The Rhetoric of Machine Learning

2026-04-08

AI Summary

Machine learning is often mistakenly perceived as neutral and objective, yet it functions as a rhetorical practice imbued with persuasive intent. This study systematically introduces rhetorical theory for the first time, integrating critical technical analysis with an examination of business models to reveal how machine learning shapes user behavior and social cognition through mechanisms such as “manipulation-as-a-service.” Challenging the myth of technological neutrality, the project elucidates the inherent rhetorical logic and socially constructed nature of machine learning systems. In doing so, it offers a novel theoretical perspective and analytical framework for the critical study of artificial intelligence, foregrounding the discursive and ideological dimensions embedded within ostensibly technical processes.

Abstract

I examine the technology of machine learning from the perspective of rhetoric, which is simply the art of persuasion. Rather than being a neutral and "objective" way to build "world models" from data, machine learning is (I argue) inherently rhetorical. I explore some of its rhetorical features, and examine one pervasive business model where machine learning is widely used, "manipulation as a service."

Problem

• machine learning
• rhetoric
• persuasion
• manipulation as a service
• objectivity

Innovation

• rhetoric
• machine learning
• persuasion
• manipulation as a service
• world models