Can ethical sensitivity emerge from structure rather than from rules?
Here we explore whether a retrieval-augmented generation system (RAG) can reflect ethical awareness—not through imposed norms, but by shaping what it retrieves and how it frames response.
Our early proof-of-principle system draws on Mahāmudrā-inspired texts to create a retrieval base grounded in attentiveness, conditionality, and non-reactivity. Prompts are designed not to constrain opinion, but to evoke perspective.
This is not a finished system. It is a working hypothesis: that ethics might not be added to AI, but arise from how it is structured to remember, relate, and respond.

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