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March 1, 2026SHILAP Revista de lepidopterología0 citationsOpen Access

Who Did AI Leave Behind? Social Inequality Perceptions in the Use of AI Tools in Croatia

IĆIvana ĆavarEBErik BrezovecNDNikša Dubreta

Key Points

  • This research investigates how perceptions of AI tools correlate with social inequalities in Croatia.
  • Analyzed survey data from a nationally representative sample
  • Used descriptive analyses and group comparisons
  • Conducted exploratory factor analysis and multiple linear regressions
  • Frequent AI users report higher affordability and perceived knowledge
  • Non-users exhibit lower accessibility and usefulness perceptions
  • Age affects perceived knowledge and accessibility, with younger users feeling more competent

Abstract

Generative artificial intelligence (AI) is increasingly embedded in everyday life, raising questions about how its use may reinforce or mitigate social inequalities. This study examines perceptions of affordability, self-assessed knowledge, practical accessibility, and usefulness of AI tools in Croatia, focusing on how gender, age, and frequency of AI use shape emerging digital divides. Drawing on survey data from a nationally representative sample, descriptive analyses, group comparisons, exploratory factor analysis, and multiple linear regressions were conducted to identify patterned inequalities across Lutz’s three sequential levels of digital inequality: access, skills, and outcomes. Factor analysis indicates that the inequality items do not form a single coherent scale, suggesting that AI-related inequality is multidimensional and that affordability, knowledge, practical accessibility, and usefulness represent distinct but related facets. Group comparisons and regression models reveal that frequency of AI use is the most consistent predictor across all facets: frequent users report higher affordability, greater perceived knowledge, lower reliance on assistance, and stronger perceptions of usefulness, while non-users cluster at the opposite end of each dimension. Age further differentiates respondents in perceived knowledge and practical accessibility, with younger cohorts feeling more competent and less dependent on help, whereas gender only marginally shapes confidence and loses significance once age and use frequency are controlled. Overall, the findings support and extend sequential models of digital inequality by demonstrating that, in the Croatian context, GenAI inequality is driven less by static sociodemographic attributes and more by practice-based divides between those who engage with AI tools and those who remain non-users.

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Cite This Study

Ćavar et al. (2026) studied this question.

synapsesocial.com/papers/69a3d6eaec16d51705d2da3dhttps://doi.org/10.7906/indecs.24.1.2
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