Promises and Problems of AI Chatbots for Survey Research |
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| Coordinator 1 | Mrs Anna Lena Fehlhaber (Leibniz University Hannover) |
| Coordinator 2 | Dr Ivar Krumpal (University of Leipzig) |
| Coordinator 3 | Dr Anatol-Fiete Näher (Hasso-Plattner-Institut Potsdam) |
The advent of artificial intelligence (AI) and natural language processing (NLP) technologies is revolutionizing data collection methodologies, particularly in the realm of survey interviews.
Traditional surveys rely on standardized questionnaires with logic-based branching, where specific responses trigger subsequent questions. This structured approach ensures consistency and comparability of data but may lack flexibility and adaptability.
Human interviewers offer more adaptability but introduce their own challenges, such as personal biases and inconsistencies in question delivery. Moreover, participants might alter their responses due to perceived social desirability when interacting with human interviewers, affecting data reliability and validity.
AI chatbots present a promising alternative by combining the standardization of traditional surveys with the adaptability of human interviewers. They offer enhanced anonymity, potentially leading to more candid responses and reducing social desirability bias. The automated nature of AI chatbots ensures consistency in questioning, further mitigating interviewer-related biases. Advanced NLP algorithms enable these chatbots to dynamically adapt to the flow of conversation, providing a more natural and engaging interview experience for survey research.
In this session, we invite presentations that explore the innovative use of AI chatbots in survey data collection. We welcome contributions on the following topics:
1. Technical Aspects: Training and fine-tuning AI chatbots for autonomous interview settings.
2. Ethical Considerations: Addressing ethical issues and data privacy in deploying AI for data collection.
3. Comparative Studies: Empirical findings comparing AI-conducted interviews with traditional methods.
4. Practical Applications: Integrating AI chatbots within existing research frameworks.
As we navigate the intersection of AI and survey research, it is crucial to understand the implications of these technological advancements. This session aims to provide a platform for sharing insights and fostering discussions on the future of AI-driven data collection.