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Measuring public opinion towards artificial intelligence: development and validation of a general AI attitude short scale
Novotny, Marcus
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Weber, Wiebke
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Kern, Christoph
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Kreuter, Frauke
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s00146-025-02478-5.pdf
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DOI:
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https://doi.org/10.1007/s00146-025-02478-5
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URL:
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https://doi.org/10.1007/s00146-025-02478-5
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URN:
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urn:nbn:de:bsz:180-madoc-705907
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Dokumenttyp:
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Zeitschriftenartikel
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Erscheinungsjahr Online:
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2025
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Datum:
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31 Juli 2025
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Titel einer Zeitschrift oder einer Reihe:
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AI & Society
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Band/Volume:
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tba
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Heft/Issue:
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tba
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Seitenbereich:
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1-33
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Ort der Veröffentlichung:
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Guildford ; London
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Verlag:
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Springer
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ISSN:
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0951-5666 , 1435-5655
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Außerfakultäre Einrichtungen > MZES - Arbeitsbereich A
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Bereits vorhandene Lizenz:
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 Creative Commons Namensnennung 4.0 International (CC BY 4.0)
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Fachgebiet:
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300 Sozialwissenschaften, Soziologie, Anthropologie
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Freie Schlagwörter (Englisch):
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artificial intelligence , attitude measurement , scale development survey research , technology acceptance , AI risk
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Abstract:
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The rapid proliferation of artificial intelligence (AI) has sparked both enthusiasm and ethical concerns in societies. As AI continues to permeate daily life, policymakers need to understand how it is perceived by diverse stakeholders and communities. To reliably measure attitudes towards AI of the general public, a short scale is essential for universal application. Existing scales face limitations in applicability due to their length, sub-standard internal consistency, or a focus on only negative attitudes. In response, we built up on existing scales and developed a unidimensional six-item general AI attitude short scale. First tests on internet panel data from Germany (n=1001) and the US (n=3091) obtained favorable results for classical test theory (CTT) and item response theory (IRT). Confirmatory factor analysis indicated an excellent fit for a single-factor structure, while the scale also exhibited strong criterion-related validity, correlating positively with digital competency and predicting acceptance of several AI applications. Additional IRT analyses suggested high item discrimination, broad coverage of the attitude spectrum and no meaningful differential item functioning (DIF). Thus, we propose a psychometrically sound short scale for measuring general AI attitude and provide insights into the antecedents and consequences of the construct.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
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 Suche Autoren in
BASE:
Novotny, Marcus
;
Weber, Wiebke
;
Kern, Christoph
;
Kreuter, Frauke
Google Scholar:
Novotny, Marcus
;
Weber, Wiebke
;
Kern, Christoph
;
Kreuter, Frauke
ORCID:
Novotny, Marcus ; Weber, Wiebke ; Kern, Christoph  ORCID: 0000-0001-7363-4299 ; Kreuter, Frauke ORCID: 0000-0002-7339-2645
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