The role of generative AI in navigating trade-offs in policy research design: balancing validity, rigour, and innovation
This study systematically examines how generative AI can assist in policy research design by analysing methodological trade-offs. Using Claude Pro, we evaluated research designs in 164 articles from leading policy journals across six dimensions: internal, external, construct, and predictive validity, methodological rigour, and conceptual novelty. The analysis demonstrates that AI can effectively identify methodological trade-offs and suggest design improvements within resource constraints, though its utility varies by research type. The findings advance our understanding of AI’s role as a complementary tool in research design while highlighting the critical importance of human expertise in methodological decisions.
Authors
- Xun Wu (ORCID: https://orcid.org/0000-0002-7518-3951)
- 栄利子 仲座
- Dale Whittington (ORCID: https://orcid.org/0000-0002-6075-8812)
- Yvonne Jie Chen (ORCID: https://orcid.org/0000-0003-4755-6025)
Institutions
- Hong Kong University of Science and Technology (HK)
- University of Manchester (GB)
- ShanghaiTech University (CN)
Publication Details
- Journal
- Journal of Asian Public Policy
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1080/17516234.2024.2425874
- Citations
- 2
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 1.05