Non-Western Logic Traditions for Explainable AI: A Survey and Research Agenda

Abstract

Explainable AI (XAI) research predominantly relies on Western logic traditions-Aristotelian syllogisms, Toulmin’s argumentation schemes, and formal symbolic logic. However, non-Western cultures have developed rich epistemological frameworks over millennia that offer complementary perspectives for interpretable AI systems, particularly for modern machine learning models and large language models. We present, to our knowledge, the first dedicated cross-tradition survey of non-Western logic traditions explicitly oriented toward XAI applications, covering traditions from India (Nyaya, Buddhist pramana, Jain logic, Yoga epistemology), East Asia (Neo-Confucian li-qi, Japanese Bud-dhist innen, Chinese Mohism), Africa (Ubuntu philosophy, Ethiopian rationalism), and Islamic scholarship (Kalam, Falsafa, Sufi epistemology). For each tradition, we identify (1) core epistemological principles, (2) structural reasoning patterns, (3) potential XAI applications, and (4) any existing computational implementations.