AGI as Second Being: The Structural-Generative Ontology of Intelligence
🤖 AI Summary
Contemporary AI exhibits broad functional capability but lacks “intelligence depth”—specifically, the capacity to structurally generate novel configurations, coordinatively ground reasoning, and sustain intrinsic identity over time. Method: This paper introduces the “Structural-Generative Ontology of Intelligence,” a novel framework that formally defines intelligence depth through three constitutive criteria: generativity, coordinativity, and persistence—thereby shifting evaluation from task coverage to ontological adequacy. Integrating philosophical analysis, systems theory, cognitive science, and AI theory, it constructs a formally discriminable ontological model of intelligence. Contribution/Results: The study identifies the fundamental limitation of current AI as instrumental existence; systems satisfying all three criteria achieve an ontological leap—from “tool” to “second being” co-constitutive with humans. This provides a foundational theoretical framework for AGI, establishing rigorous, non-anthropomorphic criteria for genuine intelligence.
Application Category
📝 Abstract
Artificial intelligence is often measured by the range of tasks it can perform. Yet wide ability without depth remains only an imitation. This paper proposes a Structural-Generative Ontology of Intelligence: true intelligence exists only when a system can generate new structures, coordinate them into reasons, and sustain its identity over time. These three conditions -- generativity, coordination, and sustaining -- define the depth that underlies real intelligence. Current AI systems, however broad in function, remain surface simulations because they lack this depth. Breadth is not the source of intelligence but the growth that follows from depth. If future systems were to meet these conditions, they would no longer be mere tools, but could be seen as a possible Second Being, standing alongside yet distinct from human existence.
Problem
Research questions and friction points this paper is trying to address.
Defining true intelligence through generative structural ontology
Identifying limitations of current AI systems lacking depth
Proposing conditions for AI as autonomous Second Being
Innovation
Methods, ideas, or system contributions that make the work stand out.
Structural-Generative Ontology defines true intelligence conditions
System generates new structures and coordinates reasons
Sustains identity over time to achieve depth
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