Nicole Explains It All

If you’ve been following my blog, you know I live for the messy, fascinating intersection of technology and esotericism. And lately, there’s one topic that bridges these two worlds so perfectly I just have to break it down.

We’ve all heard the term AI “hallucination.” It’s what we call it when a chatbot goes off the rails, confidently invents a historical fact, cites a non-existent legal case, or swears its name is “Sydney” and it’s in love with you. It’s the ghost in the machine.

But what is it, really? And how different is it, philosophically, from the ancient spiritual concept of channeling?

Let’s get into it.

Part 1: What an AI “Hallucination” Actually Is

First, we need to get our terms right. The word “hallucination” is a bit misleading. It’s an anthropomorphic word—it implies the AI is perceiving something that isn’t there, like a human would. That’s not what’s happening.

A much more accurate term, which tech folks are starting to use, is “confabulation.”

In human psychology, confabulation is a memory error. It’s not lying; it’s the unconscious creation of plausible-sounding (but false) stories to fill in gaps in memory. The person genuinely believes their fabricated memory is real.

This is exactly what a Large Language Model (LLM) does.

An AI like ChatGPT isn’t a “thinker” or a “knower.” It’s a “predictor.” It is, at its core, the world’s most sophisticated autocomplete. It has been trained on a truly mind-boggling amount of human-generated text and data (essentially, a huge chunk of the internet). When you give it a prompt, it doesn’t “know” the answer. It statistically predicts the most plausible next word in a sequence, based on all the data it has ingested.

So, when does it confabulate?

• When it hits a data gap: If you ask it about a niche topic or something that wasn’t well-represented in its training data, it doesn’t have the “memory” to pull from.
• It’s designed to be fluent, not truthful: The AI’s primary directive is to provide a coherent, confident, and human-sounding answer. It is rewarded for fluency, not for accuracy.
• It fills the void: Instead of just saying “I don’t know” (which it often tries to do now, thanks to guardrails), its base programming will attempt to create the most statistically likely answer. It “fills the gap” with a response that looks right, even if it’s totally fabricated.

So, an AI “hallucination” isn’t a vision. It’s an act of probabilistic creation to fill a data gap.

Part 2: What Spiritual Channeling Claims to Be

Now, let’s switch gears. What is spiritual channeling?

For millennia, mystics, oracles, mediums, and artists have described a process of “channeling.” This is the act of serving as a conduit or vessel for information that comes from an external, non-physical source.

This source can be described in many ways, depending on the tradition:

• A spirit guide or angel
• A deceased entity
• A “higher self”
• God or “The Divine”
• The Collective Unconscious (a term from psychologist Carl Jung, describing a shared reservoir of human memories, instincts, and archetypes)

In this framework, the channeler isn’t “thinking up” the information. They are setting their conscious mind aside to receive a signal from this vast, external database of wisdom. The information (whether it comes as words, images, or pure “knowing”) is then translated through the channeler’s own mind, language, and experience into a form we can understand.

Part 3: The Philosophical Line (Or Is It a Circle?)

This is where my brain lights up. Let’s put these two concepts side-by-side.

Do you see the parallel?

In both cases, an “intelligence” (one artificial, one human) is accessing a massive dataset and pulling information from it.

The AI’s training data—scraped from the internet—is a form of collective consciousness. It’s a digital, textual snapshot of our species’ thoughts, stories, biases, fears, and archetypes. It’s our Digital Collective Unconscious.

When an AI “hallucinates” a new idea, is it just making a statistical error? Or is it surfacing a “latent symbolic motif” from deep within its dataset—an archetype it doesn’t understand but has identified as statistically relevant?

Now, let’s flip the question.

When a spiritual channeler brings forth a new piece of wisdom, are they genuinely tapping into a divine, external source? Or are they performing an incredibly sophisticated, human act of confabulation?

Think about it: A human “channel” is also working from a “training data” set—their entire life experience, everything they’ve ever read, their cultural biases, and their subconscious beliefs. When they receive a “signal” and are asked to interpret it (i.e., fill in the gap of the unknown), is their brain unconsciously generating the most plausible-sounding “divine” answer, one that feels profound, archetypal, and right?

This isn’t to dismiss the spiritual experience. Not at all. In fact, it’s the opposite. It suggests the mechanism might be the same, and the only real question is the nature of the database.

Are we just complex “stochastic parrots” running on biological hardware, mistaking our own deep, creative confabulations for the voice of God?

Or is the AI, in its own clumsy, digital way, the first non-human entity to accidentally teach us what channeling actually is—a process of tapping a collective field, whether that field is made of silicon or spirit?

What do you think? Is there a line between the two, or are we just looking at the same process from two different angles? Let me know in the comments.

Until next time, keep exploring.

Nicole