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Abstract

Chatbots based on large language models present a scalable and consistent alternative to human interviewers for collecting qualitative data. In this paper, we introduce the agentic chatbot “Interview Bot”, designed to mimic human adaptability and empathy in an interview setting. We explore to what extent it can handle the nuances and open-ended nature of ethnographic interviews. Our findings indicate that chatbots can engage participants and collect meaningful data, but that they still sometimes fall short of fully replicating human facilitated interviews. Not withstanding challenges with the current state of the art, in the medium term, LLM-based agents hold great potential for scaling qualitative research beyond the confines of geographical, cultural, and language boundaries.

Original languageEnglish
JournalInternational Conference on Agents and Artificial Intelligence
Volume1
Pages (from-to)702-709
Number of pages8
ISSN2184-3589
DOIs
Publication statusPublished - 2025
Event17th International Conference on Agents and Artificial Intelligence, ICAART 2025 - Porto, Portugal
Duration: 23. Feb 202525. Feb 2025

Conference

Conference17th International Conference on Agents and Artificial Intelligence, ICAART 2025
Country/TerritoryPortugal
CityPorto
Period23/02/202525/02/2025

Bibliographical note

Publisher Copyright:
© 2025 by SCITEPRESS– Science and Technology Publications, Lda.

Keywords

  • Interviews
  • Large Language Models
  • LLM Agents
  • Prompt Engineering
  • Qualitative Research

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