Using Generative Artificial Intelligence (GenAI) across different Research Phases – Cases, Potential and Risks
DOI:
https://doi.org/10.7146/cfasr.v15i3.157222Keywords:
Generative Artificial Intelligence (GenAI), Research Process, Potential, Risks, Research Integrity, Disciplinary differencesAbstract
This report examines the integration of Generative Artificial Intelligence (GenAI) across the research process. Through a literature review and expert interviews, it examines GenAI applications in five research phases: idea generation and funding, research design, data collection, data analysis, and scientific publishing. The findings reveal that while GenAI offers universal benefits for tasks like literature reviews, translation, and writing assistance, its utility for data collection and analysis varies significantly across disciplines based on methodological approaches and epistemic cultures. The report concludes that effective GenAI implementation requires discipline-specific strategies developed through collaborative efforts among researchers, funders, and publishers. It emphasizes balancing the increased speed of knowledge production with maintaining research quality and addressing resource implications of widespread GenAI adoption in academia.
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