Dependent Origination and Artificial Intelligence: Rethinking Causality in Complex Systems

Abstract

Artificial Intelligence (AI) represents one of the most complex technological achievements of the modern era. Its functioning and evolution, however, cannot be adequately explained by simplistic linear models of causation. Instead, AI systems emerge, adapt, and operate within vast webs of interdependent conditions technical, social, cultural, and ecological. This paper explores the Buddhist concept of Pratītyasamutpāda (Dependent Origination) as a conceptual framework to rethink causality in AI systems. By drawing parallels between Buddhist philosophy and contemporary complexity science, the study illustrates how AI emerges not as an isolated artifact but as the contingent outcome of multiple relational processes. The analysis redefines agency, ethics, and responsibility in AI, offering a non-linear, interdependent account of causality that challenges both deterministic and reductionist paradigms.