AC LITERATURE

Dr. Anthony Chang

“Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It is really an attempt to understand human intelligence and cognition.” 

Sebastian Thrun, German-American computer scientist and entrepreneur  

 

We will conclude this series on AI in health for 2025 and beyond with a special focus on the dimension of process: 

Peripheral to Central AI

The AI adoption and workflow should involve peripheral tools like internet of things (IoT), AI-embedded devices such as wearable technology and sensors, and even edge AI with the latter generating AI dividends at the local (personal) level. At the other end of the workflow, AI technology is headed in the direction of multimodal AI, foundation model, and even digital twins coupled to deep reinforcement learning. In the middle of these two “ends” could be federated and swarm learning to enable centers in healthcare to share insights of the models without necessarily sharing raw data. 

 

Precision Medicine from Primary to Quaternary Care

 It is hoped that the people and the technology of AI can lead us into the decades long vision of precision medicine for all. With the aforementioned technology of digital twins coupled to deep reinforcement learning, precise diagnosis and treatment strategies can be realized finally. AI needs to be in the hands of not only clinicians in subspecialties, but also for primary care physicians as well as their associates to enable efficient and effective delivery of care for chronic diseases. Perhaps we will finally achieve the quintuple aim for both patients and caretakers with the aid of a panoply of AI tools.  

 

Change Management

The implementation of AI in healthcare is very dependent on change management with appreciation for education, collaboration, and adoption strategies. While most healthcare executives are not educated or trained in the concepts of artificial intelligence, they do now appreciate the immediate impact of AI now and in the near and far future. There is a growing number of “chief AI officers” or chief information and chief data officers with some focus on AI, and this movement will help to push the AI agendas in healthcare organizations and AI enterprises.    

 

With the Nobel Prizes in Chemistry and Physics given to several of the leading researchers in artificial intelligence, the future looms bright with a myriad of possibilities for use of artificial intelligence in medicine and healthcare. From complex decision support and medical image interpretation to administrative tasks and even drug and vaccine design, artificial intelligence will increase its portfolio of applications in health and medicine these coming decades. Even the Nobel laureates disagree widely, however, on the exact nature of the dynamic relationship between humans and AI in society and where this fragile dyad is headed in terms of good vs evil. As the evolution of artificial intelligence race towards artificial general intelligence (AGI), this exponential rise of AI technology will bring ongoing challenges such as bias and ethics as well as the humankind using AI for evil purposes.