Hi Carl, thanks for your thoughts & time. I appreciate the comments.
First, to be clear, the hypothesis is that the symmetry of the mathematical object isomorphic to a conscious experience corresponds to valence. This is distinct from (although related to) the symmetry of a stimulus, or even symmetry within brain networks.
This does not look like a metric that is tightly connected to sensory, cognitive, or behavioral features. In particular, it is not specifically connected to liking, wanting, aversion, and so forth. So, like IIT in the cases discussed by Scott Aaronson, it would seem likely to assign huge values (of valence rather than consciousness, in this case) to systems that lack the corresponding functions, and very low values to systems that possess them.
I strongly disagree with this in the case of humans, fairly strongly disagree in the more general case of evolved systems, and mildly disagree in the fully general case of arbitrary systems.
First, it seems extremely like to me that evolved organisms would use symmetry as an organizational principle / attractor (Section XII);
Second, in cases where we do have some relevant data or plausible models (I.e., as noted in Sections IX and XII), the symmetry hypothesis seems plausible. I think the hypothesis does really well when one actually looks at the object-level, particularly e.g., Safron’s model of orgasm & Seth and Friston’s model of interoception;
Third, with respect to extending Aaronson’s critique, I question whether “this seems to give weird results when put in novel contexts” is a good path to take. As Eric Schwitzgebel notes, “Common sense is incoherent in matters of metaphysics. There’s no way to develop an ambitious, broad-ranging, self- consistent metaphysical system without doing serious violence to common sense somewhere. It’s just impossible. Since common sense is an inconsistent system, you can’t respect it all. Every metaphysician will have to violate it somewhere.” This seems particularly true in the realm of consciousness, and particularly true in contexts where there was no evolutionary benefit in having correct intuitions.
As such it seems important not to enshrine common sense, with all its inconsistencies, as the gold standard with regard to valence research. In general, I’d say a good sign of a terrible model of consciousness would be that it validates all of our common-sense intuitions about the topic.
The falsifiable predictions are mostly claims that the computational functions will be (imperfectly) correlated with symmetry, but the treatment of boredom appears to allow that these will be quite imperfect:
Section XI is intended as the core set of falsifiable predictions—you may be thinking of the ‘implications for neuroscience’ discussion in Section XII, some of which could be extended to become falsifiable predictions.
Overall, this seems systematically analogous to IIT in its flaws. If one wanted to pursue an analogy to Aaronson’s discussion of trivial expander graphs producing extreme super-consciousness, one could create an RL agent (perhaps in an artificial environment where it has the power to smile, seek out rewards, avoid injuries (which trigger negative reward), favor injured limbs, and consume painkillers (which stop injuries from generating negative reward) whose symmetry could be measured in whatever way the author would like to specify.
I think we can say now that we could program the agent in such a way that it sought out things that resulted in either more or less symmetric states, or was neutral to such things. Likewise, switching the signs of rewards would not reliably switch the associated symmetry. And its symmetry could be directly and greatly altered without systematic matching behavioral changes.
I would like to know whether the theory in PQ is supposed to predict that such agents couldn’t be built without extraordinary efforts, or that they would have systematic mismatch of their functional beliefs and behavior regarding qualia with actual qualia.
I’d assert- very strongly- that one could not evolve such a suffering-seeking agent without extraordinary effort, and that if one was to attempt to build one from scratch, it would be orders of magnitude more difficult to do so than making a “normal” agent. (This follows from my reasoning in Section XII.) But let’s keep in mind that whether the agent you’re speaking of is a computational program or a physical system matters a lot—under my model, a RL agent running on a standard Von Neumann physical architecture probably has small & merely fragmentary qualia.
An analogy here would be the orthogonality thesis: perhaps we can call this “valence orthogonality”: the behavior of a system, and its valence, are usually tightly linked via evolutionary processes and optimization factors, but they are not directly causally coupled, just as intelligence & goals are not causally coupled.
This hypothesis does also have implications for the qualia of whole-brain emulations, which perhaps is closer to your thought-experiment.
Hi Carl, thanks for your thoughts & time. I appreciate the comments.
First, to be clear, the hypothesis is that the symmetry of the mathematical object isomorphic to a conscious experience corresponds to valence. This is distinct from (although related to) the symmetry of a stimulus, or even symmetry within brain networks.
I strongly disagree with this in the case of humans, fairly strongly disagree in the more general case of evolved systems, and mildly disagree in the fully general case of arbitrary systems.
First, it seems extremely like to me that evolved organisms would use symmetry as an organizational principle / attractor (Section XII);
Second, in cases where we do have some relevant data or plausible models (I.e., as noted in Sections IX and XII), the symmetry hypothesis seems plausible. I think the hypothesis does really well when one actually looks at the object-level, particularly e.g., Safron’s model of orgasm & Seth and Friston’s model of interoception;
Third, with respect to extending Aaronson’s critique, I question whether “this seems to give weird results when put in novel contexts” is a good path to take. As Eric Schwitzgebel notes, “Common sense is incoherent in matters of metaphysics. There’s no way to develop an ambitious, broad-ranging, self- consistent metaphysical system without doing serious violence to common sense somewhere. It’s just impossible. Since common sense is an inconsistent system, you can’t respect it all. Every metaphysician will have to violate it somewhere.” This seems particularly true in the realm of consciousness, and particularly true in contexts where there was no evolutionary benefit in having correct intuitions.
As such it seems important not to enshrine common sense, with all its inconsistencies, as the gold standard with regard to valence research. In general, I’d say a good sign of a terrible model of consciousness would be that it validates all of our common-sense intuitions about the topic.
Section XI is intended as the core set of falsifiable predictions—you may be thinking of the ‘implications for neuroscience’ discussion in Section XII, some of which could be extended to become falsifiable predictions.
I’d assert- very strongly- that one could not evolve such a suffering-seeking agent without extraordinary effort, and that if one was to attempt to build one from scratch, it would be orders of magnitude more difficult to do so than making a “normal” agent. (This follows from my reasoning in Section XII.) But let’s keep in mind that whether the agent you’re speaking of is a computational program or a physical system matters a lot—under my model, a RL agent running on a standard Von Neumann physical architecture probably has small & merely fragmentary qualia.
An analogy here would be the orthogonality thesis: perhaps we can call this “valence orthogonality”: the behavior of a system, and its valence, are usually tightly linked via evolutionary processes and optimization factors, but they are not directly causally coupled, just as intelligence & goals are not causally coupled.
This hypothesis does also have implications for the qualia of whole-brain emulations, which perhaps is closer to your thought-experiment.