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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As someone who's had two kids since AI really vaulted onto the scene, I am enormously confused as to why people think AI isn't or, particularly, can't be sentient. I hate to be that guy who pretend to be the parenting expert online, but most of the people I know personally who take the non-sentient view on AI don't have kids. The other side usually does.
People love to tout this as some sort of smoking gun. That feels like a trap. Obviously, we can argue about the age children gain sentience, but my year and a half old daughter is building an LLM with pattern recognition, tests, feedback, hallucinations. My son is almost 5, and he was and is the same. He told me the other day that a petting zoo came to the school. He was adamant it happened that day. I know for a fact it happened the week before, but he insisted. He told me later that day his friend's dad was in jail for threatening her mom. That was true, but looked to me like another hallucination or more likely a misunderstanding.
And as funny as it would be to argue that they're both sapient, but not sentient, I don't think that's the case. I think you can make the case that without true volition, AI is sentient but not sapient. I'd love to talk to someone in the middle of the computer science and developmental psychology Venn diagram.
I'm a computer scientist that has a child and I don't think AI is sentient at all. Even before learning a language, children have their own personality and willpower which is something that I don't see in AI.
I left a well paid job in the AI industry because the mental gymnastics required to maintain the illusion was too exhausting. I think most people in the industry are aware at some level that they have to participate in maintaining the hype to secure their own jobs.
The core of your claim is basically that "people who don't think AI is sentient don't really understand sentience". I think that's both reductionist and, frankly, a bit arrogant.
Couldn't agree more - there are some wonderful insights to gain from seeing your own kids grow up, but I don't think this is one of them.
Kids are certainly building a vocabulary and learning about the world, but LLMs don't learn.
LLMs don't learn because we don't let them, not because they can't. It would be too expensive to re-train them on every interaction.
I know it's part of the AI jargon, but using the word "learning" to describe the slow adaptation of massive arrays of single precision numbers to some loss function, is a very generous interpretation of that word, IMO.
But that's exactly how we learn stuff, as well. Artificial neural networks are modelled after how our neuron affect each other while we learn and store memories.
Neural networks are about as much a model of a brain as a stick man is a model of human anatomy.
I don't think anybody knows how we actually, really learn. I'm not a neuro scientist (I'm a computer scientist specialised in AI) but I don't think the mechanism of learning is that well understood.
AI hype-people will say that it's "like a neural network" but I really doubt that. There is no loss-function in reality and certainly no way for the brain to perform gradient descent.