#188 - Why AI Can't Replace Qualitative Research with Sam Ladner of Workday

About this episode

Erin May interviews Sam Ladner about the limitations of AI in qualitative research and the importance of human insight.

Erin May sits down with Sam Ladner, Senior Principal Researcher of Strategy at Workday, to explore the evolving role of AI in qualitative research. Sam brings a refreshingly balanced perspective on where AI can genuinely help researchers and where it fundamentally cannot replace human insight. Sam explains how AI has transformed labor-intensive tasks like transcription and closed coding, freeing researchers to focus on the deeper work of sense-making and understanding outliers. She emphasizes that while AI excels at mathematical correlation hunting, qualitative research is about unriddling complex human experiences that require thinking, feeling, and imagination. The conversation covers practical applications like using MAXQDA for AI-assisted coding, the importance of explaining every outlier in qualitative work, and why emotional storytelling must remain exclusively human territory. Highlights 03:09 Why machines can't replace human sense-making 08:47 Human moments AI cannot understand 12:00 Explaining outliers in qualitative coding 16:27 Building effective coding systems for AI 21:33 Getting AI to do closed coding properly 29:26 When to use AI for low stakes research 37:23 AI…

People in this episode

Host: Erin May

Guest: Sam Ladner

Topics covered

• AI in qualitative research
• human insight
• transcription
• coding systems
• emotional storytelling
• sense-making

Keywords

• AI
• qualitative research
• human insight
• coding
• transcription
• sense-making
• outliers
• emotional storytelling

Mentioned in this episode

Organizations: Workday

Books & works: Practical Ethnography: A Guide to Doing Ethnography in The Private Sector, Mixed Methods: A Short Guide to Applied Mixed Methods Research

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