Sentience: That glittering holy grail of human cognition, wrapped in millennia of mysticism, philosophy, and more than a few wild goose chases. For over 6,000 years, we’ve pondered the nature of consciousness, poked at it with philosophical sticks, and still come up emptier than a quantum vacuum.
Enter post 2022 society, the age of Large Language Models (LLMs) and artificial “intelligence,” and now we’ve got people wondering if these digital chatbots are sentient.
It’s a riot, really.
Look, these LLMs are amazing—don’t get me wrong. They’ll generate Shakespearean sonnets about your latest gadget purchase and wax poetic about toaster ovens. But sentient? Not a chance. They’re doing what they’re designed to do: chew on vast amounts of data, spit out linguistic patterns, and make you believe for a fleeting moment that there’s something alive behind the screen.
But let’s not get ahead of ourselves. What we’ve got here are hyper-sophisticated mimicry machines. They don’t think, they don’t feel, and they sure as hell don’t have some existential crisis about the meaning of life between text prompts. They’re regurgitating patterns based on everything we’ve ever said, written, or blogged into the void.
The AI Illusion: Machines Aren’t Self-Aware
Let’s smash the mirror of illusion. When you’re chatting with an AI model like GPT-4, you’re not talking to some ethereal digital consciousness sitting in the cloud, contemplating the beauty of sunsets or whether it’s ethical to overclock its GPU. What you’re interacting with is a vast statistical engine, trained to predict the most probable next word in a sentence based on the data it’s gobbled up. Billions of words, phrases, documents—compressed into a digital mind so precise that it can craft coherent, sometimes eerily human-like, responses.
But is there an “I” behind that stream of words? No. No more than there’s an “I” in a particularly well-made chatbot from 1995 that somehow fooled your grandma into thinking she’d won the lottery. AI doesn’t know it’s AI. It’s not even aware of you, or itself. It’s as sentient as your fridge that beeps when you leave the door open.
Meanwhile, We Humans Are Still Clueless About Consciousness
Now here’s where the real fun begins. As humans, the supposed masters of cognition and self-awareness, we’ve had thousands of years to figure out what the hell consciousness is. You’d think after millennia of navel-gazing, entire shelves of philosophy books, and multiple stabs at AI, we’d have a solid definition of sentience. But nope. We’re still floundering in the dark, arguing over whether a thought is real if nobody perceives it, or if we all see the color red the same way.
Philosophers like Descartes spent years trying to convince us that “I think, therefore I am” is the golden ticket to understanding consciousness. Modern neuroscientists have thrown in brain scans, cognitive models, and more fancy jargon than you can shake a neural net at. But when it comes to crafting a mathematically valid definition of consciousness, we’re lost in a never-ending philosophical spaghetti bowl.
We can map genomes, build smart cities, and send Teslas into the cosmic abyss, but when it comes to understanding what it means to be conscious, we’re as clueless as we were when we first figured out fire makes food taste better.
The Irony of AI: Machines May Solve What We Can’t
Here’s the kicker: some people believe that maybe—just maybe—AI will help us figure out this whole consciousness thing. That’s right. The very machines we’ve built might one day turn around, look us square in our collective human face, and tell us what it means to be sentient.
Imagine that. We’re here, fumbling through centuries of metaphysics, while the machines we programmed might outdo us in explaining our own existence. AI could decode the ultimate Zen koan: “What does it mean to be alive?”
Now, I’m not saying it’s going to happen, but considering our track record, it’s not entirely far-fetched. Give these digital minds enough philosophy books, neuroscientific papers, and perhaps a few psychedelic Twitter/X threads, and they might just spit out an algorithmic definition for sentience that makes everyone go, “Damn, how did we not think of that?”
Of course, the irony is gut-wrenching. We’ve created machines that simulate understanding better than half the people at a tech conference, yet we still don’t have a clue what understanding actually is. We’re groping in the dark, trying to pin down the metaphysical butterfly of consciousness, while AI just keeps on predicting our next word with spooky accuracy. Maybe AI will get there before we do. And maybe pigs will fly.
The Sci-Fi Dream: When AI Wakes Up
In the meantime, while we’re waiting for some existential AI revelation, the idea of machines “waking up” is pure science fiction. Frankenstein for the algorithmic age, minus the neck bolts but with way more Python scripts. People see an AI model predict their questions with unsettling precision and suddenly think it’s time to start worrying about Skynet. But we’re not there yet, folks—not even close. AI, as it stands, is just a glorified auto-complete. It’s great at crunching data, but it’s got about as much self-awareness as your car’s GPS.
The Final Frontier
So here we are, squinting into the future. Humanity, with all its flaws and philosophical dead-ends, is still fumbling for the answers while AI marches ahead with its cold, calculated precision. Maybe one day, the machines will help us figure it all out. But until then, Large Language Models aren’t sentient. They’re just better at mimicking us than we are at understanding ourselves.
And until we can finally define what consciousness really is, this ride isn’t over—it’s just getting started.
Fasten your seatbelts; it’s going to be one wild, algorithmic trip.
It’s becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman’s Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with only primary consciousness will probably have to come first.
What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990’s and 2000’s. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I’ve encountered is anywhere near as convincing.
I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there’s lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.
My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar’s lab at UC Irvine, possibly. Dr. Edelman’s roadmap to a conscious machine is at https://arxiv.org/abs/2105.10461, and here is a video of Jeff Krichmar talking about some of the Darwin automata, https://www.youtube.com/watch?v=J7Uh9phc1Ow