5 Questions with Faculty – The Future of Artificial Intelligence in Public Health with Xin Wang

ALBANY, NY (Oct. 2, 2023) – Today we sat down with Assistant Professor Xin Wang, who recently joined the Department of Epidemiology and Biostatistics, to talk about his interdisciplinary work in artificial intelligence (AI) and public health.

Broadly speaking, where is home for you, and what drew you to the University at Albany?

I am from Seattle, but I joined UAlbany as a faculty member because I was drawn to the AI Institute’s commitment to fostering AI innovation and academic excellence. UAlbany provides a conducive environment for exploring interdisciplinary approaches to solving complex problems. The environment here aligns well with my passion for integrating AI into education and research.

Also, the opportunity to collaborate with colleagues who are experts in their respective domains and to engage with students eager to learn and innovate was particularly appealing. I look forward to contributing to the academic community and to exploring new frontiers in knowledge and technology.

Your career started in computer science. What made you decide to pursue public health?

The intersection of computer science and public health is fascinating. I was drawn to public health from computer science due to the potential for AI technologies to impact global health issues positively. For example, AI can read diagnostic images better than human beings can in many cases. Providing primary care physicians access to this type of technology would expand access to these services substantially, potentially helping to alleviate health care deserts. Leveraging AI techniques can lead to innovative solutions for complex health challenges.

There is a lot of public interest (and concern) about artificial intelligence right now. How do you see AI impacting the field of public health?

AI has tremendous potential in the field of public health. From disease outbreak prediction to analyzing vast amounts of data for research to precision medicine and personalized healthcare recommendations, AI can streamline existing processes and offer insights that were previously out of reach. However, with this potential comes the responsibility to ensure that AI applications are ethically transparent and do not inadvertently introduce or perpetuate biases. It is important to remember that AI is ultimately authored by humans and can be embedded with the prejudices and internal biases of those humans. As a discipline, we have to think critically about what AI is doing and why, and to what extent that is consistent with what we are trying to accomplish as public health professionals.

You mentioned precision medicine. Could you say a little bit about that and how AI is involved?

Precision medicine aims to tailor medical treatment to each patient's individual characteristics, needs, and preferences. I mainly use AI for medical image analysis, but it can serve other functions as well. AI can play a critical role by analyzing vast patient data, recognizing patterns, and making predictions or recommendations tailored to individual patients. This can lead to more effective treatments and interventions, potentially reducing costs and improving outcomes at the same time. Anything that both improves health care and saves money is highly desirable, particularly in the U.S. health care system which is one of the most expensive in the world.

Do you think the anxieties that are often expressed in the media about AI are warranted? Are there any specific health-related concerns that you have about the future of AI?

While I don't have personal anxieties, it is understandable that there are concerns about AI, especially given its growing influence, like the Generative AI and Large Language Models. These are responsible for programs like ChatGPT, which seems to be very popular in the media right now. Some people have concerns about the ethics and accuracy of using AI for composing articles, essays, and other communications. For example, some schools are now using “AI detectors” on student writing to try to catch potential plagiarists.

Other concerns often revolve around privacy, data security, the potential misuse of biodata, and the ethical implications of decision-making by AI in the context of health care. And also in the health sector, there's the added complexity of ensuring that AI doesn't inadvertently cause harm through misdiagnosis, biased algorithms, or other unintended consequences. A balanced approach to AI adoption, which weighs benefits against potential risks and involves multidisciplinary expertise, such as that of my colleagues in the Department of Health Policy, Management, and Behavior, is crucial.