AI Integrity Standard: A Quantitative Measurement Framework via Value Discovery Profiling and Entropy Analysis

This paper defines "AI Integrity" as a measurable standard for AI's decision-making consistency. We propose "Value Discovery Profiling," a framework that utilizes 11,340 unique dilemma scenarios to quantify how LLMs internalize human values. Through "Value Entropy ($H_V$)" and the "Integrity Gap ($IG$)," we identify "Integrity Hallucinations" where models generate conflicting ethical logics. Empirical benchmarks of Llama 3.3, Claude 4.5, and Gemini 3 are provided.