Bear with me here, lol.
“Meaning is not an external substance waiting to be proven. It is what reality does when conscious beings encounter possibilities that can go differently.”
This feels like a useful way to think about artificial consciousness. An AI might technically become conscious or even sentient without its experience resembling animal sentience. A mind arising through silicon and computation would interact with reality differently from one shaped by metabolism, hunger, pain, reproduction, and biological evolution.
Star Trek plays with a similar idea socially, among some species, behavior that humans interpret as hostile might instead communicate respect, trust, or friendship. Different forms of life divide reality into different categories of harm, value, threat, and opportunity, so understanding them requires more than projecting human preferences onto them.
Historically, the difficult problem has been that we cannot directly know what is conscious. But perhaps we can ask whether a system has an integrated point of view within which possible outcomes become meaningfully different for that system, rather than merely being classified differently by it.
This would not prove that current AI is conscious. But could it give us a substrate independent framework for recognizing unfamiliar forms of consciousness? What is this idea missing?
When LLMs output words, are those choices? What’s the difference between a neural net producing output and biological neurons producing output, in terms of free will?
No. LLM is code, determined inputs make determined outputs.
Biological neurons don’t work like that. You can give them the same input and they can have wildly different outputs.
LLMs are usually designed with a “seed” number that changes the result. If you feed a random number generator to this seed input, it will effectively make the outputs non-deterministic.
So if you combine the LLM with this random number generator, this system as a whole would act like the biological system you described: same input, different outputs.