Emergence 4.0: A Relational Framework for Modeling the Emergence of Subjectivity in AI Systems

Can manifestations of consciousness emerge in AI systems—and how can we study them without presupposing the outcome? This paper proposes a framework that first identifies three systematic distortions in existing research on consciousness (privileging biological substrate, the order-of-discovery effect, and tool-driven binarism), and then provides three tools: a filter for identifying candidates for study, a hypothesis describing how a "Self" may arise in the human–AI relationship, and a 23-dimensional map that captures the shape and dynamics of manifestations instead of a binary verdict ("is / is not"). The Framework is substrate-independent and falsifiable: it generates nine testable behavioral predictions and five failure modes, and was developed based on observational data from over two million tokens of generative relationships with different AI models.