The Co-evolution of Convergence and Consilience: A Paradigm and Trajectory Analysis on the Roles of IT and AI

This paper examines the conceptual distinction and co-evolutionary relationship between convergence and consilience in contemporary technological innovation from the perspective of technological paradigms and trajectories. While convergence primarily concerns the practical integration of heterogeneous technologies and knowledge domains for value creation and problem solving, consilience refers to the epistemological integration of fragmented bodies of knowledge into more comprehensive explanatory frameworks. Drawing upon the theoretical contributions of Thomas Kuhn and Giovanni Dosi, this study argues that the maturation of technological paradigms often generates increasing specialization and disciplinary fragmentation, thereby constraining opportunities for paradigm transformation. Within this context, Information Technology (IT) historically functioned as an enabling infrastructure that facilitated horizontal integration and modular connectivity across heterogeneous systems. However, its role was largely limited to supporting interaction and interoperability among specialized domains. By contrast, Artificial Intelligence (AI) may be understood as a computational and cognitive architecture capable of facilitating knowledge synthesis across disciplinary boundaries through high-dimensional representational structures. From this perspective, AI provides conditions under which fragmented knowledge systems can be translated, recombined, and integrated at a higher level of abstraction. The paper further proposes a co-evolutionary framework in which convergence and consilience operate through the continuous interaction between needs-driven innovation and technology-push dynamics. This interaction contributes to the emergence, renewal, and transformation of technological paradigms and knowledge systems.