AI in Health Communication.
Fenella Chadwick.
The rapid integration of Generative Artificial Intelligence (GenAI), such as Large Language Models (LLMs), into health communication presents an urgent need for an adaptable and robust governance framework. GenAI offers unprecedented potential for personalized health information, content generation, and patient engagement, but it simultaneously introduces significant risks, including the proliferation of misinformation, the loss of trust, and ethical challenges related to bias, privacy, and accountability. This paper proposes a model for Adaptive Governance designed to continuously evolve in response to the pace and unpredictable nature of GenAI development and deployment in the healthcare sector. This model shifts from rigid, static regulations to a dynamic, multi-stakeholder system that incorporates iterative policy adjustments, regulatory sandboxes, continuous auditing, and technology-agnostic ethical principles. Key components of this approach include establishing real-time monitoring mechanisms for content accuracy and bias, defining clear liability and accountability across the health communication value chain (from model developers to health providers), and prioritizing human oversight and mandatory disclosure of AI-generated content. Ultimately, developing adaptive governance is essential to harness GenAI’s communicative power while safeguarding public health, patient autonomy, and the integrity of medical information.
