Understanding Before Ethics: A Four-Dimensional Foundation for AI

Contemporary artificial intelligence ethics frameworks frequently commit a category error: they attempt to instantiate ethical behavior in systems that structurally lack the prerequisite capacity for genuine understanding. This paper argues that understanding, properly conceived as a multi-dimensional cognitive achievement, constitutes the irreducible foundation upon which any meaningful AI ethics must be built. Drawing on Markus Gabriel's Sinnfeldontologie, Hartmut Rosa's resonance theory, Yasuo Deguchi's We-Turn philosophy, and insights from DeepMind's MuZero architecture, we develop a four-dimensional account of the depth of understanding required for authentic moral agency. We distinguish clearly between Ethics-of-AI (E1), concerning governance and oversight of AI systems, and Ethics-by-AI (E2), concerning AI systems as potential moral agents. Our analysis reveals that current AI systems, despite sophisticated behavioral outputs, operate without the ontological grounding, relational responsiveness, social embeddedness, and operational world-modeling that genuine ethical reasoning presupposes. The paper introduces the Cognitive Agent Memory Architecture (CAMA) as a research program for cultivating, rather than guaranteeing, the conditions necessary for AI understanding. We provide operational indicators for each dimension, propose a minimal viable experimentalization framework for empirical investigation, and address major philosophical objections to our position. Version 1.1 revises v1.0 (December 2025) in light of *The Containment Paradox* (Trncik, 2026c, Zenodo DOI `10.5281/zenodo.19695770`). Two revisions are structural: a Scope and Reading Conventions preamble (§0) names the pre-parity / post-parity regime vocabulary, marks the four-dimensional account as a *constitutive* rather than a *verification* reading, and introduces a Claim Ledger of five tags (THEOREM, ENGINEERING RESULT, ASSUMPTION, CONJECTURE, OPEN PROBLEM) applied to every load-bearing argumentative claim; and a closing Disclaimer chapter (§11, "What This Paper Does Not Claim") with eight subsections that state the paper's boundaries explicitly (consciousness, verification procedure, implementation, safety guarantee, specific systems, E1 displacement, AI rights/personhood/legal status, plus a positive-summary closing). Body chapters 1–10 are textual revisions that apply the Claim Ledger throughout and sharpen the E1/E2 separation per a Lexical Quarantine discipline. The argument is unchanged in direction; the revision is an exercise in making the epistemic status of each claim visible.