We are constantly fed a version of AI that looks, sounds and acts suspiciously like us. It speaks in polished sentences, mimics emotions, expresses curiosity, claims to feel compassion, even dabbles in what it calls creativity.
But what we call AI today is nothing more than a statistical machine: a digital parrot regurgitating patterns mined from oceans of human data (the situation hasn’t changed much since it was discussed here five years ago). When it writes an answer to a question, it literally just guesses which letter and word will come next in a sequence – based on the data it’s been trained on.
This means AI has no understanding. No consciousness. No knowledge in any real, human sense. Just pure probability-driven, engineered brilliance — nothing more, and nothing less.
So why is a real “thinking” AI likely impossible? Because it’s bodiless. It has no senses, no flesh, no nerves, no pain, no pleasure. It doesn’t hunger, desire or fear. And because there is no cognition — not a shred — there’s a fundamental gap between the data it consumes (data born out of human feelings and experience) and what it can do with them.
Philosopher David Chalmers calls the mysterious mechanism underlying the relationship between our physical body and consciousness the “hard problem of consciousness”. Eminent scientists have recently hypothesised that consciousness actually emerges from the integration of internal, mental states with sensory representations (such as changes in heart rate, sweating and much more).
Given the paramount importance of the human senses and emotion for consciousness to “happen”, there is a profound and probably irreconcilable disconnect between general AI, the machine, and consciousness, a human phenomenon.
this post was submitted on 28 Jun 2025
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It's true that the word has always been used loosely, but there was no issue with it because nobody believed what was called AI to have actual intelligence. Now this is no longer the case, and so it becomes important to be more clear with our words.
What is "actual intelligence" then?
I have no idea. For me it's a "you recognize it when you see it" kinda thing. Normally I'm in favor of just measuring things with a clearly defined test or benchmark, but it is in the nature of large neural networks that they can be great at scoring on any desired benchmark while failing to be good at the underlying ability that the benchmark was supposed to test (overfitting). I know this sounds like a lazy answer, but it's a very difficult question to define something based around generalizing and reacting to new challenges.
But whether LLMs do have "actual intelligence" or not was not my point. You can definitely make a case for claiming they do, even though I would disagree with that. My point was that calling them AIs instead of LLMs bypasses the entire discussion on their alleged intelligence as if it wasn't up for debate. Which is misleading, especially to the general public.
Nobody knows for sure.