The Influence of Prior Perception, Attitude, and Immediate Knowledge of AI on Adolescents’ Preferences for High- and Low-Replaceable Jobs

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Authors: Huanlei Wang, Xiaoxiong Lai, Shunsen Huang, Xinran Dai, Xinmei Zhao, Yun Wang
Cited by: 0
References: 46

Abstract

While extensive research has examined adult perceptions of Artificial Intelligence (AI)’s impact on the workforce, studies focusing on adolescents—who are at a critical stage of career development—remain scarce. Drawing upon Social Cognitive Career Theory (SCCT) and the significance of fostering adolescents’ adaptability in the era of AI, we designed a questionnaire-based experiment to examine how adolescents’ prior perceptions, attitude and immediate knowledge of AI influence their career preferences. We conducted a questionnaire-based experiment with 836 adolescents (Mage = 13.98, SD = 1.35 years; 52.30% male) to investigate the influence of three independent variable groups: prior perception of AI (familiarity with AI), prior attitudes towards AI (trust in AI and positive/negative attitude towards AI) and immediate knowledge of AI (experimental manipulation). The results showed that immediate knowledge of AI significantly and negatively predicted adolescents’ preference for both low- and high-replaceable jobs. In contrast, familiarity with AI, trust in AI and positive attitude towards AI significantly and positively predicted a preference for low-replaceable jobs. This study introduces an integrated empirical framework demonstrating that distinct AI-related factors differentially influence adolescent career preferences. Results emphasize the importance of familiarity with AI, trust in AI and positive attitude towards AI among teenagers in order to better adapt the future changes in the labor market. This finding provides an empirical reference for educators and policy makers to better guide teenagers to make career plans.

Fields of Study & Subjects

Ethics and Social Impacts of AI AI in Service Interactions Career Development and Diversity

Publication details

Journal / source
Behavioral Sciences
Volume
16
Issue
1
Pages
72–72
Publication date
5 January 2026
Language
EN