The article develops ATTARI-12, a twelve-item scale intended to measure people's general attitude toward artificial intelligence, and examines whether that attitude is associated with personality traits. The scale balances six positively and six negatively worded items and represents cognitive, affective, and behavioral content, although it is scored as one general factor. The paper reports three human studies: 601 US MTurk participants for scale construction and validation, of whom 490 are retained; German students for translation and retest, with 166 responses at T1, 163 at T2, and 150 matched; and 353 MTurk participants for the personality analysis, of whom 298 are retained under the final attention criterion. No AI system's personality is measured.
In Study 1, the strict one-factor confirmatory model fits poorly, CFI=.85, RMSEA=.15, and SRMR=.08. A bifactor S-1 model adding an orthogonal factor for negative wording improves fit to CFI=.98, RMSEA=.06, and SRMR=.03. The general factor accounts for 79% of common variance and has hierarchical omega .83; the method factor accounts for 21% and has hierarchical omega .38. The total score has alpha .93 and correlates .60 with attitudes toward voice assistants, .68 with attitudes toward robots, and .04 with social desirability. The shared data reproduce these values. This supports a general score with a material wording effect; it does not show that the simple one-factor model fits well or establish comprehensive independent validity.
In Study 2, the German version has alpha .91 at T1 and .89 at T2 and a test-retest correlation of r=.804 after 26–36 days. AI attitude correlates with stated interest in an AI-related career, r=.635 at T1 and r=.563 at T2. The released OSF file contains only the 150 matched cases, so it reproduces the longitudinal correlations but cannot reconstruct from that file the 166 T1 and 163 T2 cases used in the table. The paper describes no translation and cultural-adaptation procedure and tests neither factor structure in German nor measurement invariance across English and German.
In Study 3, a cross-sectional hierarchical regression relates ATTARI-12 to age, gender, Big Five, Dark Triad, and conspiracy mentality. The final regression uses 297 complete cases, although the table labels it N=298, and explains 14% of the variance. Significant adjusted associations are younger age, beta=-.17, higher agreeableness, beta=.27, and lower conspiracy mentality, beta=-.22. Openness is p=.065; gender, conscientiousness, extraversion, neuroticism, and all three dark traits are nonsignificant. A preregistered minimum-time cutoff was changed from four to three minutes, increasing the retained sample from 247 to 298; the strict supplementary analysis retains the three main associations but reduces the Big Five increment and the agreeableness coefficient.
The defensible contribution is an open, reasonably stable scale for studying broad human attitudes toward AI, accompanied by auditable questionnaires, data, and syntax. Important limits remain: initial validation and CFA use the same sample; items were screened by the authors without cognitive interviews or external content validation; negative wording creates method multidimensionality; convergent evidence relies on brief measures from the same domain; and the personality study is correlational, self-reported, and based on convenience samples. The prose also reports RMSEA=.03 where Table 2 reports .06, and the regression caption says N=298 even though its degrees of freedom and the open data show 297 analyzable cases. Therefore, “predicts” means statistical association within this sample, not cause, a universal stable disposition, real adoption behavior, or attitudes toward any particular AI application.