LLMs are likely not conscious

Sorry for the late response. I don't really use this forum regularly. But to get back to it - the main reason neural networks generalize is that they find the simplest function that gets a given accuracy on the training data.

This holds true for all neural networks, regardless of how they are trained, what type of data they are trained on, or what the objective function is. It's the whole point of why neural networks work. Functions that have more high frequency components are exponentially more unlikely. This holds for the randomly initialized prior (see arxiv.org/pdf/1907.10599) and throughout training, as the averaging part of SGD allows lower frequency components to be learned faster than higher frequency ones (see [1806.08734] On the Spectral Bias of Neural Networks).

You can have any objective function you want; it doesn't change this basic fact. If this basic fact didn't hold, the neural network wouldn't generalize and would be useless. There are many papers that formalize this and provide generalization bounds based off of the complexity of the function learned by the neural network.

A "conscious" neural network doesn't increase the accuracy over a neural network encoding the same function sans consciousness but does increase the complexity of the function. Therefore, it's exponentially more unlikely.

I think biological systems are really different from silicon ones. The biggest difference is that biological systems are able to generate their own randomness. Silicon ones are not - they're deterministic. If a NN is probabilistic, it's because we are feeding it random samples as an input. I think consciousness is a precursor for free will, which can be valuable for inherently non-deterministic biological systems.

In my original post, I had linked a recent paper that finds suggestive evidence that the brain is non-classical (e.g. undergoes quantum computation) but deleted it after someone told me to.

More generally, I feel that for folks concerned about AI safety, the first step is to develop a solid theoretical understanding of why neural networks generalize, the types of functions they are biased towards, how this bias is affected by the # of layers, etc.  

I feel that most individuals on Less Wrong lack this knowledge because they exclusively consume content from individuals within the rationality/AI safety sphere. I think this leads to a lot of outlandish conjectures (e.g. AI conscious, paperclip maximizer, etc.) that don't make sense. 

Since consciousness seems useful for all these different species, in a convergent-evolution pattern even across very different brain architectures (mammals vs birds), then I believe we should expect it to be useful in our homonid-simulator-trained model. If so, we should be able to measure this difference to a next-token-predictor trained on an equivalent number of tokens of a dataset of, for instance, math problems.

What do you mean by difference here? Increase in performance due to consciousness? Or differences in functions?

I'm not sure we could measure this difference. It seems very likely to me that consciousness evolved before, say, language and complex agency. But complex language and complex agency might not require consciousness, and may capture all of the benefits that would be captured by consciousness, so consciousness wouldn't result in greater performance.

However, it could be that

1. humans do not consistently have complex language and complex agency, and humans with agency are fallible as agents, so consciousness in most humans is still useful to us as a species (or to our genes),
2. building complex language and complex agency on top of consciousness is the locally cheapest way to build them, so consciousness would still be useful to us, or
3. we reached a local maximum in terms of genetic fitness, or evolutionary pressures are too weak on us now, and it's not really possible to evolve away consciousness while preserving complex language and complex agency. So consciousness isn't useful to us, but can't be practically gotten rid of without loss in fitness.

Some other possibilities:

1. The adaptive value of consciousness is really just to give us certain motivations, e.g. finding our internal processing mysterious, nonphysical or interesting makes it seem special to us, and this makes us
   1. value sensations for their own sake, so seek sensations and engage in sensory play, which may help us learn more about ourselves or the world (according to Nicholas Humphrey, as discussed here, here and here [EA · GW]),
   2. value our lives more and work harder to prevent early death, and/or
   3. develop spiritual or moral beliefs and adaptive associated practices,
2. Consciousness is just the illusion of the phenomenality of what's introspectively accessible to us. Furthermore, we might incorrectly believe in its phenomenality just because of the fact that much of the processing we have introspective access to is wired in and its causes are not introspectively accessible, but instead cognitively impenetrable. The full illusion could be a special case of humans incorrectly using supernatural explanations for unexplained but interesting and subjectively important or profound phenomena.