The Ethical Priority Map: 736 Formal Rules for AI Agent Architecture in Collective Decision-Making

Every governance system has its verification layer, execution layer, and decision layer. This post provides the full formal specification of what happens inside BeTrueCore’s AI agent layer — the layer that observes collective judgment. Most AI ethics frameworks answer one question: what properties should a system exhibit? TDSH answers a prior and distinct question: at what point does the collective decision-making process begin to lose integrity? This distinction — between system properties and process degradation thresholds — defines TDSH’s position in the landscape of AI governance methodology. What has been formally specified: 23 Asilomar AI Principles × 32 TDSH parameters = 736 intersection points. Each point is not merely a label — it is a priority assignment (CRITICAL / HIGH / MEDIUM / SUPERPOSITION) and a logical rule by which the Harmony Agent computes the ethical verdict. Priority distribution: CRITICAL: 169 cells (23%) HIGH: 515 cells (70%) MEDIUM: 47 cells (6%) SUPERPOSITION: 5 cells (1%) Core principle: Nine AI agents at L5 (Analyst, Strategist, Sentinel — three of each) operate in strict read-only mode. Through observation they record and measure — but never decide. Observation without a formal standard is not observation — it is impression. The 23×32 matrix transforms impression into notarial witness. The result of that witness is a traffic light signal (GREEN / YELLOW / RED): the only verdict the Harmony Agent is authorised to issue. The mirror does not know the arbiter from the executor — it reflects the entire space. The notary does not choose sides. The matrix measures both. Full specification: 10.5281/zenodo.21225420 The mirror reflects. The notary bears witness. The matrix measures. 2 posts - 2 participants Read full topic