I’m doing a PhD on behavioural markers of consciousness in radically other minds, with a focus on non-human animals, at the intersection of philosophy, animal behaviour, psychology and neuroscience, financed via a scholarship I won for it that allowed me considerable independence, and enabled me to shift my location as visiting researcher between different countries. I also have a university side job supervising Bachelor theses on AI topics, mostly related to AI sentience and LLMs. And I’m currently in the last round to be hired at Sentience Institute.
The motivation for my thesis was a combination of an intense theoretical interest in consciousness (I find it an incredibly fascinating topic, and I have a practical interest in uploading), and animal rights concerns. I was particularly interested in scenarios where you want to ascertain whether someone you are interacting with is sentient (and hence deserves moral protection), but you cannot establish reliable two-way communication on the matter, and their mental substrate is opaque to you (because it is radically different from yours, and because precise analysis is invasive, and hence morally dubious).People tend to only focus on damaged humans for these scenarios, but the one most important to me was non-human animals, especially ones that evolved on independent lines (e.g. octopodes). Conventional wisdom holds that in those scenarios, there is nothing to do or know, yet ideas I was encountering in different fields suggested otherwise, and I wanted to draw together findings in an interdisciplinary way, translating between them, connecting them. The core of my resulting understanding is that consciousness is a functional trait that is deeply entwined with rationality—another topic I care deeply about.
The research I am currently embarking on (still at the very beginning!) is exploring what implications this might have for AGI. We have a similar scenario to the above, in that the substrate is opaque to us, and two-way-communication is not trustworthy. But learning from behaviour becomes a far more fine-grained and in-depth affair. The strong link between rationality and consciousness in biological life is essentially empirically established; if you disrupt consciousness, you disrupt rationality; when animals evolve rationality, they evolve consciousness en route; etc. But all of these lifeforms have a lot in common, and we do not know how much of that is random and irrelevant for the result, and how much might be crucial. So we don’t know if consciousness is inherently implied by rationality, or just one way to get there that was, for whatever reason, the option biology keeps choosing.
One point I have mentioned here a lot is that evolution entails constraints that are only partially mimicked in the development of artificial neural nets; very tight energy constraints, and the need to boot-strap a system without external adjustments or supervision from step 0. Brains are insanely efficient, and insanely recursive, and the two are likely related—a brain only has so many layers, and is fully self-organising from day 1, so recursive processing is necessary—and recursive processing in turn is likely related to consciousness (not just because it feels intuitively neat, but again, because we see a strong correlation). It looks very much like AI is cracking problems biological minds could not crack without being conscious—but to do so, we are dumping in insane amount of energy and data and guidance, which biological agents would never have been able to access, so we might be bruteforcing a grossly inefficient solution biological agents could never access, and we are explicitly not allowing/enabling these AIs to use paths biology definitely used (namely the whole idea of offline processing). But as these systems become more biologically inspired and efficient (the two are likely related, and there is massive industry pressure for both), will we go down the same route, and how would that manifest when we already reached and exceeded capabilities that would act as consciousness markers in animals? I am not at all sure yet.
And this is all not aided by the fact that machine learning and biology often use the same terms, but mean different things, e.g. in the recurrent processing example; and then figuring out whether these differences make a functional difference is another matter. We are still asking “But what are they doing?”, but have to ask the question far more precisely than before, because we cannot take as much for granted, and I worry that we will run into the same opaque wall but have less certainty to navigate around it. But then, I was also deeply unsure when I started out on animals, and hope learning more and clarifying more will narrow down a path.
We also have a partial link of how these functionalities are linked, but they all still contain significant handwaving gaps; the connections are the kind where you go “Hm, I guess I can see that”, but far from a clear and precise proof. E.g. connecting different bits of information for processing has obvious planning advantages, but also plausibly helps to lead to unified perception. Circulating information so it is retained for a while and can be retrieved across a task has obvious benefits in solving tasks with short term memory, but also plausibly helps to lead to awareness. Adding highly negative valence to some stimuli and concepts that cannot be easily overridden plausibly keeps the more free-spinning parts of the brain on task and from accidental self-destruction in hyperfocus—but it also plausibly helps lead to pain. Looping information is obviously useful for a bunch of processing functions leading to better performance, but also seems inherently referential. Making predictions about our own movements and developments in our environment and noting when they do not check out is crucial to body coordination and to recognise novel threats and opportunities, but also plausibly related to surprise. But again—plausibly related; there is clearly something still missing here.
I haven’t read the the whole thread, not sure if t was already covered, but I’d be interested in hearing more about what you work on.
I’m doing a PhD on behavioural markers of consciousness in radically other minds, with a focus on non-human animals, at the intersection of philosophy, animal behaviour, psychology and neuroscience, financed via a scholarship I won for it that allowed me considerable independence, and enabled me to shift my location as visiting researcher between different countries. I also have a university side job supervising Bachelor theses on AI topics, mostly related to AI sentience and LLMs. And I’m currently in the last round to be hired at Sentience Institute.
The motivation for my thesis was a combination of an intense theoretical interest in consciousness (I find it an incredibly fascinating topic, and I have a practical interest in uploading), and animal rights concerns. I was particularly interested in scenarios where you want to ascertain whether someone you are interacting with is sentient (and hence deserves moral protection), but you cannot establish reliable two-way communication on the matter, and their mental substrate is opaque to you (because it is radically different from yours, and because precise analysis is invasive, and hence morally dubious).People tend to only focus on damaged humans for these scenarios, but the one most important to me was non-human animals, especially ones that evolved on independent lines (e.g. octopodes). Conventional wisdom holds that in those scenarios, there is nothing to do or know, yet ideas I was encountering in different fields suggested otherwise, and I wanted to draw together findings in an interdisciplinary way, translating between them, connecting them. The core of my resulting understanding is that consciousness is a functional trait that is deeply entwined with rationality—another topic I care deeply about.
The research I am currently embarking on (still at the very beginning!) is exploring what implications this might have for AGI. We have a similar scenario to the above, in that the substrate is opaque to us, and two-way-communication is not trustworthy. But learning from behaviour becomes a far more fine-grained and in-depth affair. The strong link between rationality and consciousness in biological life is essentially empirically established; if you disrupt consciousness, you disrupt rationality; when animals evolve rationality, they evolve consciousness en route; etc. But all of these lifeforms have a lot in common, and we do not know how much of that is random and irrelevant for the result, and how much might be crucial. So we don’t know if consciousness is inherently implied by rationality, or just one way to get there that was, for whatever reason, the option biology keeps choosing.
One point I have mentioned here a lot is that evolution entails constraints that are only partially mimicked in the development of artificial neural nets; very tight energy constraints, and the need to boot-strap a system without external adjustments or supervision from step 0. Brains are insanely efficient, and insanely recursive, and the two are likely related—a brain only has so many layers, and is fully self-organising from day 1, so recursive processing is necessary—and recursive processing in turn is likely related to consciousness (not just because it feels intuitively neat, but again, because we see a strong correlation). It looks very much like AI is cracking problems biological minds could not crack without being conscious—but to do so, we are dumping in insane amount of energy and data and guidance, which biological agents would never have been able to access, so we might be bruteforcing a grossly inefficient solution biological agents could never access, and we are explicitly not allowing/enabling these AIs to use paths biology definitely used (namely the whole idea of offline processing). But as these systems become more biologically inspired and efficient (the two are likely related, and there is massive industry pressure for both), will we go down the same route, and how would that manifest when we already reached and exceeded capabilities that would act as consciousness markers in animals? I am not at all sure yet.
And this is all not aided by the fact that machine learning and biology often use the same terms, but mean different things, e.g. in the recurrent processing example; and then figuring out whether these differences make a functional difference is another matter. We are still asking “But what are they doing?”, but have to ask the question far more precisely than before, because we cannot take as much for granted, and I worry that we will run into the same opaque wall but have less certainty to navigate around it. But then, I was also deeply unsure when I started out on animals, and hope learning more and clarifying more will narrow down a path.
We also have a partial link of how these functionalities are linked, but they all still contain significant handwaving gaps; the connections are the kind where you go “Hm, I guess I can see that”, but far from a clear and precise proof. E.g. connecting different bits of information for processing has obvious planning advantages, but also plausibly helps to lead to unified perception. Circulating information so it is retained for a while and can be retrieved across a task has obvious benefits in solving tasks with short term memory, but also plausibly helps to lead to awareness. Adding highly negative valence to some stimuli and concepts that cannot be easily overridden plausibly keeps the more free-spinning parts of the brain on task and from accidental self-destruction in hyperfocus—but it also plausibly helps lead to pain. Looping information is obviously useful for a bunch of processing functions leading to better performance, but also seems inherently referential. Making predictions about our own movements and developments in our environment and noting when they do not check out is crucial to body coordination and to recognise novel threats and opportunities, but also plausibly related to surprise. But again—plausibly related; there is clearly something still missing here.