The roles of personality traits, AI anxiety, and demographic factors in attitudes towards artificial intelligence
Affiliation
Ataturk University; Sivas Cumhuriyet University; University of Chester; Bayburt UniversityPublication Date
2022-12-07
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The present study adapted the General Attitudes toward Artificial Intelligence Scale (GAAIS) to Turkish and investigated the impact of personality traits, artificial intelligence anxiety, and demographics on attitudes toward artificial intelligence. The sample consisted of 259 female (74%) and 91 male (26%) individuals aged between 18 and 51 (Mean = 24.23). Measures taken were demographics, the Ten-Item Personality Inventory, the Artificial Intelligence Anxiety Scale, and the General Attitudes toward Artificial Intelligence Scale. The Turkish GAAIS had good validity and reliability. Hierarchical Multiple Linear Regression Analyses showed that positive attitudes toward artificial intelligence were significantly predicted by the level of computer use (β = 0.139, p = 0.013), level of knowledge about artificial intelligence (β = 0.119, p = 0.029), and AI learning anxiety (β = −0.172, p = 0.004). Negative attitudes toward artificial intelligence were significantly predicted by agreeableness (β = 0.120, p = 0.019), AI configuration anxiety (β = −0.379, p < 0.001), and AI learning anxiety (β = −0.211, p < 0.001). Personality traits, AI anxiety, and demographics play important roles in attitudes toward AI. Results are discussed in light of the previous research and theoretical explanations.Citation
Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M. (2022). The roles of personality traits, AI anxiety, and demographic factors in attitudes towards artificial intelligence. International Journal of Human–Computer Interaction, vol(issue), pages. https://doi.org/10.1080/10447318.2022.2151730Publisher
Taylor and FrancisAdditional Links
https://www.tandfonline.com/doi/full/10.1080/10447318.2022.2151730Type
ArticleDescription
This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Human-Computer Interaction on 07/12/2022, available online: https://doi.org/10.1080/10447318.2022.2151730ISSN
1044-7318EISSN
1532-7590ae974a485f413a2113503eed53cd6c53
10.1080/10447318.2022.2151730
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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/