This research explores public sentiment towards AI technologies, focusing on facial recognition, social media algorithms, and driverless cars. A hybrid descriptive-prescriptive data processing method, combining visualization, cross-tabulation, K-means clustering, PCA, ANOVA, and Random Forest prediction, was used to analyze a large survey dataset (over 5000 respondents). Three distinct clusters were identified, revealing varied levels of excitement and concern regarding AI. The model accurately predicted cluster affiliation (F1 score of 0.99 for the test set and 0.98 for the out-of-sample set). The findings offer insights into public perception and can inform policy and dialogue around AI adoption.

Simona-Vasilica Oprea, Adela Bâra