AI's True Value Lies in Domain Integration: Recommendations for Vietnam's Youth

Associate Professor Nguyen Van Hien, born in 1984 and affiliated with the University of Houston in the US, emphasizes that AI's true value lies in its deep integration with specific professional fields, offering concrete recommendations for the development of Vietnam's youth. His expertise spans AI, computer vision, and medical image analysis, complemented by practical experience at Siemens Healthineers and Uber ATG. Professor Hien states that AI's advancement is not a single breakthrough but a series of continuous decisions to choose challenging yet meaningful tasks, collaborate with talented individuals, and avoid rigid self-imposed limitations. He began researching deep learning around 2013, obtaining one of the world's first patents for deep learning in medical image diagnosis, which was later implemented in Siemens products. Hien is certain that AI will transform medicine, asserting that the crucial questions are "when will it happen" and "who will build the technology responsibly." Regarding AI's application in healthcare, Professor Hien champions a philosophy where AI serves as a tool to assist doctors in making better decisions, rather than replacing them. This approach is rooted in 'Ensemble Theory,' recognizing that AI and human doctors make different types of errors, thus complementing each other's weaknesses. International clinical studies have demonstrated this, such as improved accuracy in detecting breast cancer metastasis by pathologists with AI assistance and reduced reading times. AI is expected to streamline the analysis of vast amounts of images, freeing up doctors to focus on complex cases and human-centric aspects like patient communication and accountability. Professor Hien identifies Vietnam's strengths in AI as the valuable clinical data generated by a high prevalence of certain diseases, a driven young engineering workforce eager to learn, and the nation's developing national strategies and legal frameworks for AI. However, he points to significant challenges that require substantial effort to overcome: a shortage of top-tier AI experts with practical experience in high-risk fields like medicine, and underdeveloped clinical research infrastructure, including hospitals, ethics committees, and data management systems. International cooperation is deemed essential for addressing these issues, suggesting that combining domestic capabilities with global scientific collaboration is the most suitable path for Vietnam to succeed in medical AI. For young individuals aspiring to pursue AI, Professor Hien recommends three specific areas for skill development. Firstly, a deep understanding of the specialized domain where AI will be applied (e.g., medicine, finance, agriculture). Secondly, the ability to build practical systems, transforming algorithms into stable, secure software that continuously improves based on user feedback. Thirdly, adaptability for interdisciplinary work, enabling dialogue with individuals outside one's immediate field. He reiterates that AI only reaches its full potential when combined with specific professional knowledge.