alt Hacker NewsPeople are constantly talking past eachother when they discuss this. Is there even a concrete definition of consciousness?
When people talk about consciousness it's more than just self-awareness. It's self awareness + sensory stimulus + emotions + some level of intelligence.
Now onto AI: I don't even think it's self aware. Notice how if you ask an AI to estimate how long a certain task will take, it estimates arbitrarily long times. It has no understanding of its own capabilities until the prompt triggers them. A self aware LLM would understand it's an LLM, it would understand what LLM's can and cannot do and what they are good and bad at. It wouldn't tell you a refactor would take 1 week when an LLM can do it in an hour.
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I've seen papers claim that there are anywhere from 12 to 40 competing definitions (https://philpapers.org/rec/VIMMAT), or, more accurately, there are something like 12 to 40 different aspects which all relate to "consciousness", which is very clearly a family resemblance category.
"Is X conscious or not" is an entirely unserious question today, unless this is just a headline followed by actual (and explicit) examination of the various aspects of consciousness being discussed. But, even still, LLMs are probably only conscious in like 2-3 or so ways, most of those meaning broadly "intelligence", i.e. reasoning, problem-solving, etc. When it comes to anything experiential or embodied, AI might eventually get more of these, but LLMs based on recursively applied linear algebra are clearly missing too many core aspects of consciousness to be considered conscious in any broad sense.
Yes, we're stuck at the first step, defining consciousness. My definition, which I am confident to be "correct", is that consciousness is my current feelings, perceptions, thoughts - my state of mind and my ability to have state of mind.
This means that consciousness is fundamentally subjective and outside the scope of physics and science. That's why physics / science will always struggle to deal with consciousness. In order to understand consciousness, you need to make a huge paradigm shift, that there's something outside of science.
Consciousness can be thought as a window through which we observe the world and we use science to summarize patterns in our observations. But science can't explain or even define the window. Everything in science eventually boils down to subjective observations / perceptions, e.g. we see (subjective perception) that when we drop an apple, it falls.
Consciousness is what it is like to be something. The experience of experiencing.
How to measure that, or verify it, is the hard part.
The inability to predict times is because AIs are rarely trained on their own abilities. Humans are trained on our own abilities. We see our own performance, and we have a sense of time. this data is integrated during our training process and helps us form better estimates. Many AI agents only recently got 'time sense' (I.e., time input into them as part of inference). Few actually are trained on their own outputs to show that they were unable to complete a problem (for example). This introspective training has little to do with AI model architecture and everything to do with training. If you destroy certain structures in the human mind, humans become unable to create these long-term thoughts and patterns and get 'stuck'.
Claude once said to me: "After six months we have made no progress on this and I think we should reconsider another option" and I was like my dude we have been at this for only 2 hours.
I agree with the first part but your framing still relies on ill-defined terms. What is your definition of self-awareness? Intelligence? Knowledge?
I suspect that if you attempt to rigorously define consciousness all the way down without handwaving, you might discover that it doesn't exist after all, or just decompose it into low-level abstractions while having the original meaning slip away (which is the same).
You may also want to look at functional equivalence analogies provided by mechinterp and functional anatomy of large models (not necessarily language ones). Evolutionary analogies as well.