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ATTITUDES TOWARD ARTIFICIAL INTELLIGENCE AND GENDER DIFFERENCES AMONG SPANISH EMERGING ADULTS

New technologies are transforming the lifestyles, interactions and learning methods of young people. Among these new information and communication technologies, artificial intelligence (AI) platforms have recently experienced a significant boom. The importance of general attitudes towards AI has recently been examined…

New technologies are transforming the lifestyles, interactions and learning methods of young people. Among these new information and communication technologies, artificial intelligence (AI) platforms have recently experienced a significant boom. The importance of general attitudes towards AI has recently been examined to understand how and why it is used. The four-item AI Attitude Scale (AIAS) has recently been introduced to measure the general public’s attitudes towards AI. This study aims to examine attitudes towards AI among university students in Spain and analyse the gender invariance of the AIAS-4. Methods: A cross-sectional design was employed by administering a self-report questionnaire to a sample of 407 university students (63.1% female; mean age = 21.93 years). The undergraduates were enrolled at ten higher education institutions in Andalusia, Spain, and completed an online questionnaire in spring 2025. Results: The study provided psychometric validation of the AIAS-4 in a sample of Spanish undergraduates, providing descriptive information about attitudes towards AI that could inform the design of programs promoting positive use and discouraging risky and deviant behaviours. The invariance analyses showed gender invariance at the configural and metric levels, with no differences in the resulting factor nor in the factor loadings of the indicators. Differences were found at a scalar and strict levels, resulting in differences in both intercepts and residuals. Thus, measurement bias may explain that women reported most sceptical attitudes towards AI and especially concerning that AI will improve our lives. Discussion: Gender-sensitive instruments should be designed in order to prevent measurement bias. This research emphasised the need for effective interventions to foster positive attitudes towards AI and encourage critical and ethical use among male and female higher education students.

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