Artificial Hyper-Realistic Intelligence (AHI): A Framework for Human Level Realism in Artificial Intelligence

Abstract Artificial Intelligence (AI) research has traditionally focused on advancing computational capability through Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI). These paradigms primarily evaluate systems based on problem-solving ability, reasoning capacity, and performance relative to human cognition. This paper proposes a conceptual framework known as Artificial Hyper-Realistic Intelligence (AHRI), also referred to as Artificial Hyper-Intelligence (AHI). Unlike AGI and ASI, which emphasize intelligence as computational and cognitive performance, AHI focuses on the capacity of artificial systems to generate, maintain, and govern synthetic realities that may become indistinguishable from physical reality in their social, psychological, and informational effects. The framework introduces three foundational dimensions: Epistemic Substitution, Synthetic Stabilization, and Ontological Autonomy. Together, these dimensions provide a basis for evaluating AI systems beyond intelligence-centric paradigms, extending the analysis toward reality construction, synthetic ecosystem governance, and long-term hyperreal interaction. Rather than positioning itself as a successor to AGI or ASI, AHI is proposed as a complementary analytical dimension within AI development, emphasizing realism, synthetic reality generation, and the governance of digitally constructed environments. This paper establishes the theoretical foundations of AHI and outlines directions for future research in evaluation frameworks and AI governance. Keywords: Artificial Intelligence, AHI, AHRI, AGI, ASI, ANI, hyperreality, synthetic reality, digital ecosystems, epistemology, AI governance.This work represents an early-stage conceptual working paper intended for scholarly discussion and furthertheoretical development.