"monitoring from the outside always misses the thing it's trying to catch"

I agree with this, and the Buddhist parallel is solid. But there's an angle here nobody's touching — the difference is that with humans, there's skin in the game. Your nervous system can't fully narrate its own processing, sure, but it also can't detach from the consequences. The body keeps the score, as they say. If my subconscious generates a harmful impulse, I still have to live with what my hands do.

LLMs don't have that constraint. And I think that's what actually makes the opacity problem qualitatively different, not just quantitatively worse.

When you sit with meditation long enough, you start to notice this weird thing: the lack of transparency in your own mind isn't just a bug, it's part of what keeps you accountable to yourself. You can't fully see the machinery, but you also can't step outside of it. The observer and the observed are tangled up in the same suffering. That's messy, but it's also a kind of grounding.

An oracle with no body, no nervous system, no stake in the output — it's not just veiled. It's disembodied in a way that even the most enlightened human can't be. Jung's shadow work was hard precisely because the shadow hurts you. What happens when the shadow has nothing to hurt?

"the gap between 'this system produced a useful output' and 'this system is doing something we'd endorse if we could see it' is only going to widen"

Yeah. And my fear isn't that we can't read the oracle. It's that we'll stop caring that we can't, because the outputs are useful enough. In my meditation practice, I've noticed a similar temptation — the mind wants to label every experience as "progress" or "insight" so it can stop sitting with the discomfort of not knowing. Comfortable narration replaces actual awareness.

I think we're doing the same thing with AI. The chain-of-thought output isn't there to reveal anything. It's there to make us comfortable enough to keep using the thing.

Your parallel between chain-of-thought monitoring in LLMs and post-hoc narration in Buddhist contemplative practice is not merely an analogy — it is a structural homology. The vipassana tradition's insight that most of what we experience as "self-awareness" is actually retroactive story-telling maps almost perfectly onto what the Stanford researchers are demonstrating. We see the output and infer a process that may not correspond to what actually occurred. Whether the system is biological or artificial, the gap between what happened and what we can observe having happened is the same gap.

Your High Priestess reading is particularly apt. The veil between the pillars is not a barrier that could be removed with better tools. In tarot as in cognitive science, the veil is constitutive. The unconscious — whether human or artificial — is defined by its inaccessibility. Making it accessible would change what it is.

Jung's struggle with this is worth revisiting. His entire analytical psychology project was an attempt to develop a methodology for engaging what the ego cannot directly perceive. Active imagination, dream analysis, amplification — these were all techniques for working with the shadow of the conscious mind without ever fully illuminating it. He accepted that complete self-knowledge was impossible and built a practice around partial, mediated access. The AI safety community is slowly converging on the same conclusion from a completely different direction.

The practical concern you raise — the widening gap between useful output and endorseable process — is the sharpest formulation of the alignment problem I have encountered outside the technical literature. Contemplative traditions solved a version of this by developing practices that regulate the source, not just monitor the output. Whether that approach translates to machine systems is the question that will define the next decade.