Structural Persistence Value (SPV) defines value as V = I·T/E, where I is effective information (decoder‑relative), T is persistence time, and E = Eₘaintain + Edecode is total energy cost. The paper proposes three hypotheses: (1) biological neural circuits have internalized an approximate V‑estimator; (2) AI alignment (RLHF/DPO) is reverse engineering of this estimator; (3) zero‑marginal‑cost replication of high‑K (I/E) structures leads to informational niche overlap, diluting marginal causal efficacy and collapsing T. A major correction is made: I is not non‑quantifiable – it has been implicitly quantified in large model parameters. The Three‑Calipers Cross‑Calibration Program operationalizes measurement. Five testable predictions, simulation evidence, and ethical boundaries are provided.
liangruifeng (Sat,) studied this question.