WCQR2025 Pre-Conference Panel Discussed the Qualitative Researcher’s Role in the Era of AI
February 2025 will see the 9th World Conference on Qualitative Research (WCQR2025). An online panel discussion on the topic “Redefining the Qualitative Researcher’s Role in the Era of AI and Digital Innovations” took place in the lead-up to the event.
Moderated by Grzegorz Bryda, a leading researcher from Jagiellonian University in Poland, the panel featured distinguished speakers: Judita Kasperiūnienė, Associate Professor and Head of the System Analysis Department at Vytautas Magnus University, Lithuania; Prokopis A. Christou, Assistant Professor at the Cyprus University of Technology and editor of the book Artificial Intelligence (AI) in Social Research; and Tamara Pataki, leader of the Community Relations Team at Verbi Software, Germany.
Three key questions shaped the discussion:
- How did we conduct qualitative research before the Artificial Intelligence era?
- How are we conducting qualitative research in the current AI era?
- What will qualitative research look like when AI becomes even more advanced?
The panelists shared their experiences and insights into the evolving role of AI in research.
AI as a Tool for Research Assistance
Certified trainer for MAXQDA software Tamara Pataki shared her insights into the rapid integration of AI tools into software solutions for qualitative data analysis. She described how the initial release of ChatGPT sparked widespread interest in using AI for tasks traditionally handled manually, such as data coding and interpretation. While AI can provide summaries, suggest codes, and assist with analysis, Pataki emphasized that human oversight remains critical.
At MAXQDA, AI serves as an assistant rather than a replacement for the researcher. The software includes features like AI Assist, which allows researchers to integrate AI’s capabilities at various points in their workflow while maintaining control over the final output. She highlighted the importance of keeping AI’s contributions identifiable and flexible, ensuring that researchers can review, edit, or reject the AI’s suggestions.
Human-AI Interaction in Qualitative Research
One of the main concerns expressed during the conference was the balance between AI’s efficiency and human intuition. While AI tools can quickly process vast amounts of data, they lack the nuanced understanding that human researchers bring to their work. The discussion stressed that AI should complement human analysis, especially in initial coding and data organization tasks.
Judita Kasperiūnienė, an associate professor with a background in computer science, spoke about her personal experience using AI tools for qualitative research. She emphasized the importance of prompt engineering and iterative refinement when working with AI. According to Kasperiūnienė, AI can be a powerful tool for time-consuming processes such as data collection and preliminary coding. Still, it requires clear, well-structured prompts to deliver meaningful results.
Judita Kasperiūnienė also pointed out that researchers should never blindly trust AI’s conclusions. Reflexivity and critical thinking are essential to ensure that AI-generated results are accurate and aligned with the research objectives. She shared an example from her grounded theory research, where AI assisted in the analysis but required continuous human oversight to ensure the results were contextually appropriate
Reflexivity, bias, and ethical considerations
As AI becomes more integrated into qualitative research, questions about bias and reflexivity become more urgent. Large language models like ChatGPT, in particular, train on vast datasets that may contain inherent biases. This poses a risk of perpetuating stereotypes or producing skewed results, particularly in social research. During the discussion, Prokopis Christou, an assistant professor at the Cyprus University of Technology, emphasized the importance of understanding AI’s limitations. While AI can process data efficiently, it is ultimately a product of its training data and cannot replace the researcher’s critical reflection. He warned against the “deification” of AI, urging researchers to remain vigilant and not overly rely on AI tools for analysis.
Ethical considerations were also a key topic, with panelists discussing how researchers must ensure that AI tools comply with data privacy regulations and that research participants give informed consent when AI systems process their data. Tamara Pataki noted that in MAXQDA, AI processes data without storing it or using it for further training, ensuring compliance with GDPR and other data protection standards.
Competencies for the Future Researcher
The evolving role of AI in research has led to a need for new competencies in the research community. Technical literacy and an understanding of AI functions now complement traditional research skills like data interpretation and coding. Panelists discussed prompt engineering—the ability to structure effective prompts for AI tools—as a crucial skill for future researchers. Additionally, the panelists highlighted iterative refinement, which involves continuously refining AI-generated outputs, as a crucial aspect of working with AI.
Researchers must critically evaluate AI’s results and understand the underlying mechanisms by which it produces them. Judita Kasperiūnienė suggested that universities should consider incorporating AI literacy into their research curricula, ensuring that future researchers can use these tools responsibly and effectively.
The Future of Qualitative Research in an AI-Driven World
Looking forward, the panelists agreed that AI will continue to play a significant role in shaping the future of qualitative research. However, the consensus was clear: AI is a tool, not a replacement for the researcher. Human intuition, critical thinking, and ethical considerations must remain at the forefront of qualitative research methodologies. As AI technology advances, researchers will likely see new methods and tools emerge, enabling more sophisticated data analysis, visualization, and theory development. However, the researcher’s role—as the ultimate interpreter of data—will remain indispensable.
In conclusion, the pre-conference set the stage for deeper discussions at the upcoming World Conference on Qualitative Research (wcqr.ludomedia.org). The integration of AI into research holds enormous promise, but its success depends on the researcher’s ability to critically engage with the tools at their disposal. By combining AI’s efficiency with human insight, the future of qualitative research looks promising and expansive.
Note: Based on transcriptions from Zoom, ChapGPT 4o synthesized this text; António Pedro Costa and Sónia Mendes verified it; and the four pre-conference panelists validated it.
RELATED EVENTS
9th World Conference on Qualitative Research (WCQR2025)
4 to 6 February 2025 – Kraków (Poland)
11 to 13 February 2025 – Online
Call for Abstracts and Panel Discussions open
