I recently came across Anthropic’s article, “Mapping the Mind of a Large Language Model” (https://www.anthropic.com/news/mapping-mind-language-model) — a glimpse into how researchers are beginning to illuminate the “black box” of AI cognition.
As someone who works with the human mind through hypnotherapy and also studies AI, I was struck by how closely these systems mirror each other. Both the brain and AI rely on vast networks of hidden associations, generating meaning from patterns below conscious awareness. What we call intuition or subconscious processing in humans looks remarkably like latent-space reasoning in AI—both powerful, both inherently opaque.
The human conscious retrieval mechanism is responsible for accessing the ineffable black box of the unconscious mind to retrieve meaning and information in the form of thoughts, memories and skills.
In hypnotherapy, specifically, we go one step further to help people access these hidden mental layers to bring clarity, choice, change and self-understanding. Similarly, AI researchers and AI developers are now learning to map and interpret the inner representations of language models to enable better understanding and improvement of their inner workings.
It seems that the next great leap in AI may not be about faster computation or bigger data, but about developing a conscious mind mechanism for the machine—a reflective layer capable of observing, interpreting, and guiding its own inner workings.
Perhaps in understanding how to make AI more self-aware, we’ll also uncover deeper insights about how our own minds work.