The Rhetoric of Machine Learning
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Abstract (arXiv)
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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- 2026When Agents Persuade: Rhetoric Generation and Mitigation in LLMs
- 2025Decoding Human and AI Persuasion in National College Debate: Analyzing Prepared Arguments Through Aristotle's Rhetorical Principles
- 2024Large Language Models as Instruments of Power: New Regimes of Autonomous Manipulation and Control
- 2024From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap
- 2024Can LLMs Replace Economic Choice Prediction Labs? The Case of Language-based Persuasion Games
- 2025Persuasiveness and Bias in LLM: Investigating the Impact of Persuasiveness and Reinforcement of Bias in Language Models
- 2022Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda
- 2026Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games