Artificial intelligence (AI) in healthcare promises efficiency and better outcomes for patients. At the same time, studies show that medical AI can increase health disparities for marginalized groups, such as people with a migrant background, low socioeconomic status, LGBTQ+ individuals, and people with disabilities. For example, algorithms for genetic risks work much less well for non-European populations, because 79% of the training data comes from Europe, while Europe represents only 16% of the world's population. This is a challenge that must be addressed collectively.
The role of AI in health disparities
AI systems for diagnosis, prognosis, and treatment can transform healthcare and reduce costs. At the same time, these systems can inadvertently cause new problems. Bias in training data can lead to discrimination against certain patient groups. Algorithms for the allocation of healthcare resources can also inadvertently cause exclusion.
In addition, mistrust and a lack of digital infrastructure can mean that vulnerable groups benefit less from AI applications in healthcare. This highlights the importance of paying attention to the ethical, legal, and social aspects of AI development and application.
About the ELSA Lab AI for Health Equity
The ELSA Lab AI for Health Equity takes a perspective based on health equity and social well-being. Health equity means that everyone has the opportunity to achieve the highest level of health and well-being. Based on this principle, the lab focuses on the use of AI in healthcare, with particular attention to underrepresented groups.
The lab is investigating how two specific use cases, speech analysis for low literacy and synthetic data for bias reduction, can contribute to fairer medical AI. These applications are being tested in an Open Living Lab together with patient groups, professionals, and AI developers, so that solutions are directly aligned with practice and are usable.
Guiding responsible AI for equality in healthcare
The ELSA Lab AI for Health Equity is building an ecosystem of knowledge sharing to responsibly guide the growing use of medical AI. Within this ecosystem, public, private, and academic parties work together on shared issues surrounding health equity. This includes, among other things:
- Legal and ethical guidelines for designing and evaluating medical AI systems, with attention to diverse patient needs and health values.
- Research into regulations, mapping out the tension between GDPR, the EU AI Act, and the Medical Device Regulation, including practical perspectives for action.
- Fundamental research into how healthcare professionals and society experience AI in healthcare, and what this means for trust and acceptance.
- Knowledge sharing via the ELSA Network, making insights and best practices more widely accessible.
This research is conducted from a health equity perspective. AI systems are approached as part of hybrid intelligence, in which humans and AI work together. The goal is not to replace humans, but to enhance health and well-being.
Collaboration partners
Public, private, and academic partners collaborate within the lab, including:
- Academic partners: University of Amsterdam (lead), Radboud University, Utrecht University, Amsterdam UMC, VU Amsterdam, Amsterdam University of Applied Sciences
- Social partners: MIND, SGAN, Vilans, Amsterdam Municipal Health Service, Ben Sajet, Centre for Urban Mental Health
- Industrial partners: ITSLanguage, Syntho, Royal Auris
Want to know more or collaborate?
Please contact Prof. Dr. A. Anniek de Ruijter, Full Professor of Health Law and Policy, University of Amsterdam (a.deruijter@uva.nl) by sending an email.
