Understanding Intertextuality in Explainable AI
July 20, 2025
Intertextuality is a foundational concept in literary theory, but it has profound implications for Explainable AI. At its core, intertextuality refers to how texts draw meaning from other texts—through allusion, quotation, influence, or structure.
What if XAI worked the same way?
In this post, we explore how intertextual logic—juxtaposing AI outputs with human-authored documents, prior knowledge, or cultural references—can make AI explanations more grounded, transparent, and ethical.
We also introduce our working framework that maps machine salience scores against human-critical references.
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