PEEL: A Semiotic Scaffolding for Epistemically Engaged AI Literacy in Research

Summary

This commentary introduces PEEL (Protocols for Epistemically Engaged Literacy in AI), a working scaffolding proposed by Clarisse de Souza, Gabriel Barbosa, and Simone Diniz Junqueira Barbosa to address how large language models reshape research practice while quietly eroding researchers' epistemic accountability. PEEL combines deterministic distant reading via Voyant Tools with LLM interpretation via Claude, grounded in Peircean semiotics and abductive reasoning. When applied to AI-generated condensations of three source texts, PEEL reveals systematic distortions in quantity, term frequency, and epistemic voice—distortions that are invisible without non-AI measurement. The authors derive three design implications: deterministic instruments must accompany AI tools; fluency is not fidelity; and epistemic authority must be designed in, not assumed. The paper (arXiv 2506.00635) was published in June 2025 and falls in the machine learning domain.