Ethical Considerations for Learning to Use Artificial Intelligence in Qualitative Health Research

Area of Science:

• Qualitative Health Research
• Bioethics
• Health Informatics

Background:

• Artificial intelligence (AI) tools are increasingly integrated into qualitative health research, promising enhanced efficiency and novel insights.
• The rapid adoption of AI technologies, including videoconferencing, transcription services, and analysis tools, presents emerging ethical challenges.
• These ethical dilemmas require careful navigation, particularly for researchers in training who are early adopters of AI.

Purpose of the Study:

• To identify and analyze the ethical issues associated with the use of artificial intelligence in qualitative health research.
• To map specific ethical values—autonomy, privacy, validity, and equity—to decision points in the AI research process.
• To provide a framework for researchers to navigate the ethical use of AI tools in qualitative health research.

Main Methods:

• Systematic review of ethical considerations in AI application within qualitative health research.
• Mapping of AI integration points in the research lifecycle to core ethical values.
• Development of a decision-making framework for ethical AI use in qualitative health research.

Main Results:

• AI integration in qualitative health research introduces complex ethical issues impacting autonomy, privacy, validity, and equity.
• Ethical decision points arise at various stages, from data collection using AI-driven tools to AI-assisted analysis.
• A framework is proposed to guide researchers in addressing these ethical challenges.

Conclusions:

• The integration of AI in qualitative health research necessitates a proactive approach to ethical oversight.
• Researchers must critically evaluate AI tools against core ethical principles to ensure responsible innovation.
• Developing and implementing ethical frameworks are crucial for navigating the complexities of AI in health research.