EP 525: AI-Informed, Human-Led: Thoughtful AI Use in Qualitative Research
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EP 525: AI-Informed, Human-Led: Thoughtful AI Use in Qualitative Research
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About this listen
AI is shaking up qualitative research: speeding things up, cleaning messy transcripts, and even identifying hidden patterns.
Sounds amazing, right?
Buuuuuuuut there’s a catch.
When does AI go from helpful assistant to heavy-handed editor, scrubbing out the human insights qualitative research was built on?
In this episode of Everyday AI, we're tackling how to balance AI-powered qualitative research without losing touch with human nuance.
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Topics Covered in This Episode:
- Importance of Qualitative Research Training
- Challenges in AI-Assisted Qualitative Research
- AI's Role in Data Transcription
- Human-Led Analysis in Qualitative Research
- AI's Impact on Data Accessibility
- Limitations of AI in Qualitative Analysis
- Future of AI and Qualitative Research
- Critical Thinking in AI-Assisted Research
Timestamps:
00:00 PhD and Qualitative Research Training
05:07 "Qualitative Research and Multiple Narratives"
08:04 AI in Research: Balancing Automation
09:57 AI-Assisted Data Analysis Caution
16:23 AI's Impact on Qualitative Research
19:19 Analyzing Qualitative Data Interpretation
25:11 Balancing AI in Qualitative Research
Keywords:
Qualitative research, qualitative researcher, AI use in research, AI in qualitative research, AI-informed, human-led, thoughtful AI use, research impacts, health psychology, apprentice plumber analogy, training for PhD students, data analysis, transcribing interviews, transcription time, structured versus unstructured data, meaning making, words as data, interpretive work, subjective interpretation, data set analysis, line by line coding, thematic analysis, story telling in research, ensuring rigor in research, critical thinking in research, efficiency in research processes, literature gap identification, data visualization, AI as an intern, sharing research findings with lay audience, implicit meaning in data, biases in models, accessibility of academic work, academic pressure to publish, research dissemination, insights from research, qualitative research processes, interpretation in qualitative research.
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