Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Pujari, Jyoti Prakash; Dirghangi, Aditi Title A name given to the resource Beyond Lexical Accuracy: AI's Catastrophic Loss of Political Blood in Translating Lorde's Revolutionary Vernacular Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Cultural Considerations for Effective Digital Transformation in Education;pp.27-50 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-3673-2.ch002" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-3673-2.ch002</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105023743127?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023743127?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Pujari J.P., Christ University, India; Dirghangi A., Christ University, India Description An account of the resource This chapter examines how generative AI systems (ChatGPT-4o, Gemini 2.5) process the revolutionary poetics of Audre Lorde, revealing systematic patterns of grammatical standardization, affective dilution, and political neutralization. Through comparative analysis of three poems (Power, A Litany for Survival, Who Said It Was Simple) under minimal and culturally contextual prompts, the study demonstrates AI's architectural inability to preserve African American Vernacular English (AAVE), embodied metaphor, or radical tonality. These distortions-rooted in training data biases and fluency optimization-constitute epistemic violence by sanitizing texts where form enacts resistance. Findings expose limitations in developer frameworks prioritizing "harmlessness" over linguistic justice. The chapter proposes pedagogical strategies for critical AI literacy and urges redesign of systems to honor marginalized epistemologies. Ultimately, it argues that tools shaped by dominant grammars cannot ethically translate insurgent voices. 2026, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833733675-6; 979-833733673-2; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online