Do People Rely on ChatGPT More Than Their Peers to Detect Fake News?

Material type: 文書・図像類

Author: Fu, Yuhaoほか

Publisher: The Institute of Social and Economic Research, Osaka University

Publication date: 2024-03

Material Format: Paper

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Note (General)：: In the era of rapidly advancing artificial intelligence (AI), understanding to what extent people rely on generative AI products (AI tools), such as C...

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Paper

Material Type: 文書・図像類
Title: Do People Rely on ChatGPT More Than Their Peers to Detect Fake News?
Author/Editor: Fu, Yuhao
Hanaki, Nobuyuki
Author Heading: Fu, Yuhao
Hanaki, Nobuyuki
https://nrid.nii.ac.jp/nrid/1000070400611
Publication, Distribution, etc.: The Institute of Social and Economic Research, Osaka University
Publication Date: 2024-03
Publication Date (W3CDTF): 2024-03
Periodical title: Institute of Social and Economic Research Discussion Papers
No. or year of volume/issue: 1233
Volume: 1233
Pages: 1-61
ISSN (Periodical Title): PISSN : 0473453X
EISSN : 24350982
Text Language Code: eng
Subject Heading: GAI
ChatGPT
AI reliance
fake news identification
WOR
activation-integration model
Heckman selection
Target Audience: 一般
Note (General): In the era of rapidly advancing artificial intelligence (AI), understanding to what extent people rely on generative AI products (AI tools), such as ChatGPT, is crucial. This study experimentally investigates whether people rely more on AI tools than their human peers in assessing the authenticity of misinformation. We quantify participants’ degree of reliance using the weight of reference (WOR) and decompose it into two stages using the activation-integration model. Our results indicate that participants exhibit a higher reliance on ChatGPT than their peers, influenced significantly by the quality of the reference and their prior beliefs. The proportion of real parts did not impact the WOR. In addition, we found that the reference source affects both the activation and integration stages, but the quality of reference only influences the second stage.
References (URI): https://www.iser.osaka-u.ac.jp/library/dp/2024/DP1233.pdf
URI
https://www.iser.osaka-u.ac.jp/library/dp/2024/DP1233.pdf
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 大阪大学 : 大阪大学学術情報庫　桜華