M. Matheny, D. Whicher, & S. Israni
The promise of artificial intelligence (AI) in health care offers substantial opportunities to improve patient and clinical team outcomes, reduce costs, and influence population health. Current data generation greatly exceeds human cognitive capacity to effectively manage information, and AI is likely to have an important and complementary role to human cognition to support delivery of personalized health care. For example, recent innovations in AI have shown high levels of accuracy in imaging and signal detection tasks and are considered among the most mature tools in this domain.
However, there are challenges in realizing the potential for AI in health care. Disconnects between reality and expectations have led to prior precipitous declines in use of the technology, termed AI winters, and another such event is possible, especially in health care. Today, AI has outsized market expectations and technology sector investments. Current challenges include using biased data for AI model development, applying AI outside of populations represented in the training and validation data sets, disregarding the effects of possible unintended consequences on care or the patient-clinician relationship, and limited data about actual effects on patient outcomes and cost of care.
AI in Healthcare: The Hope, The Hype, The Promise, The Peril, a publication by the National Academy of Medicine (NAM), synthesizes current knowledge and offers a reference document for the responsible development, implementation, and maintenance of AI in the clinical enterprise. The publication outlines current and near-term AI solutions; highlights the challenges, limitations, and best practices for AI development, adoption, and maintenance; presents an overview of the legal and regulatory landscape for health care AI; urges the prioritization of equity, inclusion, and a human rights lens for this work; and outlines considerations for moving forward. This Viewpoint shares highlights from the NAM publication.
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