What question did this study set out to answer?

To investigate how generative AI is described in various discourses while critiquing the technology itself.

May 29, 2026Open Access

Discourse Depot

Key Points

To investigate how generative AI is described in various discourses while critiquing the technology itself.
Utilizes critical discourse analysis frameworks with extensive system instructions and JSON schemas.
Produces analyses of AI-related texts across multiple analytical frameworks.
Develops interactive learning objects and pedagogical materials for AI literacy education.
Identifies a gap between the sophistication of AI outputs and the simplistic, anthropomorphic language used to describe them.
Emphasizes the importance of recognizing the human and corporate responsibilities behind AI technologies.

Abstract

Discourse Depot is a public, independent scholarly project that uses large language models as research instruments to examine how generative AI is described, explained, and naturalized in popular, technical, and academic discourse. Founded in October 2025 by Troy Davis, a librarian at William Political Framing; Critical Forensic; Critical Activist; and others); The analytical instruments themselves — the system-instruction-and-schema designs that generate the analyses, advanced under a "prompt as scholarship" pedagogy in which the prompt is the scholarly artifact; Pedagogical materials, including the Glass Box Syllabus, an alignment of the audit prompts with the ACRL Framework for Information Literacy, and an educator's FAQ on generative AI; Interactive learning objects (LLM Training Journey, LLM Inference Journey, and others) and a companion library of standalone, citable analysis artifacts. The accompanying essay, "Looking Through the Glass Box," sets out the project's argument in full.

Discourse Depot

Key Points

Abstract

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