PERSPECTIVE article
Front. Res. Metr. Anal.
Sec. Research Methods
Volume 10 - 2025 | doi: 10.3389/frma.2025.1519008
This article is part of the Research TopicEthical Artificial Intelligence: Methods and ApplicationsView all articles
The online survey as a qualitative research tool: Can AI be a probing tool?
Provisionally accepted- Teesside University, Middlesbrough, United Kingdom
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Surveys are commonly associated with quantitative methods, yet there is growing recognition of their potential to yield qualitative insights into complex social phenomena. However, the effectiveness of open-ended survey questions is often limited by issues such as respondent fatigue and low-quality responses. To address these limitations, researchers are increasingly exploring the use of artificial intelligence (AI) to support dynamic survey design, probing questions, and participant engagement.This article explores the role of qualitative surveys in social science research, by considering their alignment with qualitative paradigms. The content assesses how AI-powered features, such as machine learning and chatbot-driven interfaces, can enhance data collection through adaptive questioning. The article also discusses key challenges related to data quality, participant inclusivity, and ethical considerations.Particular attention is given to the concept of "felt anonymity" in online surveys, which can encourage candid disclosures on sensitive topics and broaden participation across diverse populations. When designed with ethical and methodological care, qualitative surveys can thus serve as powerful tools for accessing underrepresented perspectives. By integrating AI into qualitative survey design, researchers can enhance both the richness and reach of their data. This article argues that AI-powered qualitative surveys, especially those capable of dynamic probing, offer a promising hybrid approach, bridging the scalability of surveys with the responsiveness of interviews, and calls for further empirical study of their ethical and epistemological implications.
Keywords: Qualitative survey, question design, Research Design, artificial intelligence, Survey
Received: 29 Oct 2024; Accepted: 18 Aug 2025.
Copyright: © 2025 Williams. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ryan Thomas Williams, Teesside University, Middlesbrough, United Kingdom
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