Foundation for Technology Assessment TA-SWISS
Ein molekulares Skalpell für Eingriffe am Erbgut: Chancen und Risiken des Genome Editings (in German)
Genome Editing – auch «Genomchirurgie» genannt – nutzt den zelleigenen Reparaturmechanismus am Genom, um dieses zu verändern. Damit ermöglicht es präzisere Eingriffe in die Erbsubstanz als die herkömmliche Gentechnik. Die hier vorliegende Kurzfassung basiert auf einer wissenschaftlichen Studie, die im Auftrag von TA-SWISS durchgeführt wurde.
Authors: Alexander Lang, Armin Spök, Malte Gruber, Dominik
Harrer, Caroline Hammer, Florian Winkler, Lukas
Kaelin, Helmut Hönigmayer, Andrea Sommer, Milena
Wuketich, Michael Fuchs, Erich Griessler
Swiss Academies of Arts and Sciences a+
STEM 2026: Where Switzerland stands today
Twelve years on from the first STEM Youth Barometer, the new 2026 edition reveals that interest in STEM has remained largely stable, stereotypes persist, and women underestimate their own abilities. At the same time, the findings are more nuanced than expected and point to clear areas for improvement.
Swiss Academy of Sciences SCNAT
Beyond the transaction: commodity trade and sustainable development
This factsheet maps the sustainability links of commodity trade, identifies knowledge gaps, and outlines options for commodity hubs, including Switzerland, to reduce economic, environmental and social sustainability risks.
Swiss Young Academy SYA
Impact of AI on Early Career Researchers: Challenges, Opportunities and Responsibilities
Artificial Intelligence (AI) is rapidly transforming science and is therefore profoundly reshaping the work of Early Career Researchers. Against this backdrop, the publication Impact of AI on Early Career Researchers: Challenges, Opportunities, and Responsibilities, developed by members of the Swiss Young Academy, namely Emmanuel Senft, Sabrina H. Kessler, Pamela Delgado, Devi Bühler, and Alexandre Bovet, offers a timely interdisciplinary reflection on these changes. The booklet examines both the opportunities and risks of AI across five key areas – research, teaching, science communication, policymaking, and sustainability – while also addressing critical issues such as research integrity, data privacy, misinformation, governance, and environmental impact. It further highlights the responsibilities of Early Career Researchers and higher education institutions in promoting AI literacy, transparency, ethical standards, and responsible use of AI in science.