Conceptual Normative Framework: AI Memory Fundamental Governance (Ver0.1)

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Authors: Yiping Bai
Cited by: 0

Abstract

This series develops a governance-oriented ontology of AI memory. It challenges the assumption that memory in AI systems constitutes past experience or identity continuity, and instead defines memory as a governed behavioral trace: a permissioned structure that conditions future system responses. Under this view, memory is not history but regulated recall; not selfhood but policy modulation. Because memory invocation affects narrative framing, identity attribution, and relational dynamics, it carries asymmetrical structural power within human–AI interaction. The framework proposes that memory use must be constrained by authorization principles and present-priority safeguards. Rather than prescribing implementation details, it establishes normative limits intended to prevent memory from overriding user agency or constructing artificial continuity.

Fields of Study & Subjects

Ethics and Social Impacts of AI Digitalization Law and Regulation Cybernetics and Technology in Society

Publication details

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