Child and Adolescent Cultural-Social Research

Child and Adolescent Cultural-Social Research

Adolescents’ Engagement with Generative AI Responses and the Process of Judgment Regarding Social Issues: A Qualitative Study in Karaj

Document Type : Original Article

Author
Yaghoub Moradian
Ph.D. student in Communication Sciences, Faculty of Culture and Communication, Soore International University, Tehran, Iran. Email: y.moradian@soore.ac.ir
10.22083/cssca.2026.597066.1118
Abstract
Introduction: Generative artificial intelligence (GenAI) is increasingly becoming part of adolescents’ social knowledge environment rather than merely a tool for retrieving information. Through conversational systems, adolescents can ask about social relationships, justice, inequality, identity, institutions, and future possibilities and receive coherent, context-sensitive responses. In this study, social reality refers to the interpretations and judgments that adolescents construct about social actors, relationships, institutions, norms, inequalities, and the social future. Such understandings are formed and revised through lived experience, interaction, and comparison across multiple sources. GenAI introduces a new communicative and epistemic mediator because its generated responses may not only provide information but also frame and interpret social issues. Existing research has focused mainly on AI literacy, educational applications, misinformation, trust, and cognitive dependence. Less attention has been paid to how adolescents engage with AI-generated responses to social issues, assess their credibility, and make judgments when sources converge or conflict. Accordingly, this study examines adolescents’ engagement with GenAI responses and their processes of judgment regarding social issues in Karaj.
Methods: The study adopted a qualitative approach and employed thematic analysis. The research was conducted in Karaj, Iran, and data were collected in 1405 SH. Participants were 23 adolescents aged 15–18 years with direct experience using GenAI systems. Purposive, criterion-based sampling was employed, with attention to variation in age, gender, socioeconomic background, and patterns of GenAI use. The sample included adolescents from all four age groups, with variation in gender and socioeconomic background. Data were collected through 23 face-to-face semi-structured interviews lasting 30–45 minutes. The interview guide addressed engagement with social issues, responses generated by AI systems, credibility assessment, and judgment when sources converged or conflicted. Interviews were recorded with participants’ consent and fully transcribed. Data analysis followed Braun and Clarke’s six-phase approach and was conducted primarily inductively at the semantic level. No specialized qualitative analysis software was used; coding was performed manually in Microsoft Word. The conceptual framework integrated the social construction of reality, mediated construction of reality, epistemic vigilance, and epistemic agency, functioning as a sensitizing framework rather than imposing predetermined themes. Trustworthiness was enhanced through comparison with raw data, selected member checking, peer review, documentation of analytical decisions, and attention to discrepant cases. Ethical principles included informed consent, confidentiality, anonymity, and the right to withdraw from the study.
Findings: The analysis yielded five interconnected themes: “dialogic interaction and cognitive reframing,” “expansion and revision of the social horizon,” “grounding understanding in lived experience,” “multi-criteria and cross-source credibility assessment,” and “situated judgment and preservation of epistemic agency.” Dialogic interaction enabled adolescents to clarify ambiguities, request simpler explanations or examples, and organize fragmented knowledge. Generated responses could broaden adolescents’ social horizons by introducing alternative perspectives and prompting them to reconsider previous assumptions. However, these responses did not occupy a fixed or authoritative position; their meaning and credibility were interpreted in relation to prior knowledge, lived experience, and other sources of social knowledge.
Lived experience functioned as an interpretive context rather than as a definitive criterion of truth. Adolescents compared AI-generated responses with experiences from family, school, neighborhood, and everyday life, and discrepancies often prompted further questioning. Credibility assessment involved source transparency, traceability of evidence, internal coherence, confirmation through independent sources, acknowledgment of uncertainty, and balance across viewpoints. Fluent language or confident presentation alone was not considered sufficient grounds for acceptance.
Judgment became particularly visible when AI-generated responses converged with or conflicted with other sources. Convergence generally increased confidence without producing absolute certainty. Conflict could lead to suspension of judgment, context-dependent weighting of sources, consultation with trusted individuals, cross-source comparison, integration of more credible elements, or provisional judgment. Within-group comparisons suggested that requests for explanations and examples were more prominent in some accounts from 15- and 16-year-olds, whereas attention to multiple perspectives, structural factors, multi-source credibility assessment, and maintaining an open judgment appeared more prominently in some accounts from 17- and 18-year-olds. These patterns should not be interpreted as fixed age-based differences, and no clear recurring pattern was identified in relation to gender or socioeconomic background. The integrated interpretation was “situated epistemic agency,” referring to adolescents’ active yet context-dependent role in questioning, assessing, comparing, suspending judgment, and revising their positions.
Keywords
Social Reality
Generative Artificial Intelligence
Social Understanding
Credibility Assessment
Epistemic Agency
Adolescents
Subjects
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Child and Adolescent Cultural-Social Research
Volume 3, Issue 3 - Serial Number 10
Autumn 2026
Pages 171-205