The pace of AI innovation in healthcare is moving faster than the development of regulation, governance, infrastructure. This gap creates not only inconsistent adoption across organizations, but also increased risk of unintended harm to patients and clinicians alike.
The Trusted Exchange Framework and Common Agreement (TEFCA) has already shown that it’s possible to align federal policy, technical standards, and private-sector participation toward a shared vision. To succeed, we’ll need open, consensus-based frameworks that enable transparency across the entire AI lifecycle.
One of the biggest risks in AI is the potential to widen existing disparities in healthcare. Standards play a central role in that effort leveling the playing field so that safety, transparency, and trust aren’t dependent on organizational budget.
【MORE】