Qualitative Research with AI¶
Qualitative research with AI examines how AI tools can assist with traditionally qualitative research methods — from interview coding to thematic analysis — while preserving the interpretive richness that defines qualitative inquiry.
Context & Background¶
AI tools offer several capabilities relevant to qualitative research:
- Interview transcription: Converting audio to text with high accuracy
- Thematic coding: Identifying and categorizing themes in text data
- Pattern recognition: Finding recurring concepts across interview transcripts
- Memo generation: Drafting analytical memos from coded data
- Translation: Working with multilingual qualitative data
Practical Implications¶
- Use AI for coding assistance, not replacement: AI can suggest codes, but human interpretation remains essential
- Validate AI coding: Compare AI-generated codes against your own for a subset of data
- Leverage speed for iteration: AI enables more rounds of coding and refinement
- Be transparent: Report AI involvement in qualitative analysis methods sections
Key Sources¶
- The Train Has Left the Station: Agentic AI and the Future of Social Science Research
- Jesus Fernandez-Villaverde Thread: Twelve Arguments for Traditional Higher Education
- Project Management with AI
- AI Agents & Agentic AI
- Agents vs Skills