AI for reliable clinical decision-making
Digital systems are increasingly being used in healthcare to support professionals in clinical decision-making. These systems can help refine diagnoses, explore treatment options, and better tailor care to individual patients. At the same time, the use of AI in medical decision-making raises questions about reliability, responsibility, and trust. Precisely because decisions in healthcare have major consequences, the careful use of AI is a prerequisite.
The role of AI in clinical decision-making
AI-supported decision-making systems can recognize patterns in medical data and support healthcare professionals in making complex decisions. They offer opportunities to bring information together and provide insight into scenarios. In practice, however, many of these systems prove difficult to understand. It is often unclear how recommendations are made and who is responsible when decisions are influenced by AI.
This lack of clarity can lead to reluctance to use AI, both among healthcare professionals and organizations. It also raises questions about legal liability and ethical responsibility. This makes it necessary to design and apply AI in clinical decision-making in such a way that transparency, accountability, and human oversight are guaranteed.
About the ELSA Lab Accountable Decision Support
The ELSA Lab Accountable Decision Support is an interdisciplinary research and collaboration partnership that focuses on the ethical, legal, and social aspects of AI-supported decision-making in healthcare. The lab investigates how AI systems can be designed and deployed in a way that is understandable, verifiable, and accountable to all stakeholders. Collaboration between humans and technology is central to this.
The goal of the ELSA Lab Accountable Decision Support is to contribute to the reliable and responsible use of AI in clinical decision-making. By providing insight into responsibilities, decision-making, and oversight, the lab aims to help prevent uncertainty about AI from undermining confidence in healthcare decisions.
Guiding responsible AI in the clinic
The ELSA Lab Accountable Decision Support is working on concrete approaches and tasks to guide responsible AI applications in clinical practice. Among other things, the lab is working on:
- Methods for traceability, so that AI recommendations can be traced back to data, assumptions, and reasoning.
- Frameworks for responsibility and accountability in hybrid human-AI decision-making.
- Legal analysis of existing regulations and their practical implications for medical AI.
- Design principles for responsible interaction between healthcare professionals and AI systems, with a focus on transparency and human oversight.
- Practical applications and use cases, in which these insights are tested in realistic clinical contexts.
- Knowledge sharing via the ELSA Network, so that lessons learned and best practices become more widely available within and outside the healthcare sector.
These activities are aimed at supporting healthcare organizations and professionals in the responsible use of AI, without compromising professional autonomy and quality of care.
Collaboration partners
Safety issues surrounding medical AI require different perspectives and domains. Within the lab, more than twenty public, private, and academic partners work together on shared tasks, each from their own role and expertise:
Want to know more or collaborate?
For more information, visit the project website or contact Prof. J.H.P. Kwisthout (Johan) directly.
