AI in Healthcare: Global and Local Adoption Cases from the USA & Hungary

This study group builds on our previous discussions on the application of AI in healthcare. It will focus on more specialized use cases, illustrating what it takes to develop AI as a system-level capability within healthcare, and exploring the future trajectory of the technology.

We will examine the opportunities, challenges, and ethical considerations associated with AI in predictive medicine, diagnosis, and drug discovery. The discussion will also compare governance approaches in the United States and the European Union, and consider whether regulatory choices will shape the relative leadership of these regions in this domain.

We expect the participants to learn not only a conceptual framework for understanding the capabilities AI brings to healthcare and the systemic risks it entails, but also a deeper appreciation of the forces driving innovation in this field. The session is designed for those interested in how AI capabilities are built and scaled, as well as those seeking to understand how AI intersects with the structural challenges facing modern health systems.

We'll draw on the expertise of three practitioners working at the frontier of this space.

Dr. Mauricio Santillana is Director of the Machine Intelligence Group for the Betterment of Health and the Environment (MIGHTE) at the Network Science Institute, Northeastern University. His research demonstrates how machine learning can monitor and predict disease outbreak dynamics using unconventional data sources — internet search activity, social media, clinician behavior, human mobility, and weather patterns — that were never designed for epidemiological purposes.

Dr. Miklós Szócska is a Senior Fellow at the Mossavar-Rahmani Center for Business and Government (MRCBG) at Harvard Kennedy School and former Minister of State for Health in Hungary. Drawing on his experience spanning government, policy, and AI implementation in health systems, Dr. Szócska will offer a strategic overview of what responsible AI adoption actually requires and the institutional foundations, system-level prerequisites, and governance considerations that often receive less attention than the technology itself.

Dr. Zoltan Szallasi, is a senior research scientist in the Computational Health Informatics Program, at Children’s Hospital, Boston, Harvard Medical School. Dr. Szallasi's group has been applying genomics to characterize key cancer associated biological processes. His main work is focusing around detecting and quantifying DNA repair deficiencies in breast cancer and other solid tumors using next generation sequencing data. The main goal of this work is to enable synthetic lethality driven cancer therapies that target aberrations in specific DNA repair pathways such as homologous recombination or nucleotide excision repair.