Embracing AI in qualitative research, thoughtfully and responsibly
발표자 Henri Schildt46 minutes

Embracing AI in qualitative research, thoughtfully and responsibly

In this webcast, our CEO professor Henri Schildt discusses the approaches to AI use in qualitative research and gives three concrete ways you can leverage Skimle to support your research process.

In this webcast, Henri Schildt, professor of strategy at Aalto University and co-founder of Skimle, makes the case for using AI to augment the expert rather than replace them. He traces how AI use has moved from "AI slop" to power users to genuine super-experts, addresses the real fear of losing our craft, and argues that knowledge work is not a purely cognitive task but a social activity built around shared objects and artifacts. He then shows three concrete ways any researcher can start benefiting from Skimle today.

What you'll learn:

  • Why AI is such a controversial topic in qualitative research, and the difference between using it to augment experts versus automate them away
  • The design principles behind Skimle including: transparency, predictability, effortless control, and versatility, and why they matter for avoiding cognitive offloading
  • How to take stock of your data quickly with automatic thematic analysis, transcription, and document summaries
  • How to dig deeper into your key themes using predefined categories or agentic analysis, cross-tabulations, metadata patterns, and tags
  • How to build a compelling, defensible story, including counter-evidence

Who this is for: Qualitative researchers and academics who want to use AI thoughtfully without losing rigour or control over their analysis.

Skimle로 데이터를 더 깊이 파고드십시오

Skimle은 인터뷰, 설문 응답, 보고서 등 질적 데이터를 자동으로 수집, 분석, 분류합니다. 현대적인 질적 분석 소프트웨어로서 엄밀하고 투명한 워크플로와 AI의 속도를 결합합니다.

텍스트나 오디오를 업로드하고, Skimle Anonymise로 민감한 데이터를 제거하고, 카테고리와 하위 카테고리를 자동으로 만들고, 문서 전반의 데이터를 탐색하고, 워크플로에 매끄럽게 맞도록 데이터를 내보내십시오. 전문가가 전문가를 위해 만들었으며, 완전한 개인정보 보호와 GDPR 준수를 갖췄습니다.

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