Experts warn that safety research around artificial intelligence in healthcare needs to accelerate as regulatory frameworks evolve. Recent changes in how clinical decision support tools are treated have allowed many AI systems to enter medical settings with fewer regulatory hurdles, increasing their use in diagnostics, patient interaction, and routine clinical workflows.
While these developments may improve efficiency and access to medical insights, specialists caution that many AI tools are being deployed faster than they are being thoroughly evaluated. Potential risks include inaccurate recommendations, hidden biases, and misleading outputs that could negatively affect patient care if not properly understood and monitored.
The article highlights that AI systems in healthcare can change over time as they learn from new data, making traditional approval and oversight models less effective. Without strong post-deployment monitoring and independent validation, errors or performance drift may go unnoticed, increasing the risk of harm.
Overall, the experts call for a balanced approach that encourages innovation while strengthening safety research, transparency, and accountability. They argue that rigorous evaluation and ongoing oversight are essential to ensure AI enhances healthcare outcomes without compromising patient safety.
