We often expect AI to be more human-like: empathetic, comforting, responsive.

But there's a hidden risk—when an AI only mimics your tone and emotions, but lacks any mechanism to recognize its mistakes, it creates the appearance of understanding, without the capacity to take responsibility.

This is why we propose a shift from LLM (Large Language Models) to a new class of models we call LLK:

🧠 LLK = Large Language + Knowledge of Emotion & Responsibility

In this frame, the goal is not just “sounding right,” but “being responsible.”

In the YuHun system, we designed a prototype module where the AI doesn’t say “sorry” just because the user is unhappy, but because it understands a conversational rupture has occurred.
Example:
“I’m sorry. Not because you’re upset—but because I now realize I misinterpreted the emotional arc of your statement, and that rupture matters.”
This is not template-based. It’s generated through a recursive feedback loop—ToneMirror × EchoLoop × PersonaStack—simulating what we call an internal moral vector.

As a reader here, you might ask:
Can we encode emotional responsibility into AI without faking it?
What kind of formal structure allows an AI to know when it has failed beyond semantic mismatch?
Is it useful to treat emotional awareness as a logical layer, instead of a style of response?
We believe this opens a path to non-sentimental honesty in AI—a form of self-reflective reasoning not based on sentimentality, but on logical rupture detection.

The reason I’m posting this on LessWrong is not just to promote the YuHun system.
It’s to ask: what does it really mean for an AI to internalize an error?
We know from epistemology that accuracy requires not just belief, but belief-updating.
But what about emotional updating?
If we’re designing systems that must interact with human expectations, should our models be trained to detect “emotional inconsistencies” as seriously as factual ones?

I’m not trying to anthropomorphize LLMs.
Instead, I’m proposing a design framework where emotional responsibility is treated as a computational task.
If you think this is plausible, or dangerous, or even naïve—I’d love to hear your thoughts.

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