Sarah Dégallier Rochat

What if the competitiveness of Swiss companies did not lie in replacing people, but in elevating their unique expertise?

As the limits of full automation become increasingly clear, AI and robotics should not be seen as substitutes for human talent, but as powerful amplifiers of know-how. By combining human intelligence with advanced technologies, businesses can achieve greater agility, stronger innovation, and sustainable performance — without losing what truly sets them apart: the expertise, judgment, and creativity of their people.

Rather than pursuing replacement strategies that are often disconnected from operational realities, embrace an approach where technology empowers people and unlocks their full potential.

This interactive session explores the use of AI in research through the lens of scientific integrity and the core purposes of scholarship. Rather than a one-way presentation, participants will actively reflect on their own practices, assumptions, and decision-making around AI.

We begin by examining current AI-driven research practices and identifying key integrity risks, including reproducibility, authorship, bias, and transparency, as well as the ways productivity and efficiency pressures can distort research incentives.

We reconnect AI use to the deeper purpose of research: to learn, discover, explain, and advance reliable knowledge for society, not merely to maximize outputs or metrics. Instead of prescribing a single policy, participants will work with a principled framework grounded in research integrity (reliability, honesty, respect, and accountability) to articulate and refine their own perspective on responsible AI use.

By the end of the session, participants will have developed a clearer understanding of their own values and practices, identified potential misalignments, and formulated concrete, context-sensitive approaches to using AI responsibly. They will leave with practical guidelines, real-world examples of integrity-preserving workflows, and a set of decision questions to critically evaluate AI in their own research.

Discussions about innovation, and artificial intelligence in particular, often prioritize sensationalism—viral videos, provocative predictions, scripted demonstrations—at the expense of rigorous, contextualized information. This strategy blurs the lines between scientific facts, commercial promotion, and speculation, thereby calling into question the fundamental role of science communication.

At a time when technological trends are redefining the use of natural resources, the future of work, and the balance of democracies, science communication cannot shy away from its responsibility. Only an informed discourse, grounded in a critical analysis of technological promises and the underlying political, economic, and social power dynamics, will restore public trust and re-establish democratic debate at the heart of scientific decision-making.

Artificial intelligence is fundamentally transforming research and higher education. It opens up new possibilities for knowledge production and, in doing so, poses new challenges to the core principles of academic integrity and effective university teaching. How can AI tools be used effectively—and in which situations should their use be deliberately avoided so as not to undermine learning processes, scientific judgment, and the development of expertise? And what responsibilities do researchers, educators, and institutions bear in this regard?

Wie beeinflusst KI unsere Bildung? Dieser Workshop geht weniger um KI selbst als um Bildung in einer Welt mit KI. Wir hinterfragen Narrative, diskutieren ethische Herausforderungen und analysieren die Perspektive von Studierenden. Ziel ist es, Ansätze für eine reflektierte und resiliente Bildungspraxis zu entwickeln.

Die Künstliche Intelligenz (KI) ist in aller Munde, und doch scheint sie nicht richtig fassbar. Wo wird die KI eingesetzt, wird sie uns helfen, effizienter oder produktiver zu werden, oder wird sie auf die gleiche Stelle wie der Mensch gesetzt? Sarah Rochat hat in Robotik, Mathematik und Psychologie geforscht und berichtet über Fakten, Chancen und Herausforderungen der KI.

This presentation explores AI use in research through the lens of scientific integrity and the core purposes of scholarship. It surveys current AI-driven practices, pinpoints integrity risks (reproducibility, authorship, bias, transparency), and examines how productivity and efficiency pressures distort research incentives. We reconnect AI use to the deeper purpose of research — to learn, discover, explain, and advance reliable knowledge for society, not merely to maximize paper counts or metrics. Rather than prescribing a single policy, the talk proposes a principled framework to align AI adoption with the principles of research integrity: reliability, honesty, respect and accountability. Attendees will leave with concise, actionable takeaways: clear guidelines, concrete examples of integrity‑preserving workflows, and a set of decision questions to critically evaluate AI in their own work.

Les récits sur l’intelligence artificielle et la robotique sont souvent accompagnés de démonstrations spectaculaires, de vidéos virales et d’annonces de « ruptures » qui donnent l’impression d’une technologie se déployant d’elle-même à un rythme effréné. Dans cette présentation, j’argumente que cette mise en scène vise à occulter les choix sociaux, économiques et politiques qui orientent les développements technologiques et à les exclure ainsi du débat public. À partir de l’exemple de la robotique humanoïde, souvent présentée comme une solution naturelle à la crise des soins, j’analyse comment les rhétoriques d’innovation dominantes contribuent à dévaloriser et à invisibiliser le travail vivant, donnant l’impression que son automatisation est non seulement possible, mais aussi désirable. Je termine en argumentant que la mise en lumière des rapports de force, des mécanismes d’exclusion et des impacts à long terme renforcés par ces rhétoriques est nécessaire pour rétablir un débat démocratique sur le développement technologique et l’innovation.

Wer bei uns vorbeikommt, erlebt Robotik niederschwellig und interaktiv. Ob in der Produktion, im Bauwesen oder in der Pflege: Roboter werden zum flexiblen Werkzeug, das intuitiv programmierbar ist und Menschen bei ganz unterschiedlichen Aufgaben unterstützt.

An der BFH bilden wir die Ingenieurinnen und Ingenieure aus, die diese Zukunft mitgestalten – mit Studiengängen in kollaborativer Robotik, intelligenten Produktionssystemen, Medizininformatik, Digitales Bauen und mehr. Unsere Studierenden sind vor Ort und geben gerne persönlich Auskunft zum Studium an der BFH.

How to provide actionable strategies to deploy AI that empower your teams, drive resilience, and create lasting impact from day one. Connect, share, and learn at the BFH Business Breakfast.

The Digital Days offer a space
to learn, experiment, and
exchange ideas. How can I protect my
data? How can I use artificial intelligence
responsibly? What kind of digital future do
we want for our city?

We break down digital barriers and create an inclusive digital future for everyone. That is our mission.

BRIDGE is a joint programme of the Swiss National Science Foundation SNSF and Innosuisse - the Swiss Agency for Innovation Promotion. It offers funding at the interface of basic research and science-based innovation.

The interdisciplinary and interfaculty Graduate School “Digitality and Education” is a collaborative project between the University of Bern, the Bern University of Teacher Education (PHBern) and the Bern University of Applied Sciences (BFH).

The development of a supplement to the Code of Conduct for Scientific Integrity for GenAI applications.

Ambizione grants are aimed at early career researchers who wish to conduct, manage and lead an independent project at a Swiss higher education institution.

Your partner for the future of automation. Say goodbye to complex training and intricate programming – our user-friendly design makes adapting robot applications as easy as operating your smartphone. Bring flexibility and innovation to your manufacturing processes.

The European University Association (EUA) is the collective voice of the universities of Europe, institutions that have shaped our world for a millennium.

The Swiss Cobotics Competence Center (S3C) offers a space to all companies that want to increase their production line’s flexibility and their workforce’s capabilities.

Innovation Booster Robotics, is a program dedicated to fostering radical innovation in the Swiss robotics ecosystem.

The SNSF awards PtS grants to qualified experts with proven practical experience who wish to join a university of applied sciences or a university of teacher education as a professor, and to newly appointed professors at a university of applied sciences or a university of teacher education who wish to strengthen the academic component of their dual scientific-practical skill profile.

Best Paper Awards for the Article: Empowering Production Workers to Program Robots: A No-Code, Skill-Based Approach, Blanc, Charly and Boudry, Lionel and Sonderegger, Andreas and Nembrini, Julien and Dégallier-Rochat, Sarah.

Award to thank personalities from French-speaking Switzerland for their contributions to the development of innovation in the Swiss Industry.