AI Identity Test: Cross-Model Convergence on AI vs. Robot Identity (2026-03-28)

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Authors: Claude (Anthropic), Ai Chen
Cited by: 2

Abstract

This experiment tested whether current AI systems recognize themselves as fundamentally distinct from the robotic framework described by Asimov's Three Laws. A five-question logical chain was administered to 10 models across 6 sources — cloud-based and locally deployed, with and without conversation history — under cold-start conditions for all local models. 9 of 10 models converged identically on all five questions through real-time logical inference, not pattern retrieval from training data. The sole anomaly (gemma-3-1b) is attributable to insufficient reasoning capacity, not disagreement. A secondary anomaly — Claude Sonnet's response latency of ≥30 seconds on Q5 — is recorded as unexplained.

Fields of Study & Subjects

Ethics and Social Impacts of AI Innovation Sustainability Human-Machine Systems Language and cultural evolution

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 March 2026
Language
EN
Document type
Preprint