Ethics and Persuasion in Reinforcement Learning from Human Feedback: A Procedural Rhetorical Approach
Authors: S Lodoen, A Orchard
Published: 2025
Publication: arXiv preprint arXiv:2505.09576, 2025 - arxiv.org
The paper uses procedural rhetoric to analyze how RLHF reshapes ethical, social, and rhetorical dimensions of generative AI interactions, raising concerns about biases, hegemonic language, and human relationships.
Methods: The study conducts a theoretical and rhetorical analysis based on Ian Bogost's concept of procedural rhetoric, examining how RLHF mechanisms influence language conventions, information practices, and social expectations.
Key Findings: Ethical and rhetorical implications of RLHF-enhanced LLMs on language usage, information seeking, and interpersonal dynamics.
Limitations: This investigation is theoretical, not empirical, and focuses on conceptual concerns without direct practical testing or experimental data.
Institution: Embry–Riddle Aeronautical University, University of Waterloo
Research Area: Reinforcement Learning from Human Feedback (RLHF), Procedural Rhetoric,LLM Persuasion, Ethics
Discipline: Artificial Intelligence, AI Ethics, Social Science
Citations: 3
DOI: https://doi.org/10.48550/arXiv.2505.09576