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Navigating artificial intelligence in qualitative research: ethical and practical considerations from concept to
Tyra Girdwood1, Lydia Manikonda2
1The University of Tennessee Health Science Center College of Nursing, Memphis, TN, United States.
Frontiers in Research Metrics and Analytics
|July 3, 2026
Summary
Artificial intelligence (AI) offers tools for qualitative research but raises ethical concerns. This paper synthesizes recommendations for AI use in qualitative research to ensure rigor and reproducibility.
Area of Science:
- Social Sciences
- Computer Science
- Research Methodology
Background:
- The integration of artificial intelligence (AI) into qualitative research presents both opportunities and significant challenges.
- Existing AI techniques for qualitative analysis are evolving, raising concerns about data privacy, ethical considerations, and the potential for inaccurate outputs (hallucinations).
Purpose of the Study:
- To address the emerging ethical and practical challenges of using AI in qualitative research.
- To provide a synthesis of recommendations for the responsible application of AI across the qualitative research process.
Main Methods:
- Identification of key ethical and practical concerns associated with AI in qualitative research.
- Development of recommendations tailored to five distinct stages of the qualitative research lifecycle.
Main Results:
- AI tools can assist in qualitative research but necessitate careful consideration of potential risks.
- Specific concerns include AI's predictive capabilities potentially violating privacy and generating unreliable outputs.
Conclusions:
- Researchers and stakeholders need guidance to safely integrate AI into qualitative methodologies.
- Implementing strategic recommendations can mitigate risks, enhance rigor, and ensure the reproducibility of AI-assisted qualitative research.
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