When Machine and Bandwagon Heuristics Compete

Understanding Users’ Response to Conflicting AI and Crowdsourced Fact-Checking

Datos Bibliográficos

ID7296014
AutoresJohn A Banas (0000-0002-5641-3985, University of Oklahoma, autor de correspondencia), N A Palomares (0000-0002-7754-6357, Department of Communication Studies, University of Texas at Austin , Austin, TX, USA), Adam S Richards (0000-0003-3721-5622, Furman University), David M Keating (0000-0003-4276-1097, University of New Mexico), Nick Joyce (0000-0002-3310-7061, Department of Communication, University of Maryland, College Park, MD, USA), A Rain (0000-0002-1639-8557, University of Arizona), Stephen A Rain, Stephen A Rains (University of Arizona)
Año2022
Volumen48
Número3
Páginas430-461
Fecha de publicación2022-04-29
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaHuman Communication Research (JOURNAL)
Identificadores de la revistaISSN: 0360-3989 • E-ISSN: 1468-2958
EditorialWiley (PUBLISHER • GB)
DOI10.1093/hcr/hqac010
OpenAlexW4225133198
IdiomaEN
Citas recibidas26
Referencias citadas19

Three experiments tested if the machine and bandwagon heuristics moderate beliefs in fact-checked claims under different conditions of human/machine (dis)agreement and of transparency of the fact-checking system. Across experiments, people were more likely to align their belief in the claim when artificial intelligence (AI) and crowdsourcing agents’ fact-checks were congruent rather than incongruent. The heuristics provided further nuance to the processes, especially as a particular agent suggested truth verdicts. That is, people with stronger belief in the machine heuristic were more likely to judge the claim as true when an AI agent’s fact-check suggested the claim was likely true but not false; likewise, people with stronger belief in the bandwagon heuristic were more likely to judge the claim as true when the crowdsource agent fact-checked the claim to be true but not false. Making the system more transparent to users does not appear to change results

Bandwagon effect · Cognitive psychology · Computer security · Crowdsourcing · Heuristic · Heuristics · Interpretability · Machine learning · Transparency (behavior · World Wide Web · Computer Science · Ethics and Social Impacts of AI · Misinformation and Its Impacts · Psychology · Psychology of Moral and Emotional Judgment · Artificial Intelligence · Social Psychology