AI in Healthcare That Works for Everyone
AI in healthcare promises efficiency and better outcomes for patients. Research shows that medical AI can widen health disparities for marginalized groups, such as people with an immigrant background, those with low socioeconomic status, LGBTQ+ individuals, and people with disabilities. For example, genetic risk algorithms perform much less effectively for non-European populations: 79% of the training data comes from Europe, which represents 16% of the world’s population.
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.
Collaboration partners
Public, private, and academic partners collaborate within the lab:
- 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 Public Health Service (GGD Amsterdam), Ben Sajet, Center for Urban Mental Health
- Industrial partners: ITSLanguage, Syntho, Royal Auris
