Exploring Gen Z's Ambivalent Relationship to AI 

Role: Principal Investigator with Research Team                                                 

Timeline: 2026-present

 

Public discourse often assumes that adolescents and young adults are enthusiastic adopters of AI, particularly readily accessible large language models (LLMs). This research challenges that assumption by investigating the sources and forms of AI skepticism among Gen Z. Focusing on the lived experiences of 18- to 28-year-olds with generative AI tools, recommendation systems, and AI-mediated social interactions, the study explores why many members of Gen Z—even those who use AI to support their studies, work, and social lives—also express deep skepticism about its growing presence in everyday life. The research aims to provide a nuanced understanding of the opportunities and limits of AI adoption among a generation widely regarded as its earliest adopters.

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Key Questions

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• How do members of Generation Z perceive artificial intelligence across different domains, including education, creativity, work, social interaction, and everyday decision-making?

• What experiences contribute to trust, skepticism, or outright resistance toward AI systems?

• How do concerns about authenticity, privacy, bias, misinformation, environmental impact, surveillance, and employment shape attitudes toward AI?

• Under what circumstances do young people view AI as helpful, and when do they perceive it as intrusive, deceptive, or socially undesirable?

• How can organizations design AI systems that better align with the expectations, values, and concerns of younger users?

 

Methodology

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The research adopts a qualitative, user-centered approach that combines in-depth interviews with digital elicitation techniques to examine how participants encounter, interpret, and evaluate AI technologies in everyday life. Rather than measuring attitudes through surveys alone, the study explores the reasoning, experiences, and social contexts that shape participants' perspectives. Particular attention is given to the relationship between stated opinions and actual patterns of AI use, revealing how skepticism and adoption frequently coexist.

 

Study Design

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• In-depth interviews: Participants engage in one-on-one interviews exploring their experiences with AI across education, work, creativity, communication, and everyday life. Interviews examine patterns of AI use alongside broader questions of trust, authenticity, perceived value, and technological change.

• Digital elicitation: Participants share examples of AI-generated content, conversations, recommendations, prompts, and outputs they have encountered or created, using these artifacts to ground discussion in real-world experiences rather than abstract opinions.

• Technology walkthroughs: Participants demonstrate AI tools they regularly use—or deliberately avoid—and explain how they decide when, why, and whether to rely on AI in different contexts.

• Scenario exploration: Participants respond to realistic scenarios involving AI in areas such as learning, employment, relationships, creativity, and decision-making, allowing the research team to examine how attitudes shift across contexts and use cases.

• Follow-up interviews: A subset of participants reconnect with the research team several months later to explore how their perceptions and patterns of AI use evolve as technologies continue to develop and become integrated into everyday life.

 

Sampling 

 

Participants between the ages of 18 and 28 are being recruited from diverse educational, occupational, and social backgrounds. Rather than seeking statistical representation, the study prioritizes variation in AI experience, technological fluency, and patterns of use. Sampling is designed to capture a broad spectrum of perspectives, from enthusiastic adopters to active skeptics, allowing recurring themes and points of divergence to emerge across interviews.​​

 

Key Insights (emerging)

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• AI skepticism among teens and young adults is widespread: Even among highly technologically literate young adults, many appear to adopt AI tools, including accessible LLM platforms, selectively and reluctantly.

• Trust is highly contextual: participants often embrace AI for efficiency while rejecting it for tasks involving creativity, learning, relationships, or personal identity.

• Application matters: Participants distinguish between using AI as a support tool and allowing AI to replace human judgment or expertise.

• Transparency matters: Transparency and user control strongly influence perceptions of legitimacy and trustworthiness.

• Negative attitudes toward AI are shaped not only by the technology itself but also by broader concerns about corporate power, surveillance, environmental costs, labor displacement, and the erosion of human creativity.

• Many participants simultaneously use AI extensively while expressing significant reservations about its long-term social consequences, illustrating that adoption and skepticism often coexist.

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Impact

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The findings of this study will be shared in future publications and presentations. 

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