Generative AI is transforming knowledge production in research – rapidly, profoundly, and not without conflict. In their article, Kimon Kieslich (University of Amsterdam) and Josephine B. Schmitt (Center for Advanced Internet Studies) analyze the challenges arising from the increasing integration of generative AI into academic work processes.
The basis for their analysis is a workshop held at CAIS in December 2024, during which researchers from various disciplines developed future scenarios regarding the role of AI in science. These scenarios clearly show: the use of generative AI is often a response to structural pressures – such as overload, temporary employment, or dependence on third-party funding.
But this relief comes at a cost. Inaccuracies, synthetic data, ethical gray areas, and a potential alienation between science and society are real risks. The authors therefore call for clear ethical guidelines, stronger institutional responsibility, and a fundamental reform of academic work culture.
The paper is available here:
Kieslich, K. & Schmitt, J. B. (2025). “But what is the alternative?!” – The impact of generative AI on academic knowledge production in times of science under pressure. Internet Policy Review. https://policyreview.info/articles/news/what-alternative-impact-generative-ai-academic-knowledge-production-times-science