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A Case Study on Assessing AI Assistant Competence in Narrative Interviews.

Chitat Chan1, Yunmeng Zhao1, Jiahui Zhao1

  • 1Social Work, Hong Kong Baptist University, Hong Kong, Hong Kong.

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|November 18, 2024
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Summary
This summary is machine-generated.

This study explored AI

Keywords:
Artificial IntelligenceConversational AIDigital Research MethodologiesNarrative InquiryPrompt EngineeringQualitative ResearchWhatsApp Interviews

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Area of Science:

  • Social Sciences
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • AI's role is expanding beyond data analysis to social research interaction.
  • The impact of AI on narrative interviews, a collaborative data collection method, remains underexplored.
  • Effective narrative interviewing requires interviewer skills like empathy and structured questioning.

Purpose of the Study:

  • To investigate the potential of AI in conducting narrative interviews.
  • To evaluate AI's performance in maintaining interview structure, empathy, and narrative quality.
  • To assess the utility of observation-based metrics for non-technical researchers evaluating AI-driven interviews.

Main Methods:

  • A case study using an OpenAI Assistant on WhatsApp to conduct narrative interviews.
  • A participant shared a story twice: once standard, once deliberately deviating.
  • AI performance evaluated via conversation analysis and narrative indicators (structure, empathy, coherence, agency support).

Main Results:

  • The AI demonstrated adaptability and structure maintenance in conversations.
  • Findings illustrate AI's potential for personalized and flexible narrative interviews.
  • The study successfully tested metrics for evaluating AI-driven narrative interviews.

Conclusions:

  • Observation-based metrics can help non-technical social researchers assess AI interview quality.
  • The study prompts reflection on AI's evolving role in qualitative social research.
  • Results encourage further research into AI applications for narrative data collection.