AI competence and sentiment: a mixed-methods study of attitudes and open-ended reflections - Lāma, Gatis; Lastovska, Agnese (Frontiers in Artificial Intelligence, 2025)
As artificial intelligence (AI) technologies become increasingly integrated into everyday life, understanding how the public perceives and interacts with AI is essential for fostering responsible and secure adoption. This study investigates the relationship between self-assessed AI competence, trust in AI-generated content, and sentiment toward AI among public and private sector employees in Latvia. Using a mixed-methods approach, the research combines quantitative survey data with open-ended qualitative responses to explore how demographic factors influence AI-related perceptions. Results reveal that although participants rate their AI competence and trust relatively highly, a significant portion of respondents either do not use AI or use it only for simple tasks. Sentiment toward AI is generally positive but often neutral, indicating that public attitudes are still forming. Statistically significant differences in AI competence were found across gender, age, and work sector, while trust in AI varied by education and age. Sentiment remained consistent across groups. Importantly, AI competence was positively correlated with trust, which in turn correlated with sentiment. Thematic analysis identified concerns about risk assessment, ethical implications, and the uncertain role of AI in daily life. The study underscores the need to enhance AI literacy and critical evaluation skills to ensure informed trust and societal resilience. These findings inform future strategies for public education, workforce training, and digital security policy in the context of accelerating AI adoption.