AI for reliable clinical decision-making
In healthcare, digital systems are increasingly being used to support professionals in making clinical decisions. 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, accountability, and trust. Precisely because decisions in healthcare have far-reaching consequences, the careful use of AI is essential.
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 initiative that focuses on the ethical, legal, and societal 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 effort.
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 trust in healthcare decisions.
Guiding the Responsible Use of AI in Clinical Practice
The ELSA Lab Accountable Decision Support is developing concrete approaches and tasks to guide the responsible use of AI 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 Liability 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 through the ELSA Network, so that lessons learned and best practices become more widely available both 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 a variety of perspectives and fields of expertise. Within the lab, more than twenty public, private, and academic partners are collaborating on shared challenges, each contributing their own role and expertise:
