Hospitals and health systems are increasingly adopting artificial intelligence technologies built into health IT such as EHRs, telehealth services, remote patient monitoring and other tools that can expand access to care and improve health equity.

At the same time, conversations around AI safety and regulatory measures are happening around the globe, including a major recent executive order issued by President Biden.

As AI becomes embedded in the daily lives of people across the country, learning how to best use the technology while prioritizing security and equity – both on the individual level and more broadly – ​​is paramount.

Researchers at the University at Albany’s School of Public Health are actively exploring ways that artificial intelligence and machine learning can be applied to public health, to improve health outcomes for patients while prioritizing patient safety and data security.

Xin Wang is an assistant professor in the department of epidemiology and biostatistics at the University at Albany. His areas of expertise include artificial intelligence, deep learning, precision medicine and medical image computing, among other related subjects.

Here he shares his thoughts on how public health researchers can support the development of safe and effective health-centered AI.

Q. Where do public health and