AIF Insights No. 22 (2025) | Dependent Origination and Systems Thinking: A Buddhist Logic for Explainable AI

AIF Insights No. 22 (2025) | Dependent Origination and Systems Thinking: A Buddhist Logic for Explainable AI

This chapter explores how the Buddhist principle of pratityasamutpada (dependent origination) can enrich explainable AI (XAI) by offering a systems-based, relational understanding of causality. Challenging linear and reductionist models, it argues for a paradigm of situated explainability rooted in interdependence, contextuality, and moral awareness. Drawing parallels between Buddhist logic and systems thinking, the chapter advocates for viewing AI not as autonomous or intrinsically intelligent, but as emergent from networks of design choices, data structures, institutional practices, and sociohistorical conditions. Incorporating insights from Nagarjuna’s Madhyamaka philosophy, it critiques essentialist assumptions in AI and proposes a flexible, pluralistic approach to explanation. Ultimately, a Buddhist-informed XAI framework fosters transparency, epistemic humility, and inclusive design—enabling AI systems to be not only technically accountable but also ethically and culturally responsive.