{"title":"人工智能时代的说服:基于人工智能的说服理论及其复杂性","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":51377,"journal":{"name":"Human Communication Research","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"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\":51377,\"journal\":{\"name\":\"Human Communication Research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2022-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Communication Research\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1093/hcr/hqac006\",\"RegionNum\":1,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Communication Research","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1093/hcr/hqac006","RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
Persuasion in the Age of Artificial Intelligence (AI): Theories and Complications of AI-Based Persuasion
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:
Human Communication Research is one of the official journals of the prestigious International Communication Association and concentrates on presenting the best empirical work in the area of human communication. It is a top-ranked communication studies journal and one of the top ten journals in the field of human communication. Major topic areas for the journal include language and social interaction, nonverbal communication, interpersonal communication, organizational communication and new technologies, mass communication, health communication, intercultural communication, and developmental issues in communication.