How Is AI Affecting Open Research?

As open research moves closer to the mainstream, it is also responding to broader changes in technology and the research ecosystem. Uses of generative AI—to synthesize data, write academic papers and create funding applications—challenge the status quo, even as the tools bring gains in accessibility and efficiency. How can young scientists take on practices that align with open research goals for outputs that are findable, accessible, reusable and interoperable while still working within traditional measures of academic success?

To provide insight and practical advice, we talk to two experts in open science with expertise in teaching, research, publishing and policy.

Julia Priess-Buchheit is a professor and researcher at Kiel University in Germany and, since 2018, scientific director and chair of the board of the Centre for Constructive Science. Priess-Buchheit has provided scientific advice to international and European initiatives, including the Global Research Initiative on Open Science and the European Open Science Cloud Association. In June, the report she co-authored with a large interdisciplinary team, “Open Science and the Effects of Generative Artificial Intelligence in Scientific Exchange,” was presented at the meeting of the Panel for the Future of Science and Technology at the European Parliament. 

Sarahanne Field is an assistant professor in pedagogy at the University of Groningen in the Netherlands. With a background in psychology and metascience, she teaches on ethics, research practice, scientific knowledge production and its relationship to society, as well as qualitative research methods. Field is editor in chief of the open-access Journal of Trial and Error. 

To learn more about how to foster an open research culture, head to our latest spotlight guide.

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