Research Ethics and AI in Doctoral Training at NMBU

Research ethics and artificial intelligence (AI) in doctoral training at NMBU: the PhD courses VET400 and VET422, coordinated by Professor Andrew M. Janczak.

About the Courses

Doctoral training at the Faculty of Veterinary Medicine rests on a central foundation of philosophy of science and research ethics. As a supplement, the faculty offers an open seminar course in the responsible use of artificial intelligence, providing candidates with a practical toolbox for the digital challenges they encounter throughout their entire research trajectory. Together, these courses give PhD candidates a comprehensive foundation to plan, execute, and communicate research of high academic and ethical quality, providing everything from foundational philosophical and ethical understanding to proficiency with the newest digital tools. Both courses are open to PhD candidates and staff across all of NMBU, bringing together participants from different faculties and disciplines.

The teaching is anchored in the faculty's broad responsibility for research and methodology training. Furthermore, these courses link PhD education directly to active research in computational ethology and precision animal welfare, among other fields at the Faculty of Veterinary Medicine.

• Philosophy of Science and Research Ethics

  VET400: Introduction to ethical and philosophical perspectives in biomedical research contributes to providing PhD candidates with a language and a framework to handle the ethical and philosophy of science dilemmas they will face as researchers. Through work with the philosophy of science, research ethics, and issues related to animal experimentation and scientific integrity, candidates develop the ability to identify and justify their own positions. This approach ensures they do not merely know the rules, but understand why they exist.

  The teaching format is dialogue-based: candidates work with the syllabus, bring their own dilemmas from ongoing projects into the discussion, and present reflections to one another. This makes the course equally relevant for candidates in laboratory research as it is for those working with clinical data, registry data, or computational models.

  For the formal course description, learning outcomes, and enrollment information, see the official course page for VET400: Introduction to ethical and philosophical perspectives in biomedical research.

• Practical use of artificial intelligence in biomedical research

  VET422 gives PhD candidates and staff practical competence in the responsible use of artificial intelligence throughout the entire research process. The course addresses the concrete challenges participants face in their daily work, including literature searches, academic writing, data analysis, method development, and administrative tasks such as grant writing and reporting.

  Through monthly seminars featuring open participation across faculties, participants build not only technical familiarity with generative AI tools, but also the critical capacity to evaluate when and how they should be used, and when they should be avoided. A continuous theme throughout the course is the institutional and regulatory frameworks governing AI in academia, including NMBU's own guidelines and the European Union Artificial Intelligence Act (EU AI Act).

  For the formal course description, learning outcomes, and enrollment information, see the official course page for VET422: Practical use of artificial intelligence in biomedical research.

• Research-Based Teaching

  The teaching in VET400 and VET422 is tightly coupled with an active research environment. Professor Janczak leads the Computational Ethology and Precision Animal Welfare research group, which combines classical ethology and animal welfare science with computer vision, machine learning, and digital phenotyping.

  The teaching in artificial intelligence directly supports this research profile in precision animal welfare. Here, the goal is to translate continuous behavioral and sensor data into objective indicators, providing an early warning of health and welfare deviations, as well as practical decision support for animal owners, producers, and veterinarians. This close integration ensures that PhD candidates receive ethics and AI training that is anchored at the absolute forefront of research. The competence they build can be applied directly within their own projects, in continuing education (EVU), and within a broader perspective of lifelong learning.

  See projects, methods, and researchers in the Computational Ethology and Precision Animal Welfare Research Group

• An Interdisciplinary Learning Community

  What binds the two courses together is a student-active and dialogue-based teaching format where the participants themselves contribute actively. In VET400: Introduction to ethical and philosophical perspectives in biomedical research, this takes pace through discussions and presentations for peers. In VET422: Practical use of artificial intelligence in biomedical research, an open seminar community is created where participants contribute their own topics, demonstrations, and peer reviews. In this manner, the courses function as an interdisciplinary meeting place where researchers from different disciplines and at various career stages can share experiences and collaboratively develop common standards for responsible research practice.

• Contributors for VET400

  Feroz Mehmood Shah

  Senior Lecturer, UiO

  Kaia Kjølbo Rød

  Business Developer, Ard Innovation

• About contributors to VET422

  As VET422 is organised as a participant-driven seminar community, there is no fixed roster of lecturers. Instead, PhD candidates and researchers at NMBU are invited to contribute actively with their own experiences, demonstrations and testing of generative AI tools, as an integral part of the shared exchange of knowledge.

• Cross-Disciplinary Coordination

  As the course coordinator for VET400 and VET422, Professor Janczak coordinates the faculty's PhD training in research ethics and the responsible use of artificial intelligence. In this manner, the doctoral curriculum connects directly to the section's active research environment within animal welfare and ethology. This coordination ensures a comprehensive and coherent academic path, leading candidates all the way from foundational philosophical and ethical perspectives to the practical application of the latest digital tools.

  For a broader overview of the section's animal welfare curriculum, see the main page for Animal Welfare in Veterinary Education at NMBU.

• Sources

  The structural descriptions and institutional framework provided across these sections are sourced from the course descriptions for VET400 and VET422, current instructional schedules, and the administrative guidelines of the Faculty of Veterinary Medicine at NMBU. Further course details, timetables and teaching materials are available in Canvas after you have registered for the courses via StudentWeb.

• Editorial information and academic basis

  The content on this page has been prepared, maintained, and communicated by the course coordinator for VET400 and VET422, in accordance with the individual responsibility for the content and organization of teaching under Section 2-2, fourth paragraph, of the Norwegian Universities and University Colleges Act, as well as the individual right and responsibility for dissemination under Section 2-2, sixth paragraph.