From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis

• URL: http://arxiv.org/abs/2501.19275v1
• Date: Fri, 31 Jan 2025 16:37:19 GMT
• Title: From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis
• Authors: Elisabeth Kirsten, Annalina Buckmann, Leona Lassak, Nele Borgert, Abraham Mhaidli, Steffen Becker,
• Abstract summary: The advent of AI tools, such as Large Language Models, has introduced new possibilities for qualitative data analysis (QDA) The advent of AI tools, such as Large Language Models, has introduced new possibilities for QDA, offering both opportunities and challenges. To help navigate the responsible integration of AI into QDA, we conducted semi-structured interviews with 15 HCI researchers experienced in QDA. While our participants were open to AI support in their QDA, they expressed concerns about data privacy autonomy, and the quality of AI outputs. We developed a framework that spans from minimal to high AI involvement, providing tangible scenarios for
• Score: 2.2010811029011474
• License:
• Abstract: The advent of AI tools, such as Large Language Models, has introduced new possibilities for Qualitative Data Analysis (QDA), offering both opportunities and challenges. To help navigate the responsible integration of AI into QDA, we conducted semi-structured interviews with 15 HCI researchers experienced in QDA. While our participants were open to AI support in their QDA workflows, they expressed concerns about data privacy, autonomy, and the quality of AI outputs. In response, we developed a framework that spans from minimal to high AI involvement, providing tangible scenarios for integrating AI into HCI researchers' QDA practices while addressing their needs and concerns. Aligned with real-life QDA workflows, we identify potentials for AI tools in areas such as data pre-processing, researcher onboarding, or mediation. Our framework aims to provoke further discussion on the development of AI-supported QDA and to help establish community standards for their responsible use.

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