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Discourse Depot

Discourse Depot

Anthropomorphism, metaphor, and discourse analysis of AI

Examining how language makes artificial intelligence sound human, assigns agency to computational systems, and shapes public understanding of large language models.

Primary Framework

Anthropomorphism, Metaphor & Explanation in AI Discourse​

Discourse Depot applies critical discourse analysis to the language used to describe artificial intelligence and large language models. The audits examine how words such as “hallucination,” “learning,” and “reasoning” can make statistical systems sound like human minds, blur the distinction between observable output and internal experience, and obscure human and institutional responsibility.

Explore AI Discourse Audits đź““

From the Corpus​

This consciousness architecture relies on a complete conflation of observable output with internal cognitive mechanics. By claiming the AI “understands that others might hold beliefs” or “imagines future scenarios,” the text builds a load-bearing assumption that computational token prediction is identical to subjective phenomenal awareness.

Resources & Deep Dives​

Corpus-level findings, teaching frameworks, and interactive tools for examining anthropomorphism, metaphor, and AI discourse.

Corpus Libraries

Thematic extractions across all audits: reframings, source-target mappings, accountability patterns, and critical observations. Queried from the database and consolidated for cross-document exploration.

Browse Corpus Libraries →

What Survives?

The deconstruction experiment: strip away anthropomorphic metaphors and see what remains. Each text receives a verdict: Preserved, Reduced, or No Phenomenon.

Explore the Deconstructions →

Glass Box Syllabus

A course framework treating machine instructions as scholarly inquiry. Schema as argument. Iteration as metacognition. Provenance as scholarship.

View the Syllabus →

Educator's FAQ

“Isn’t this just plagiarism?” “Does AI really understand?” A working archive of recurring questions and not-so-recurring answers.

Read the Educator’s FAQ →

Slippage Tools

Interactive learning objects that walk through LLM training and inference step by step, revealing the gap between what AI language implies and what the systems do.

Try the Slippage Tools →

Standalone Artifacts

Self-contained HTML versions of individual analyses, packaged as standalone artifacts. The companion site currently features the Metaphor, Anthropomorphism & Explanation Audit framework.

Visit the Artifacts →

Experimental Frameworks​

Side explorations applying LLM-driven discourse analysis to political and institutional language. These remain works in progress.

Political Framing

Deconstructing how political actors use language to shape policy agendas, define national interests, and manufacture consent.

Critical Discourse

A dual-track forensic and activist analysis of power relations, agency, and structural ideology embedded in corporate and media texts.