Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research
Researchers have developed PEEL (Protocols for Epistemically Engaged Literacy in AI), a framework combining deterministic distant reading tools with LLM interpretation to measure and expose systematic distortions in AI-generated text summaries. The framework reveals that large language models introduce undetectable errors in quantity, term frequency, and epistemic voice, challenging the assumption that AI fluency equals fidelity and raising critical questions about researcher accountability in AI-assisted scholarship.