AI is already transforming drug discovery and diagnosis—and has the potential to do likewise across other elements of the healthcare industry. But to get there will require robust regulatory frameworks to address safety, privacy, and bias concerns—as well as scenario-based assessments to ensure AI’s safe and ethical deployment.
Regulating AI in healthcare is an intricate task that involves striking a balance between fostering scientific innovation and protecting human rights and safety. Different countries may adopt various approaches to AI regulation, reflecting their unique values and priorities. These diverging regulatory approaches result in significant compliance burdens for companies deploying and building AI.
A risk-based framework is recommended for regulating AI in healthcare. This approach involves varying the approval processes based on the risk level of each application. Essentially, the higher the risks associated with the AI tools, the more controls and safeguards should be required by authorities.
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