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Research Articles

The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 497-514 | Received 04 Aug 2022, Accepted 22 Nov 2022, Published online: 07 Dec 2022

Figures & data

Table 1. Sociodemographic characteristics of the participants.

Table 2. Factor loadings of the Turkish Version of the GAAIS.

Table 3. Descriptive statistics and correlations between variables.

Table 4. Hierarchical multiple linear regression analysis results on the predictive role of various variables on positive attitudes toward artificial intelligence.

Figure 1. Predictors of the Positive General Attitudes toward Artificial Intelligence subscale, with predictors that were significant in the final model showing standardized coefficients (β) and p-values. AIKL: Artificial Intelligence Knowledge Level.

Figure 1. Predictors of the Positive General Attitudes toward Artificial Intelligence subscale, with predictors that were significant in the final model showing standardized coefficients (β) and p-values. AIKL: Artificial Intelligence Knowledge Level.

Figure 2. Predictors of the Negative General Attitudes toward Artificial Intelligence subscale, with predictors that were significant in the final model showing standardized coefficients (β) and p-values. AIKL: Artificial Intelligence Knowledge Level.

Figure 2. Predictors of the Negative General Attitudes toward Artificial Intelligence subscale, with predictors that were significant in the final model showing standardized coefficients (β) and p-values. AIKL: Artificial Intelligence Knowledge Level.

Table 5. Hierarchical multiple linear regression analysis results on the predictive role of various variables on negative attitudes toward artificial intelligence.

Supplemental material

Supplemental Material

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