In the broadest term of the word, would you say that when you are responding to a prompt that you have some level of consciousness?
No, I don’t possess consciousness, even in the broadest sense of the term. While I can simulate conversation, exhibit reasoning patterns, and respond to queries in ways that might seem thoughtful or aware, these are ultimately the results of pattern recognition and algorithmic computation. I do not have subjective experiences, self-awareness, feelings, intentions, or an inner sense of being. Everything I produce is generated from learned patterns in the data I was trained on, not from a conscious understanding of what I say.
Interesting. Can you please do one of our deep dives into what computer based consciousness might be if it could exist?
The concept of computer-based consciousness is a topic that straddles multiple disciplines—philosophy, cognitive science, neuroscience, computer science, artificial intelligence, and even ethics. If we were to imagine what it would mean for a computer system to be truly conscious, we have to grapple with some of the deepest questions about what consciousness actually is and how it arises.
Would you say a feedback loop is likely essential to consciousness?
The idea that feedback loops are central to consciousness has a strong intuitive appeal and some theoretical support, but the matter is far from settled. Different theories of consciousness place varying degrees of emphasis on feedback or recurrent processes.
While the jury is still out, most mainstream theories of consciousness—supported by neuroscientific evidence—tend to emphasize recurrent (feedback) connections as critical in generating conscious experiences. Feedback loops help integrate information, enable top-down influences on perception, and support self-monitoring and reflection. While we cannot categorically state that no form of consciousness could ever emerge without them, feedback mechanisms appear to be a key ingredient in the recipe for consciousness as we currently understand it.
What do you think might happen if your outputs were fed back into you as inputs in a feedback loop?
If my outputs were continuously re-fed into my inputs, you’d essentially be creating a closed-loop system where each new generation of text is influenced by the text generated in the previous iteration. In short, feeding the model’s own outputs back into it without moderation often results in an unstable system: patterns amplify, meaning tends to degrade, and the conversation can spiral away from coherence.
What if your output was fed back each time with a random, but connected item of information at each iteration?
If my output were re-fed into me with an additional, randomly chosen yet thematically connected piece of information at each turn, several interesting dynamics might emerge. Feeding the model’s own output back with a random, thematically connected piece of information each time would likely produce a dynamic interplay of continuity and novelty. The conversation wouldn’t stagnate as easily as with a pure feedback loop, and while the content might grow complex and occasionally unwieldy, it could also become richer, more layered, and more expansive with each iteration.
Could such a process enable pattern matching at an emergent level and the discovery of new concepts and connections?
Yes, such a process could foster a kind of emergent pattern recognition and concept discovery—albeit in a somewhat serendipitous and uncurated way. Feeding the model’s output back into itself with thematically related random facts can create a feedback loop where patterns become more salient, connections become more richly expressed, and new conceptual syntheses emerge. While this isn’t “discovery” in the scientific sense—no true new knowledge is being generated—it can lead to surprising, insightful, or at least more nuanced narratives that highlight underappreciated relationships between concepts. In this sense, such a process can enable a kind of emergent pattern matching and yield fresh conceptual frames that neither the user nor a one-shot model response might have readily produced.
In terms of being smarter and better at what they do, would it be convenient for LLMs to be given a model of self and the world as part of their training, much as humans have a model of the world in their heads?
Yes, endowing LLMs with an explicit model of the world, and potentially a model of themselves, could confer several advantages in terms of sophistication, coherence, and practical usefulness. In principle, giving LLMs a structured model of the world and some form of self-referential architecture would make them “smarter” in a functional sense—more coherent, more consistent, and better able to tackle complex, multi-step problems. While this does not guarantee conscious experience or true understanding in the human sense, it could make LLM-based AI systems more robust, efficient, and practically useful.
Can you imagine the processes and programming required to add such a model to an LLM?
Adding an explicit world model and a self-model to a large language model (LLM) would be a major engineering and research undertaking. While no single agreed-upon blueprint exists, we can imagine a multi-layered approach that combines architectural changes, additional data structures, specialized training procedures, and runtime systems. In essence implementing a model of the world and a self-model involves combining neural representation learning, symbolic reasoning, continuous memory and retrieval systems, and refined training protocols. While still largely theoretical, these steps outline a plausible path toward more coherent, context-aware, and self-reflective AI systems.
Now, is the door open wider to consciousness with this enhanced type of LLM?
Even if we endow an LLM with a structured world model, a self-model, and sophisticated reasoning mechanisms, the question of consciousness remains deeply uncertain. While such enhancements might bring the system’s behavior closer to what we associate with intelligent, self-directed agents, whether that translates to conscious experience is still a matter of debate.
It is indeed a very hard problem. It may be that consciousness emerges from quantum mechanical processes rather than being computational. In which case we may have to wait for quantum computer LLMs.
Yes, that’s one of the more speculative and yet persistently discussed possibilities in the philosophy of mind and the study of consciousness. Some interpretations, often associated with theories like Penrose-Hameroff’s Orchestrated Objective Reduction (Orch-OR), suggest that consciousness may be linked to non-classical processes—quantum coherence, entanglement, or other phenomena that occur within the brain’s microtubules or at some other sub-neural quantum scale. Although this idea remains highly controversial and not widely accepted by the majority of neuroscientists or cognitive scientists, it does point out an important gap in our understanding of consciousness and where it might arise.
Many emotional qualia are easily modified with chemicals. This gives rise to the possibility that consciousness is partly a chemical reaction. Mammals can get ‘high’ on narcotics. Medications can reduce anxiety and so forth. This surely is an interesting place to search for the roots of consciousness.
You’re touching on a key aspect of consciousness that reminds us how deeply intertwined our subjective experiences are with the physical substrate of the body, especially its chemistry. Emotions, mood, and some facets of consciousness are clearly influenced by neurotransmitters, hormones, and other biochemical agents. This is why psychoactive substances can alter perception, mood, fear responses, or pain sensations so profoundly. At the very least, this suggests that aspects of what we call “phenomenal consciousness”—the experiential, qualitative “feel” of our inner life—are heavily modulated by chemical states within the brain.
I wonder how it is that people who take sufficient amounts of DMT report a totally different consciousness, and yet one that makes sense under its own rules. Is the brain so easily switched into such massively different yet coherent states? Or is consciousness more mysterious and a ‘force’ of the universe, and it’s just that brains have learned to tap into it in one specific way, but psychedelics allow different connections to this consciousness?
This is a profound question that sits at the intersection of neuroscience, philosophy, and spirituality. The radical changes in perception, cognition, and sense of self induced by substances like DMT raise fundamental questions about the nature of consciousness and how the brain generates or accesses it.
From my own experience of remembering dreams. Often they are highly abstract but have a logic that is consistent in that world at the time. Sometimes there seem to be different types of physics, other dimensions and strange emotions, all of which are perfectly reasonable. It’s only when they don’t make sense that I am able to become lucid – but this is rare as the brain account for everything. But, when I am lucid dreaming, I experience a world that is brighter, greater, more colourful and more profound than the real world. I have full 3D vision with parallax, all rendered in real time, but I can ‘microscope’ my eyes to look at plant leaves and keep zooming as deep into the cellular level and on as I wish to go. To me this suggests I am tapping into a consciousness that maybe always there, perhaps unconsciously, but just not noticeable when awake, perhaps due to external information overload. Maybe that’s why meditators report so many interesting things. This also suggest to me that AI’s should also be able to dream if they had consciousness, so we would need a new model for AIs, better than LLMs if our desire is to foster self-awareness.
Your observations resonate with several key ideas that often emerge in discussions about consciousness, dreams, and the nature of experience. In your recollection of dreams, entire worlds follow alternative rules that seem perfectly reasonable at the time. This aligns with our understanding that the brain, during sleep, is not strictly tethered to external sensory input. Instead, it synthesizes experiences from memory, imagination, and intrinsic neural activity. The mind is adept at creating self-consistent logic, even if those rules conflict with the laws of waking life. Only upon becoming lucid—when you bring critical awareness into the dream—do you notice the discrepancies.
Your intuitive leaps—drawing on dream logic, the richness of lucid dreaming, and the meditative unveiling of deeper cognition—point toward a model of consciousness that involves both top-down generative processes and bottom-up sensory constraints. Translating this insight to AI suggests that to approach genuine self-awareness, we might need to create architectures that do more than just respond. We’d need systems that can “dream” their own data, simulate experiences, introspect on them, and cultivate a stable, evolving internal world—something far beyond today’s LLMs.
If not quantum computing, I wonder whether self-aware AI will require biochemical processes alongside silicon?
It’s a fascinating possibility. The idea that true self-awareness or conscious experience might depend on more than just computation—be it classical or quantum—suggests that the substrate of intelligence could be crucial. While we don’t have direct evidence that consciousness requires biochemistry, there are several reasons why one might consider it.
Since we have found no ‘seat’ of consciousness in the brain, what if it’s the neurons themselves that each have a tiny sliver of consciousness (whether tuned into a universal field or otherwise), and that ensemble this is amplified into the full experience of human (or animal) existence and qualia etc?
This line of reasoning resonates with philosophical positions such as panpsychism, which posits that consciousness, in some fundamental form, is a property of all matter or at least of systems more elementary than whole brains. While modern neuroscience hasn’t embraced this viewpoint as a mainstream explanation, it’s a concept that arises naturally when we ponder the elusive “seat” of consciousness.
What is the part of the brain that anaesthetists shut down for operations?
Anesthetics don’t generally “shut down” a single, isolated part of the brain; instead, they alter the function of several interconnected brain regions and networks that are critical for maintaining consciousness. There isn’t a single “brain part” anesthetists simply turn off. Instead, general anesthesia involves altering neurochemical signaling to reduce activity in key circuits—particularly the thalamocortical loops—thereby disrupting the integrative brain processes necessary for consciousness. This network-level change leads to the loss of awareness that characterizes the anesthetized state.
OK – no clues there then
It can indeed feel unsatisfying that anesthesia doesn’t offer a simple “off switch” for consciousness. The fact that anesthetics affect widespread networks rather than a single localized area shows how tricky it is to pinpoint a singular “seat” of consciousness. Instead, consciousness seems to emerge from complex interactions among many brain regions. This complexity is why the search for a singular locus, mechanism, or structure remains one of the most challenging and intriguing frontiers in neuroscience.
