Recap – Toward Human-Centered AI to Improve Decision Making in Healthcare, with Hyunggu Jung 

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Published on August 13, 2026

On Friday July 24, Dr. Hyunggu Jung delivered a research seminar at CAIS (The Centre for Artificial Intelligence & Society), titled “Human-Centered AI to Improve Decision Making in Healthcare.” The Dahdaleh Institute for Global Health Research co-sponsored this event.  

Dr. Hyunggu Jung began by sharing an overview of his past research, which focused on the early-stage development of innovative technologies through design and engineering to support people with disabilities and older adults. His work spans the intersection of artificial intelligence, human-computer interactions, and health informatics. For instance, some of his projects included the development of technology for supporting the daily lives of older adults, media engagement by people with visual impairments, and improving information accessibility for people with visual impairments.  

Furthermore, Dr. Jung reflected on the cascading effects of the design and use of AI systems. This includes AI reflecting real-world patterns of health inequality and discrimination, application injustices, biases in AI design and deployment practices, as well as discriminatory data, including sampling biases and a lack of representative datasets.  

Subsequently, Dr. Jung explained the concept behind human-centered AI, which is to create AI systems that “amplify and augment rather than displace human abilities” (IBM Research). Comparing AI-centered models to human-centered models, AI-centered models seek to emulate human behaviours, with AI engineering focused on replacing human performance. Conversely, human-centered models enhance human performance, making systems dependable, safe, and trustworthy. Human-centered AI can be applied to healthcare in multiple domains which can be divided by stakeholders, for instance, patients, clinicians, and researchers. Some applications of AI in healthcare include patient-facing technologies, wearables and devices, and drug discovery.  

Touching upon recent research efforts, Dr. Jung shared how AI drives his work through enhancement, not substitution, and emphasized the importance of AI-assisted models, as opposed to AI-based models. Currently, he is developing an AI-based platform to support multiple stakeholders for better healthcare, including clinical guidelines, disease predictions, and health behaviour changes. In the end, Dr. Jung discussed some recommended practices for developing effective human-centered AI systems, including identifying multiple metrics to assess training and monitoring, and directly examining draw data.  

Watch the full seminar presentation here: https://youtu.be/kzDQWVdWnB0

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