Conducting Qualitative Interviews with AI

Felix Chopra, Ingar Haaland and Ingar K. Haaland
Authors registered in the RePEc Author Service: Ingar Haaland

No 10666, CESifo Working Paper Series from CESifo

Abstract: We introduce a new approach to conducting qualitative interviews by delegating the task of interviewing human subjects to an AI interviewer. Our AI interviewer conducts 381 interviews with human subjects about their reasons for not participating in the stock market. The AI-conducted interviews uncover rich evidence on the underlying factors influencing non-participation in the stock market. Among our main qualitative findings is a prominent role for an active investing mental model. A separate large-scale survey shows that this mental model differs systematically between stock owners and non-owners. We also document systematic differences between factors identified in initial top-of-mind responses and those uncovered in subsequent responses, with mental models consistently emerging later in the interviews. Finally, a follow-up study shows that the interview data predicts economic behavior eight months after being collected, mitigating concerns about “cheap talk” in interviews. Our results demonstrate that AI-conducted interviews can generate rich, high-quality data at a fraction of the cost of human-led interviews.

Keywords: artificial intelligence; interviews; large language models; qualitative methods; mental models; stock market participation; surveys (search for similar items in EconPapers)
JEL-codes: C83 C90 D14 D91 Z13 (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-cmp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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