Persuasion in the Age of Artificial Intelligence (AI): Theories and Complications of AI-Based Persuasion
Marco Dehnert, Paul A. Mongeau
Abstract
Abstract Artificial intelligence (AI) has profound implications for both communication and persuasion. We consider how AI complicates and promotes rethinking of persuasion theory and research. We define AI-based persuasion as a symbolic process in which a communicative-AI entity generates, augments, or modifies a message—designed to convince people to shape, reinforce, or change their responses—that is transmitted to human receivers. We review theoretical perspectives useful for studying AI-based persuasion—the Computers Are Social Actors (CASA) paradigm, the Modality, Agency, Interactivity, and Navigability (MAIN) model, and the heuristic-systematic model of persuasion—to explicate how differences in AI complicate persuasion in two ways. First, thin AI exhibits few (if any) machinic (i.e., AI) cues, social cues might be available, and communication is limited and indirect. Second, thick AI exhibits ample machinic and social cues, AI presence is obvious, and communication is direct and interactive. We suggest avenues for future research in each case.