Lower Saxony Center for AI and Causal Methods in Medicine (CAIMed)
Ethics Working Group at the UMG Campus
Funding:
Lower Saxony Ministry of Science and Culture, with funding from the Volkswagen Foundation’s ‘zukunft.niedersachsen’ programme. (VWZN4257)
Grant Amount:
551,434.00 EUR (UMG location of the Ethics Research Group)
Duration:
01/2025 – 10/2028
Project Participants:
- Prof. Dr. Silke Schicktanz – Mentor
- Dr. Lorina Buhr – Research collaboration
- Lea Nickel, M. Sc. – Research collaboration
- Natalie Jaworski, M. A.
Project Partners:
Forschungszentrum L3S (Gottfried Wilhelm Leibniz Universität Hannover)
Website:
https://caimed.de/
Research Background
Thanks to innovative treatments and improved medical care, the population is ageing. However, this places immense pressure on the healthcare system, creating a growing need for improved prevention, diagnosis and treatment, particularly for common diseases such as cancer, cardiovascular disease, diabetes and Alzheimer’s. The digitalisation of the life sciences offers new ways of addressing this major future societal challenge. By linking research, clinical and care data through the use of AI and causal methods, prevention, diagnosis, treatment and the monitoring of therapeutic success are set to become significantly more effective and efficient. Ethical reflection is essential from the conception and development to the deployment of these technologies to ensure the appropriate use of data-driven methods and AI technologies in medicine.
Research Topics
CAIMed is developing innovative, AI-based causal analysis methods to improve personalised healthcare. The focus is on major, widespread diseases, such as cancer, cardiovascular and infectious diseases. The aim is to translate data-driven, methodologically sound approaches into clinical practice, thereby contributing to long-term improvements in medical decision-making processes. The Ethics Working Group addresses the associated ethical aspects. These include questions regarding the system's benefits and risks, data protection, privacy, transparency, traceability and explainability of decisions made by the AI system. The group also considers issues of justice, non-discrimination and fairness, and how these systems affect the autonomy, responsibility and accountability of the stakeholders involved. The AGE's work focuses on analysing the content, significance and implications of ethical concepts, principles and values in the context of using AI methods in medicine. In addition to conceptual analysis, determining the respective socio-technical context through empirical research plays an important role.
Research Aims
- CAIMed: improving healthcare and enhancing the efficiency of the healthcare system by using innovative AI methods and applications in medicine
- AGE: Anticipating, mitigating and, when necessary, preventing negative implications by addressing ethical considerations at an early stage in the development and application of AI systems
Outreach
- Ethics Meet-Up in Göttingen featuring high-profile keynote speakers and group discussions („World Cafes“), 14.11.2025
The Sub-Projects
Sub-Project 1 (SP1): Communicating with and about digital technologies in personalised oncology. An empirical ethical exploration of the patient trajectory in the age of AI
Lea Nickel (PhD project)
This doctoral project adopts a patient-centred approach and focuses in particular on the epistemic modelling technique known as ‘patient journey mapping’. This method will be used to trace and discuss the ethical issues arising from the complex interplay between communication practices and the multiplicity of AI applications in oncology. The focus is on an empirical-ethical investigation of informed decision-making in the context of AI. The study examines the two interrelated dimensions that constitute informed decision-making: the provision of information through communication practices, and the availability and accessibility of decision-making options. The aim is to develop and reflect on ethically grounded communication practices that support oncology patients in navigating this multiplicity of AI implementations.
Sub-Project 2 (SP2): Interviewstudie zu Entscheidungen zur Implementierung von KI-Modellen in der medizinischen Forschung und Praxis
Dr. Lorina Buhr, Natalie Jaworski
This interview study with experts examines the question: Who decides which AI model (e.g. in an oncology or radiology department) is to be introduced, and which stakeholders and considerations are taken into account in this decision-making process? Understanding the contexts and processes involved in implementing AI can reveal where and to what extent ethical expertise and considerations, as well as stakeholder involvement, can be effectively integrated, and where participatory design may be ineffective due to specific decision-making contexts.