A Mechanistic Explanatory Strategy for XAI

Understand

Despite significant advancements in XAI, scholars note a persistent lack of solid conceptual foundations and integration with broader scientific discourse on explanation.

• In response, emerging research draws on explanatory strategies from various sciences and the philosophy of science literature to fill these gaps.
• This paper outlines a mechanistic strategy for explaining the functional organization of deep learning systems, situating recent developments in explainable AI within a broader philosophical context.
• According to the mechanistic approach, the explanation of opaque AI systems involves identifying mechanisms that drive decision making.