The National Academy of Medicine introduced a new artificial intelligence code of conduct designed to guide how AI is developed, evaluated, and deployed across healthcare.
One of the 21 authors of the policy is Penn Integrates Knowledge University Professor Kevin Johnson. The 206-page report, titled “An Artificial Intelligence Code of Conduct for Health and Medicine,” lays out a unified ethical framework aiming to regulate the use of AI in healthcare.
“The same thing that happened with electronic health records is happening again with AI,” Johnson told Penn's Leonard Davis Institute of Health Economics. “Everyone’s building tools, but there isn’t a shared playbook to make sure they’re safe, fair, and actually useful. This report was needed to bring some order to the chaos.”
“It gives us a national framework so AI in health care can be developed and used responsibly, with transparency and trust at the center,” he added.
According to Johnson, a lack of shared standards has created uneven oversight, rising concerns about bias, and increasing pressure on already strained clinical workforces.
“Hospitals, companies, and agencies are all moving quickly, but not necessarily in the same direction,” he said. “That lack of coordination leads to duplicated work, unclear accountability, and uneven protections for patients. This report provides a way to fix that.”
At the heart of the new framework are six major code commitments: advance humanity, ensure equity, engage impacted communities, improve workforce well-being, monitor performance, and foster innovation and continuous learning.
The commitments are paired with ten code principles, including transparency, accountability, safety, and fairness.
“Everyone has different priorities, incentives, and comfort levels with risk,” Johnson said. “Until developers, clinicians, regulators, and patients share a common understanding of what ‘trustworthy AI’ means, we’ll keep bumping into the same issues. We need to agree on shared values, safety checks, and how we measure success.”
On its website, NAM explained that the report’s elements are designed to apply across the entire AI lifecycle, beginning with data collection and running through algorithm design, real-world implementation, and long-term monitoring.
“The AICC vision is to align and catalyze collective action to realize the potential of AI to revolutionize health care delivery, generate groundbreaking advances in health research, and contribute to robust health for all,” its website reads.
