Veterans Affairs Department Appoints First AI Director

The Veterans Affairs (VA) Department has appointed its first director of artificial intelligence. Dr. Gil Alterovitz – who has degrees from MIT and Carnegie Mellon in electrical, biomedical, and computer engineering – will be based in the VA’s Office of Research and Development. He is also a professor at Harvard Medical School and the Computational Health Informatics Program at Boston Children’s Hospital. Alterovitz states that his overarching career interest is “bridging engineering and medicine.”

“Given how healthcare is evolving, AI is really the only way to move forward in terms of reducing costs and providing better care,” said Alterovitz.

A major focus of Alterovitz’s work will center on deriving more insights from the massive amount of genomic and health data the agency has already collected from more than 750,000 consenting Veteran volunteers. Using AI, computers will be able to rapidly assess thousands of data points in order to uncover correlations between such factors as medical conditions, genetics, and medications.

“That is what you need to do optimal AI—a lot of deep knowledge,” says Alterovitz. “AI is key to really taking advantage of that data to help Vets and potentially others, as well.”

Alterovitz will also lead a “sprint” modeled after the “Health Tech Sprint” that he co-led when he worked as a Presidential Innovation Fellow with the Department of Health and Human Services. The Health Tech Sprint involved ten international organizations creating apps and other digital tools that leveraged open databases from different federal agencies, and technologies such as AI. One tool they created helped match cancer patients to clinical trials and experimental therapies. The VA sprint will focus on forging partnerships with outside organizations that specialize in AI.

“We’re working with a few organizations that can test out small amounts of data in the VA format,” says Alterovitz. “Then they can build the AI tools and develop a program that can then be used on a larger data set.”

He says the goal is to develop a “parallel, potential pathway to partnerships that comes about through data-based sprints.”