New Publication explores the impact of artificial intelligence on everyday scientific life

As an organization that brings together early-career researchers from a wide range of disciplines, the Swiss Young Academy is uniquely positioned to reflect critically on the implications of AI for science and society and to foster interdisciplinary dialogue on its current and future role. Developed by Emmanuel Senft, Sabrina H. Kessler, Pamela Delgado, Devi Bühler, and Alexandre Bovet, the publication examines how AI is influencing the daily practices, roles, and responsibilities of researchers, while also addressing the growing responsibilities of higher education and research institutions in light of these technological transformations. Rather than prescribing specific ways of using AI, the booklet seeks to identify and assess the impact of AI on scientists – especially early career researchers within the Swiss research ecosystem and beyond – highlighting key areas for reflection, offering recommendations for responsible engagement, and encouraging informed discussion on the present and future of AI in science.

As co-author Sabrina H. Kessler notes: “As early career researchers, we find ourselves at the forefront of a profound transformation of academic work. AI can greatly enhance our research, teaching, and communication – but only if we use it responsibly, transparently, and with a clear awareness of its risks. Our aim with this publication is to provide a foundation for exactly that: informed reflection, critical dialogue, and a shared understanding of how we can shape the future of AI in science rather than merely react to it.”

The publication explores opportunities and challenges across five central areas. In the context of research, it highlights for example how AI can significantly increase productivity through faster data analysis, automated text annotation, synthetic data generation, and accelerated literature reviews, while also raising critical issues related to data quality, overuse of AI methods and research integrity risks. In teaching, the booklet discusses how AI is transforming learning design, assessment practices, feedback mechanisms and data privacy. With regard to science communication, it examines how AI opens new possibilities for accessibility and public outreach, while simultaneously posing risks such as misinformation, automation bias, and a potential erosion of public trust. The publication further addresses the growing role of researchers in shaping evidence-based policymaking and governance, in which easier access to information for understanding the functioning of and participation in the regulatory process are becoming more important, but at the same time new legal and integrity risks and governance and regulatory challenges are associated with this. As pointed by co-author Emmanuel Senft: “Scientists across all disciplines, not only those in AI, should participate in conversations about AI’s influence on research and society. Broad, cross-disciplinary input is vital to developing regulatory frameworks that capture the full range of scientific perspectives.” The publication also reflects on the tension between the substantial environmental footprint of AI infrastructures and their potential contributions to sustainability transitions.

Two additional chapters are dedicated to responsibilities in the evolving AI landscape. One focuses on the role of early career researchers, for example emphasizing the importance of developing AI literacy, ensuring transparency in the use of AI tools, and actively participating in public discourse and regulatory processes. The other addresses the responsibilities of higher education institutions, calling for the establishment of institutional policies and ethical guidelines, the creation of incentives for responsible AI use, and the provision of training, resources, and appropriate tools to support early career researchers.

By bringing together diverse disciplinary perspectives, the publication emphasizes that early career researchers are both drivers and subjects of the profound transformations currently reshaping academia. It seeks to empower  researchers and institutions alike to engage with AI in ways that are responsible, transparent, and sustainable, and to actively shape the future of AI in science.

To the publication