Dark Future: Development and Initial Validation of Artificial Intelligence Conspiracy Beliefs Scale (AICBS)
- PMID: 40607584
- PMCID: PMC12224044
- DOI: 10.1002/brb3.70648
Dark Future: Development and Initial Validation of Artificial Intelligence Conspiracy Beliefs Scale (AICBS)
Abstract
Background: In the past few years, the rapid development of artificial intelligence (AI) and its success in many areas of everyday life have attracted global attention. Some discussions have noted that generative AI tools can make decisions on their own with the potential to improve themselves. Subsequently, conspiracy theories have emerged concerning the future implications of AI. In the present study, the Artificial Intelligence Conspiracy Beliefs Scale (AICBS) was developed to assess conspiracy beliefs concerning AI, andits psychometric properties were examined.
Methods: A cross-sectional survey was conducted with 788 Turkish participants (Mage = 25.10 years, 56% female). The sample was split to carry out an exploratory factor analysis (EFA; n = 423) and a confirmatory factor analysis (CFA; n = 365), resulting in a 30-item scale comprising five subdimensions.
Results: The five-factor structure explained 62.58% of the total variance. The CFA showed acceptable model fit indices and confirmed the EFA's five-factor structure. Based on the EFA's factor loadings, a short five-item version of the AICBS (AICBS-5) was developed with one item from each subdimension (which explained 45.28% of the variance). The CFA confirmed the unidimensional structure of the AICBS-5. The internal consistency coefficients of the AICBS, its subdimensions, and the AICBS-5 demonstrated very good reliability. Correlation analyses with external criterion measures (AI Anxiety Scale, Generic Conspiracist Beliefs Scale-5, and Anomie) supported the concurrent validity of the AICBS, its subdimensions, and the AICBS-5.
Conclusion: The findings demonstrate that both AICBS and AICBS-5 are valid and reliable psychometric instruments to assess AI conspiracy beliefs.
Keywords: artificial intelligence; artificial intelligence conspiracy theories; conspiracy theories; generative artificial intelligence; psychometric testing; scale development.
© 2025 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.
Conflict of interest statement
The authors declare no conflicts of interest.
Similar articles
-
Turkish adaptation of the artificial intelligence ethics scale (EAI): a validity and reliability study for nursing students.BMC Psychol. 2025 Aug 17;13(1):925. doi: 10.1186/s40359-025-03283-x. BMC Psychol. 2025. PMID: 40820222 Free PMC article.
-
The General Attitudes towards Artificial Intelligence Scale (GAAIS): validation and psychometric properties analysis in the Italian context.BMC Psychol. 2025 Jul 1;13(1):641. doi: 10.1186/s40359-025-02935-2. BMC Psychol. 2025. PMID: 40597372 Free PMC article.
-
Development and Psychometric Properties of Scale for Safe Pesticide Use Behaviors Assessment Based on the Health Belief Model.J Agromedicine. 2025 Jul;30(3):454-467. doi: 10.1080/1059924X.2025.2485929. Epub 2025 Apr 3. J Agromedicine. 2025. PMID: 40181560
-
Artificial intelligence for detecting keratoconus.Cochrane Database Syst Rev. 2023 Nov 15;11(11):CD014911. doi: 10.1002/14651858.CD014911.pub2. Cochrane Database Syst Rev. 2023. PMID: 37965960 Free PMC article.
-
The measurement of collaboration within healthcare settings: a systematic review of measurement properties of instruments.JBI Database System Rev Implement Rep. 2016 Apr;14(4):138-97. doi: 10.11124/JBISRIR-2016-2159. JBI Database System Rev Implement Rep. 2016. PMID: 27532315
References
-
- Akhter, S. , Ahmad M. R., Chibb M., Zai A. F., and Yaqoob M.. 2024. “Artificial Intelligence in the 21st Century: Opportunities, Risks and Ethical Imperatives.” Educational Administration: Theory and Practice 30, no. 5: 4600–4605. 10.53555/kuey.v30i5.3125. - DOI
-
- Akinrinola, O. , Okoye C. C., Ofodile O. C., and Ugochukwu C. E.. 2024. “Navigating and Reviewing Ethical Dilemmas in AI Development: Strategies for Transparency, Fairness, and Accountability.” GSC Advanced Research and Reviews 18, no. 3: 050–058. 10.30574/gscarr.2024.18.3.0088. - DOI
-
- Brailovskaia, J. , Margraf J., and Schneider S.. 2021. “Social Media as Information Source, Stress Symptoms and Burden Caused by Coronavirus (COVID‐19): A Cross‐National Investigation of Predictors.” European Psychologist 26, no. 4: 373–386. 10.1027/1016-9040/a000452. - DOI
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Miscellaneous