{"title":"Persuasion in the Age of Artificial Intelligence (AI): Theories and Complications of AI-Based Persuasion","authors":"Marco Dehnert, Paul A. Mongeau","doi":"10.1093/hcr/hqac006","DOIUrl":null,"url":null,"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.","PeriodicalId":4,"journal":{"name":"ACS Applied Energy Materials","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Energy Materials","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1093/hcr/hqac006","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 12
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.
期刊介绍:
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.