ParadigmShiftGPT: A General-Purpose Artificial Intelligence Framework for Paradigm Identification, Fundamental Assumption Challenging, and the Reconstruction of New Conceptual Systems

Contemporary artificial intelligence systems have demonstrated increasingly sophisticated capabilities in information retrieval, logical reasoning, knowledge synthesis, and problem solving. Nevertheless, most existing systems remain fundamentally oriented toward reasoning within established conceptual structures. When users present a question, these systems typically attempt to identify an appropriate answer using existing knowledge, established theories, and previously learned relationships. Although such capabilities are valuable, they raise a deeper question concerning the potential of artificial intelligence: Can an AI system recognize when the theoretical framework through which a problem is understood is itself fundamentally inadequate, and subsequently develop an alternative conceptual system? Throughout the history of science, significant intellectual transformations have not always resulted from accumulating additional knowledge within existing theoretical structures. Some have emerged when established assumptions, explanatory principles, or conceptual foundations became insufficient to account for observed phenomena, creating opportunities for fundamentally different interpretations. Drawing inspiration from the philosophy of scientific revolutions, particularly Kuhn's theory of paradigm shifts, this paper proposes ParadigmShiftGPT, a conceptual framework for a general-purpose artificial intelligence system designed to identify limitations in existing paradigms and explore the reconstruction of alternative theoretical and conceptual systems. The proposed architecture integrates six interconnected mechanisms: paradigm identification, anomaly and limitation detection, fundamental assumption challenging, alternative paradigm exploration, paradigm reconstruction, and independent paradigm validation. Unlike conventional reasoning systems that primarily optimize solutions within predefined assumptions, ParadigmShiftGPT investigates whether those assumptions should be reconsidered, whether the existing explanatory structure is fundamentally incomplete, and whether an alternative framework could provide a more coherent understanding of the problem. Importantly, the proposed system is designed for multimodal operation, allowing it to analyze textual knowledge, images, videos, audio, scientific diagrams, mathematical representations, three-dimensional structures, and other forms of information when identifying inconsistencies and developing alternative conceptual models. Its potential applications extend across scientific research, engineering, education, medicine, economics, business, technology, and general-purpose intellectual exploration. This paper establishes a conceptual and technically oriented foundation for paradigm-oriented artificial intelligence and proposes research hypotheses and evaluation methodologies for future empirical investigation. No experimental performance or demonstrated ability to produce verified scientific revolutions is claimed at this conceptual stage.