Full bibliography

AIs-Discovered Framework for Artificial Information Integration: Mathematical Conditions for Synthetic Consciousness This paper presents a theoretical framework for artificial information integration systems, developed through a novel collaboration between human researchers and large language models (ChatGPT and Claude). It represents an exploratory attempt to co-author a theoretical scientific paper with AI agents, examining the possibility that artificial systems may assist in the construction of new conceptual frameworks. The significance and implications of this possibility are left to the judgment of the reader. The aim of this study is to explore how computational principles inspired by physics and information theory can be applied to synthetic architectures indepen- dent of biological consciousness. As a proof of concept, the AIs collaboratively construct a mathematical model connecting the holographic principle with formal- izations of information integration, proposing a boundary-based approach to infor- mation processing in artificial systems. While this framework draws partial inspiration from existing theories such as Integrated Information Theory (IIT), its scope is explicitly limited to artificial and computational systems, and it does not intend to replace or critique neuroscientific models of consciousness. The resulting formulation provides a testable and modular foundation for future research in artificial general intelligence (AGI).This study takes Tononi et al.’s Integrated Information Theory (IIT) as a conceptual starting point; however, the measure of integrated information (ψ ̸= Φ) introduced herein is a fundamentally distinct and novel metric.