Impact of misinformation from generative AI on user information processing

How people understand misinformation from generative AI

Dados Bibliográficos

ID6443550
AutoresDoh Shin (0000-0002-5439-4493, Texas Tech University, autor correspondente), Amy Koerber (0000-0002-6926-5520, Texas Tech University), Joon Soo Lim (0000-0003-0519-4169, Syracuse University)
Ano2024
Volume27
Fascículo7
Páginas4017-4047
Data de publicação2024-03-20
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoNew Media & Society (JOURNAL)
Identificadores do periódicoISSN: 1461-4448 • E-ISSN: 1461-7315
EditoraSAGE Publishing (PUBLISHER • US)
DOI10.1177/14614448241234040
OpenAlexW4393003817
IdiomaEN
Citações recebidas54
Referências citadas56

This study examines the impact of artificial intelligence (AI) on the ways in which users process and respond to misinformation in generative artificial intelligence (GenAI) contexts. Drawing on the heuristic–systematic model and the concept of diagnosticity, our approach examines a cognitive model for processing misinformation in GenAI. The study’s findings revealed that users with a high-heuristic processing mechanism, which affects positive diagnostic perception, were more likely to proactively discern misinformation than users with low-heuristic processing and low-perceived diagnosticity. When exposed to misinformation from GenAI, users’ perceived diagnosticity of misinformation can be accurately predicted by the ways in which they perform heuristic systematic evaluations. With this focus on misinformation processing, this study provides theoretical insights and relevant recommendations for firms to be more resilient in protecting users from the detrimental impacts of misinformation

Computer security · Generative grammar · Generative model · Misinformation · Computer Science · Ethics and Social Impacts of AI · Knowledge Management and Technology · Misinformation and Its Impacts · Psychology · Artificial Intelligence