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 generat...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-04-01
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| Series: | International Journal of Qualitative Methods |
| Online Access: | https://doi.org/10.1177/16094069251333335 |
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| author | Luciara Nardon Camila Brüning Sasha Valgardsson Manuela Busato |
| author_facet | Luciara Nardon Camila Brüning Sasha Valgardsson Manuela Busato |
| author_sort | Luciara Nardon |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c6d0fa64fbe04a1085c682c1e19f5458 |
| institution | OA Journals |
| issn | 1609-4069 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Qualitative Methods |
| spelling | doaj-art-c6d0fa64fbe04a1085c682c1e19f54582025-08-20T01:48:29ZengSAGE PublishingInternational Journal of Qualitative Methods1609-40692025-04-012410.1177/16094069251333335AI-Image Generation in Research Interviews: Opportunities and ChallengesLuciara NardonCamila BrüningSasha ValgardssonManuela BusatoDrawing 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.https://doi.org/10.1177/16094069251333335 |
| spellingShingle | Luciara Nardon Camila Brüning Sasha Valgardsson Manuela Busato AI-Image Generation in Research Interviews: Opportunities and Challenges International Journal of Qualitative Methods |
| title | AI-Image Generation in Research Interviews: Opportunities and Challenges |
| title_full | AI-Image Generation in Research Interviews: Opportunities and Challenges |
| title_fullStr | AI-Image Generation in Research Interviews: Opportunities and Challenges |
| title_full_unstemmed | AI-Image Generation in Research Interviews: Opportunities and Challenges |
| title_short | AI-Image Generation in Research Interviews: Opportunities and Challenges |
| title_sort | ai image generation in research interviews opportunities and challenges |
| url | https://doi.org/10.1177/16094069251333335 |
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