The VA Looks To Ai: Rebellion Op-ed
On July 11, 2019, the U.S. Department of Veterans Affairs (VA) named its first Director of Artificial Intelligence (AI): Gil Alterovitz. Mr. Alterovitz brings significant expertise at the intersection of technological and medical innovation, notably advancing health initiatives that leverage AI technologies to provide an expedited and improved patient experience. Mr. Alterovitz will incorporate data science into VA wellness and outreach programs. The VA department’s emphasis on implementing innovative technologies and algorithms applies beyond primary health initiatives and into aggregate data collection and health infrastructure projects.
The VA department foresees AI applications in patient data collection, the advancement of medical detection technology, and the completion of a veterans medical database to better facilitate patient treatment procedures and drive veteran specific medical insights. The VA department will particularly utilize AI development in its Million Veteran Program, collecting and parsing a million veteran health records to establish verifiable medical trends and potential solutions for prevalent healthcare challenges.
Mr. Alterovitz supports extensive AI research and development, and he will ensure the development of ethical AI-based medical technologies. Despite the absence of significant AI infrastructure, Mr. Alterovitz has committed to realizing a vision of widespread AI utilization in the VA department for effective and efficient healthcare. Recognizing the cost-mitigating nature of AI deployment, the VA department has seized particular leadership among federal agencies in the space.
The VA department’s adoption of fundamental AI technologies and algorithms reveals the universal appeal of machine-learning programs for the facilitation of effective commerce, solution development, and healthcare. The VA department will continue to solicit third party AI technology vendors to spur medical software competition and innovation; the department’s advancement of AI suggests that federal agencies will increasingly leverage data-driven models and machine-learning algorithms to promote efficacy and mitigate costs in future programs.
Written by Aaron Rennert, Edited by James Mueller & Alexander Fleiss