenomenal Consciousness in Caenorhabditis Elegans.
I like to compare the sentience-adjusted welfare ranges (probability of sentience times the welfare range conditional on sentience) of organisms with neurons assuming they are proportional to “individual number of neurons”^”exponent”. I consider exponents from 0 to 2 reasonable best guesses. An exponent of 0.188 explains very well the sentience-adjusted welfare ranges presented in Bob’s book (which rely on much more than the individual number of neurons). Below is a graph illustrating this.
For comparisons involving organisms with and without neurons, I would assume sentience-adjusted welfare ranges proportional to “individual mass”^”exponent”, or “metabolic rate”^”exponent”. I do not think the specific proxy matters that much. In allometry, “the study of the relationship of body size to shape,[1] anatomy, physiology and behaviour”, “The relationship between the two measured quantities is often expressed as a power law equation (allometric equation)”. If the sentience-adjusted welfare range is proportional to “proxy 1“^”exponent 1”, and “proxy 1” is proportional to “proxy 2“^”exponent 2”, the sentience-adjusted welfare range is proportional to “proxy 1”^(“exponent 1“*”exponent 2”). So the results for “proxy 1” and exponent “exponent 1“*”exponent 2” are the same as those for “proxy 2” and “exponent 2″.
Thanks for the detailed response and the links!
The exponent-based approach is interesting, though I’m still a little uncertain about its validity. I’ll check out the posts!
Here is some more context about the exponent-based approach.