Affiliation:
1. Accreditation Council for Continuing Medical Education , Chicago, IL 60611 , USA
2. Department of Medical Education and Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine , Chicago, IL 60611 , USA
Abstract
Abstract
Artificial intelligence (AI) holds the promise of addressing many of the numerous challenges healthcare faces, which include a growing burden of illness, an increase in chronic health conditions and disabilities due to aging and epidemiological changes, higher demand for health services, overworked and burned-out clinicians, greater societal expectations, and rising health expenditures.
While technological advancements in processing power, memory, storage, and the abundance of data have empowered computers to handle increasingly complex tasks with remarkable success, AI introduces a variety of meaningful risks and challenges. Among these are issues related to accuracy and reliability, bias and equity, errors and accountability, transparency, misuse, and privacy of data.
As AI systems continue to rapidly integrate into healthcare settings, it is crucial to recognize the inherent risks they bring. These risks demand careful consideration to ensure the responsible and safe deployment of AI in healthcare.
Cited by
4 articles.
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