Explaining AI as an Exploratory Process: The Peircean Abduction Model

Abduction is an exploratory process, not just a single inference step. The paper argues that following philosopher Charles Sanders Peirce's original conception, abductive reasoning should be understood as an ongoing exploratory activity rather than a one-time logical leap. This distinction matters for AI systems because it suggests that explanations work best when they show the reasoning journey, not just the final conclusion.

Current XAI approaches may be missing a key component of human reasoning. The authors note that existing "Explainable AI" discussions largely overlook abduction's role in how humans actually explain things. By incorporating abductive reasoning into AI systems, developers could create explanations that better mirror how people naturally think through problems and arrive at conclusions.

Abduction aligns with modern psychology research on human cognition. The paper connects Peirce's 19th-century philosophical framework to contemporary psychological findings, suggesting that treating explanation as an exploratory process reflects how human minds actually work. This alignment could help make AI explanations more intuitive and trustworthy to users.

The framework explains why some XAI projects succeed while others struggle. By grounding XAI in abductive reasoning theory, the paper provides a lens for understanding which explanation approaches are likely to work effectively—offering practical guidance for responsible AI developers about what makes explanations genuinely useful rather than just technically transparent.