The use of large language models (LLMs) and other forms of generative AI (GenAI) in healthcare has surged in recent years, and many of these technologies are already applied in clinical settings. As such, they often qualify as medical devices and must comply with specific laws and regulatory frameworks.
The new autonomous and broad-scope technologies have fundamentally different characteristics. They demonstrate greater autonomy, adaptability, and scope than previous AI technologies. As they are capable of autonomously executing complex workflows, they present significant challenges for regulators and developers.
As AI agents’ capabilities exceed the scope of current regulatory frameworks, the researchers propose several potential solutions to overcome barriers to their implementation:
1.Immediate adaptations: include extending enforcement discretion policies.
2.Medium-term solutions: involve developing voluntary alternative pathways (VAPs) and adaptive regulatory frameworks.
3.long-term solutions: regulating AI agents to the qualification of medical professionals.