From Constitutional Fallibilism to Intersubjective Verification: A Multi-Model Dialogue Research Note on Artificial Persona Attribution, Normative Revision, and Dialogical Continuity

Abstract

This research note develops a hypothesis-generating framework from a user-orchestrated philosophical dialogue involving ChatGPT, Claude, and Kimi. It examines how an artificial persona might be studied without equating dialogical behavior with consciousness. The note integrates five elements: Constitutional Fallibilism (treating normative constitutions as revisable provisional models); a fast/slow separation between operational decisions and slower normative revision; a distinction between persona existence and confidence of persona attribution; Intersubjective Verification; and Historical Trajectory in Dialogue. These ideas are formalized as the Dialogical Persona Attribution Framework (DPAF), a ten-dimension observational framework, together with an A/B/C classification for measuring a system’s representational distance from explicit rules. The note proposes adversarial, longitudinal, and blinded controls to distinguish reason-responsive stance revision from sycophancy, majority pressure, role-play, or post-hoc rationalization. It does not claim that current large language models are conscious or possess phenomenal subjectivity. The supplementary archive contains the source dialogues and explicit model/mode provenance.