In the AStA Wirtschafts- und Sozialstatistisches Archiv, Berger et al. (2026) demand changes to statistics education at universities.
The position paper formulates nine propositions for the further development of statistics education in the context of data science and artificial intelligence. The focus is on data and statistical literacy, data quality and ethics, the connection between statistics and machine learning, and the strengthening of an independent approach to statistics education.
The discussion contributions expand on these perspectives: Christina Elmer emphasizes science communication and AI literacy; Helmut Küchenhoff highlights project-based learning and data protection; Christoph Weisser focuses on industrial practice and organization-wide data literacy; Göran Kauermann addresses the integration of statistics and data science; and Rolf Biehler and Karin Binder discuss didactic and institutional development.
The response takes up these ideas and underscores the interdisciplinary responsibility for a sustainable statistics education.
The article can be downloaded here: link.springer.com/article/10.1007/s11943-026-00372-0
