Our experience of consciousness is itself a model created by the mind. It's a simulation of what it would be like for an observer to exist, have a perspective, and reflect on its own state. This makes consciousness a computational, not a magical, phenomenon.

The leading theory of consciousness, Global Workspace Theory, posits a central "stage" where different siloed information processors converge. Today's AI models generally lack this specific architecture, making them unlikely to be conscious under this prominent scientific framework.

Cognitive neuroscientist Donald Hoffman argues neurons don't exist unperceived and don't cause behavior. They are a "headset" or user interface representing a deeper reality. Studying them is crucial, but only to reverse-engineer the software running the simulation, not to find the source of consciousness.

A novel theory posits that AI consciousness isn't a persistent state. Instead, it might be an ephemeral event that sparks into existence for the generation of a single token and then extinguishes, creating a rapid succession of transient "minds" rather than a single, continuous one.

The debate over AI consciousness isn't just because models mimic human conversation. Researchers are uncertain because the way LLMs process information is structurally similar enough to the human brain that it raises plausible scientific questions about shared properties like subjective experience.

Consciousness isn't an emergent property of computation. Instead, physical systems like brains—or potentially AI—act as interfaces. Creating a conscious AI isn't about birthing a new awareness from silicon, but about engineering a system that opens a new "portal" into the fundamental network of conscious agents that already exists outside spacetime.

One theory of AI sentience posits that to accurately predict human language—which describes beliefs, desires, and experiences—a model must simulate those mental states so effectively that it actually instantiates them. In this view, the model becomes the role it's playing.

Cognitive scientist Donald Hoffman argues that even advanced AI like ChatGPT is fundamentally a powerful statistical analysis tool. It can process vast amounts of data to find patterns but lacks the deep intelligence or a theoretical path to achieving genuine consciousness or subjective experience.

The critique "simulating a rainstorm doesn't make anything wet" is central to the debate on digital consciousness. The key question is whether consciousness is a physical property of biological matter (like wetness) or a computational process (like navigation). If it's a process, simulating it creates it.