Researchers at Duke University have been awarded a $196,000 grant to address a growing issue related to the use of artificial intelligence (AI) in healthcare: the gray area between explaining decisions to patients and protecting trade secrets associated with clinical decision support (CDS) software. 

Funded by The Greenwall Foundation, the one-year grant was awarded to the Duke Law Center for Innovation Policy and Duke-Margolis, MD, Center for Health Policy. The researchers’ goals include generating "explainability recommendations" to healthcare professionals and patients and determining whether legal or private self-regulatory approaches should be considered.

The grant will allow the researchers to collect and review quantitative data on private and public investment in AI-based CDS software, conduct interviews and hold workshops with various stakeholders in the healthcare sector.

“While software development has always involved trade secrecy, the importance of trade secrecy as an innovation incentive may have increased as a consequence of challenges associated with securing and enforcing software patents,” principal investigator Arti Rai, JD, of the Duke Law Center for Innovation Policy, said in a prepared statement. “For this reason, the principal regulator of AI-based software, the FDA, as well as professional organizations, providers, and insurers are actively interested in the question of how to balance explainability and trade secrecy.”

Rai and colleague Gregory Daniel, PhD, MPH, of the Duke-Margolis, MD, Center for Health Policy, will publish their results and recommendations in journals and also anticipate publishing a white paper highlighting their findings. 

“Research on how to effectively integrate artificial intelligence into health care delivery is a new and emerging area of work for the Duke-Margolis Center,” Daniel said in the same statement. “By working in collaboration with Duke Law, we can move much more quickly to identify real-world policy approaches to support emerging technologies that incorporate AI in helping physicians and patients make better healthcare decisions.”