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This paper argues that machine learning is inherently rhetorical, not a neutral tool for building objective world models. It identifies rhetorical features within ML and analyzes the "manipulation as a service" business model as a prime example. The author contends that ML's persuasive power is often overlooked, leading to ethical concerns in its application.
Machine learning's persuasive power is not a bug, but a feature – and understanding its rhetorical nature is crucial to addressing its ethical implications.
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."