AI-Image Generation in Research Interviews: Opportunities and Challenges

Drawing on our experience developing a visual polyvocal narrative of the immigration system in Canada and Brazil, we explore the role of artificial intelligence (AI) image generation as a tool for supporting interview participants in articulating their experiences. We found that the AI image generation process supported participants’ ability to reflect and express their experiences. However, there were several challenges due to technological limitations and inherent biases embedded in the AI, which resulted in unsatisfactory images and repeated image generation attempts. We came to conceptualize the AI image generation tool as a third agent in the interview process, facilitating access to artistic expression yet introducing content into the conversation. We identified five primary roles played by the AI image generation tool in the interview process: Helper (supported the image generation process), Distractor (transferred attention from the topic of study to prompt engineering), Motivator (motivated participants to better articulate their vision), Influencer (introduced content in the conversation), and Facilitator (facilitated reflection and sensemaking). We discuss avenues for maximizing the benefits of AI image generation in interviewing and mitigating its challenges. We contribute to a growing body of research on reflective and arts-based interventions in interviewing by illustrating the role new technologies can play in advancing the potential of interview-based research.

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Publication Details

Journal
International Journal of Qualitative Methods
Published
2025-04-01
DOI
https://doi.org/10.1177/16094069251333335
Citations
4
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
2.62

Funders

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article

AI-Image Generation in Research Interviews: Opportunities and Challenges

Luciara Nardon, Camila Brüning, Manuela Busato, Sasha Valgardsson
4 citations
International Journal of Qualitative Methods
Artificial Intelligence in Healthcare and Education
2.62
article

AI-Image Generation in Research Interviews: Opportunities and Challenges

Luciara Nardon, Camila Brüning, Manuela Busato, Sasha Valgardsson
article en
4 citations

Abstract

Drawing on our experience developing a visual polyvocal narrative of the immigration system in Canada and Brazil, we explore the role of artificial intelligence (AI) image generation as a tool for supporting interview participants in articulating their experiences. We found that the AI image generation process supported participants’ ability to reflect and express their experiences. However, there were several challenges due to technological limitations and inherent biases embedded in the AI, which resulted in unsatisfactory images and repeated image generation attempts. We came to conceptualize the AI image generation tool as a third agent in the interview process, facilitating access to artistic expression yet introducing content into the conversation. We identified five primary roles played by the AI image generation tool in the interview process: Helper (supported the image generation process), Distractor (transferred attention from the topic of study to prompt engineering), Motivator (motivated participants to better articulate their vision), Influencer (introduced content in the conversation), and Facilitator (facilitated reflection and sensemaking). We discuss avenues for maximizing the benefits of AI image generation in interviewing and mitigating its challenges. We contribute to a growing body of research on reflective and arts-based interventions in interviewing by illustrating the role new technologies can play in advancing the potential of interview-based research.

International Journal of Qualitative MethodsVol. 24
Universidade Federal do Paraná (BR), Carleton University (CA)
Carleton University, Mitacs, Universidade Federal do Paraná
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
2.62
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