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This study explores the use of generative AI (GenAI) and research integrity assessments of use cases by researchers, including PhD students, at Danish universities. Conducted through a survey sent to all Danish researchers from January to February 2024, the study received 2,534 responses and evaluated 32 GenAI use cases across five research phases: idea generation, research design, data collection, data analysis, and writing/reporting. Respondents reported on their own and colleagues' GenAI usage. They also assessed whether the practices in the use cases were considered good research practice. Through an explorative factor analysis, we identified three clusters of perception: "GenAI as a work horse", "GenAI as a language assistant only", and "GenAI as a research accelerator". The findings further show varied opinions on GenAI's research integrity implications. Language editing and data analysis were generally viewed positively, whereas experiment design and peer review tasks faced more criticism. Controversial areas included image creation/modification and synthetic data, with comments highlighting the need for critical and reflexive use of GenAI. Usage differed by main research area, with technical and quantitative sciences reporting slightly higher usage and more positive assessments. Junior researchers used GenAI more than senior colleagues, while no significant gender differences were observed. The study underscores the need for adaptable, discipline-specific guidelines for GenAI use in research, developed collaboratively with experts to align with diverse research practices and minimize ethical and practical misalignment. • Survey of Danish academic researchers reveals three main perceptions of GenAI in research: "work horse," "language assistant only," and "research accelerator." • Language editing and data analysis tasks seen as positive uses; experiment design and peer review more controversial. • Technical fields and junior researchers report higher GenAI usage, with no gender differences. • GenAI usage is still restricted to a limited number of use cases, with more intensive use associated with more positive attitudes. • Factor analysis shows varied comfort levels with GenAI in terms of research integrity based on research roles and tasks.
Andersen et al. (Wed,) studied this question.