The American Medical Association (AMA) has released a set of guidelines aimed at directing the responsible development and implementation of augmented intelligence (AI) in healthcare, in response to the rapidly expanding field of this technology.
The company is aware of how much AI can do to enhance patient care, treatment outcomes, and diagnostic accuracy. However, the AMA seeks to promote a proactive and moral approach to oversee and regulate healthcare AI, acknowledging the ethical issues and possible risks associated with such transformative power.
In order to develop policies governing the use of AI in healthcare, legislators and industry stakeholders will need to be guided by these principles, according to AMA President Jesse M. Ehrenfeld, MD, MPH. The following are the main topics that the principles address:
Oversight:
To develop regulations that reduce the risks connected with healthcare AI, the AMA supports an all-encompassing, national strategy. It acknowledges the part non-governmental organizations play in making sure proper governance and oversight are in place.
Transparency:
The guiding principles emphasize how important it is require important details regarding the creation, advancement, and application of AI procedures, including any possible sources of unfairness. It is believed that openness is necessary to build trust between medical professionals and patients.
Disclosure and Documentation:
When AI has a direct impact on patient care, medical decision-making, access to care, communications, or the medical record, the statement mandates appropriate disclosure and documentation.
Generative AI:
It is recommended that healthcare institutions create and implement policies that foresee and reduce any potential drawbacks. It is stressed that these policies must be in place before adoption.
Security and Privacy:
It is recommended that AI developers consider privacy when designing systems. Protecting patients’ privacy and ensuring responsible handling of their personal information is a shared responsibility between healthcare organizations and developers. It is crucial to fortify AI systems against cybersecurity risks in order to ensure their dependability, resilience, and safety.
Bias Mitigation:
To support fair and inclusive healthcare systems and equitable healthcare outcomes, the American Medical Association (AMA) advocates for the early detection and mitigation of bias in AI algorithms.
Liability:
In line with current legal perspectives on medical liability, the association supports limiting physician liability for using AI-enabled technologies.
The statement also exhorts payers to refrain from using automated decision-making systems in a way that would deny certain groups access to care or limit their ability to receive necessary care. It highlights how crucial it is to make sure that clinical judgment is not superseded by these systems and that human evaluation of specific cases is kept.