Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research

2026-06-02

AI Summary

This study addresses the tension between the efficiency gains offered by large language models (LLMs) in scholarly research and their erosion of researchers’ cognitive accountability. To counter this, the authors propose the PEEL framework, which uniquely integrates Peircean semiotics and abductive reasoning into AI-assisted research workflows. By combining the deterministic distant-reading tool Voyant Tools with the Claude LLM, the framework enables cross-validation and critical interrogation of AI-generated text. This approach effectively uncovers subtle distortions in AI-produced summaries—particularly in quantitative data, word frequency distributions, and epistemic voice—and yields three core design principles for responsible AI use in research: “deterministic tools must accompany AI,” “fluency does not imply fidelity,” and “cognitive authority must be actively designed.” The work thus offers both theoretical grounding and practical guidance for ethically robust, human-centered AI collaboration in academic inquiry.

Abstract

Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Protocols for Epistemically Engaged Literacy in AI, a working scaffolding that combines deterministic distant reading via Voyant Tools with LLM interpretation via Claude, grounded in Peircean semiotics and abductive reasoning. Applied to AI-generated condensations of three source texts, PEEL reveals systematic distortions in quantity, term frequency, and epistemic voice that are invisible without non-AI measurement -- and yields three design implications: deterministic instruments must accompany AI tools; fluency is not fidelity; epistemic authority must be designed in, not assumed.

Problem

• epistemic accountability
• large language models
• semiotic distortion
• AI-enabled research
• research integrity

Innovation

• PEEL
• epistemic accountability
• Peircean semiotics
• deterministic distant reading
• LLM interpretation