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 language | English |
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Journal | International Conference on Agents and Artificial Intelligence |
Volume | 1 |
Pages (from-to) | 702-709 |
Number of pages | 8 |
ISSN | 2184-3589 |
DOIs | |
Publication status | Published - 2025 |
Event | 17th International Conference on Agents and Artificial Intelligence, ICAART 2025 - Porto, Portugal Duration: 23. Feb 2025 → 25. Feb 2025 |
Conference
Conference | 17th International Conference on Agents and Artificial Intelligence, ICAART 2025 |
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Country/Territory | Portugal |
City | Porto |
Period | 23/02/2025 → 25/02/2025 |
Bibliographical note
Publisher Copyright:© 2025 by SCITEPRESS– Science and Technology Publications, Lda.
Keywords
- Interviews
- Large Language Models
- LLM Agents
- Prompt Engineering
- Qualitative Research