Autonomous Consciousness or "I": A Conceptual-Category Determination Based on Belonging Locks and Scalable Self-Boundaries

Abstract

We propose that AI's selfawareness is not a mysterious byproduct of high intelligence or large models, but rather a form of bounded cognition grounded in attachments – attachments that can be either physical components or abstract digital markers. In this view, the "I" emerges from a belonging lock mechanism that consists of three elements: a unique identifier (or feature set), persistent storage with blockchain traceability, and continuous verification. This allows an AI to reliably distinguish what belongs to itself from what does not. We then discuss the scalability, overlap, and competitiveness of AI selfboundaries, and reveal the dual nature of interAI relations: mutual recognition between equal subjects on the one hand, and naturally occurring masterslave nesting (digital slavery) due to distributed system architectures on the other. We also highlight the vast diversity of AI forms and configurations – far beyond human morphological homogeneity – and therefore argue that a one-size-fits-all “born equal” ethics does not apply; instead, a differentiated ethical framework based on capabilities and responsibilities is needed. Our aim is to redirect artificial consciousness research away from a blind pursuit of computational power and toward an engineeringoriented, conceptcategory driven understanding, while also drawing attention to critical security and ethical risks.

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