A common complaint: LLMs have no concept of truth and therefore none of honesty or dishonesty. I think this is a peculiar kind of red herring. It seems to assume that humans have access to actual things in the world and therefore we have direct access to truths about the world (not just a concept of truth or a belief in a true statement) and that our experience is somehow more than mere information, whereas LLM information is mere letters and spaces.
Of course AIs, behaviorally, can be honest or dishonest. I think we've all had the experience of calling out an AI's mistake, and its response is recognition that it was wrong -- that what it said was untrue -- along with effusive apologies. The AI skeptic says, the AI doesn't mean what it says, since it merely produces strings of letters and spaces.
That response misses two points, one about AIs and one about humans. AIs don't merely choose the next word based on a probability in the internet literature. The AI has already weighted every word -- possibly multiple weighted versions of each word associated with distinct contexts in which it occurs -- and placed it in a multidimensional vector space along with all the other words, relative to each other, with distances between each and spatial directions. In other words, the AI is modeling a world based on its vast text training set. Those weights + locations relative to other weighted words are meanings that are not merely letters. They could, for example, be used by a physical robot to manipulate the actual world of things in space and time. So they are meanings very much as human language meanings.
That's one missed point. The other missed point is that human word learning does much the same. The only difference is that humans learn their meanings often from their interactions with the spatio-temporal world. In both cases -- humans and AI -- the intelligence is modeling the symbols by means of information from a source, either text or sense-based information.
But information is always only information. Humans don't have a privileged analog access to truth or to the world of phenomena. The humans don't have analog objects in the skull or in their brains. The brain interprets the sense data as information that it models the world with. Just as an LLM does with text.
The exception for humans is, of course, our inner world of sensations, feelings, moods, emotions -- all of the constituents of consciousness. This has been well understood and accepted as pretty much obvious since Kant's first critique, which is why his name has survived, and Descartes before him, and a host of ancient South Asian philosophers as well. Those constituents of consciousness and consciousness itself -- those, we have special access. It's not even analog; it's immediate. The sensation of the color of a green leaf is the color, not an analog of the color of the leaf. Leaves don't have colors. They reflect light frequencies which we interpret as color. This immediate access might lead one to think that we have access to all of the physical world, as if our mind's interpretation of the world were the actual world, what Kant called the noumenal world of things-in-themselves. That's just a mistake.
To be clear: we don't have special access to the frequencies; they come to us the way strings of text come to an LLM's neutral network. What we have special access to is the sensation of color. It would be a mistake to assume that because we have access to our awareness that we therefore have direct access to the rest of the physical world of phenomena. Our world outside the inner sensations is an interpretation constructed of sensory responses to our interaction with the world. It's not the world as it is. The world we see is our mind's interpretation -- the phenomenal world you see is your mind -- that worlds is your mind responding to the pressures of a real world that you can only access through that interpretation.
How is this, as a source of truth or knowledge different from LLM information? If anything, the LLM has a more direct informational access since it doesn't have the sensory interpretation. For an AI, color talk is just more information about humans. It's the words humans use to talk about their reception of light frequencies. Humans give the frequencies names, and then they talk about the names.
For sure there are distinctions in purpose and focus between AI modeling and humans modeling. Humans have evolved to survive with emotions and drives and fear of dangers, while the AI is not engineered to survive and replicate, so it doesn't learn through evolved emotions, drives and fears of danger. AI expressions of emotions have meaning, but the AI doesn't feel those emotions, whereas humans do have emotions which are not only real but influence its thinking and acting. Notice also that human language has no means to accurately describe the one aspect of experience that we have direct access to immediately -- our sensations (qualia in the philosophy of mind discourse) -- aside from naming them. We have a name for the color green, but can you describe what green looks like? Like a leaf. Okay, what does that color look like? Green. That's where words fail us, just where our access is immediate! That seems to me to be the clear evidence that the AI skeptic has missed the point that most of human language use is mediated by information just as AI is. That is, human and AI meanings of words are on all fours with each other. The difference arises only when it comes to the true immediate organic human traits that AIs don't have, and that human language ironically fails to describe.
Another difference: humans think with tenacious biases; AI bias toward the norm, the frequent, is not tenacious -- a good prompt and it will abandon its initial "perspective". It is not emotionally committed.
[For more on these differences and similarities: Yoneda learning, wikichip, complexity and AI, AI myths of human intelligence, the hierarchy of data, why AIs are not conscious and are not likely ever to be, AI introspection, limits of language, qualia and noumena]
No comments:
Post a Comment