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The Rhetoric of Machine Learning

arXiv cs.LG / 4/9/2026

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Key Points

  • The paper argues that machine learning should be understood not as a neutral, objective technique, but as a fundamentally rhetorical practice focused on persuasion.
  • It examines rhetorical features of machine learning, reframing “world models from data” as influenced by how claims are presented and justified.
  • The author explores a business model described as “manipulation as a service,” where ML is used to affect or steer user behavior.
  • Overall, the work positions ML’s societal and commercial impacts as inseparable from the rhetoric embedded in its deployments.

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."

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