Division of Medical Ethics and Law, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
S Afr Med J. 2023 Dec 31;114(1):22-26. doi: 10.7196/SAMJ.2024.v114i1.1631.
The sanctity of the doctor-patient relationship is deeply embedded in tradition - the Hippocratic oath, medical ethics, professional codes of conduct, and legislation - all of which are being disrupted by big data and 'artificial' intelligence (AI). The transition from paper-based records to electronic health records, wearables, mobile health applications and mobile phone data has created new opportunities to scale up data collection. Databases of unimaginable magnitude can be harnessed to develop algorithms for AI and to refine machine learning. Complex neural networks now lie at the core of ubiquitous AI systems in healthcare. A transformed healthcare environment enhanced by innovation, robotics, digital technology, and improved diagnostics and therapeutics is plagued by ethical, legal and social challenges. Global guidelines are emerging to ensure governance in AI, but many low- and middle-income countries have yet to develop context- specific frameworks. Legislation must be developed to frame liability and account for negligence due to robotics in the same way human healthcare providers are held accountable. The digital divide between high- and low-income settings is significant and has the potential to exacerbate health inequities globally.
医患关系的神圣性深深植根于传统——希波克拉底誓言、医学伦理、专业行为准则和立法——所有这些都被大数据和“人工智能”(AI)所颠覆。从纸质记录到电子健康记录、可穿戴设备、移动健康应用程序和手机数据的转变为数据收集提供了新的机会。可以利用规模庞大的数据库来开发人工智能算法和改进机器学习。复杂的神经网络现在处于医疗保健中无处不在的人工智能系统的核心。创新、机器人技术、数字技术以及诊断和治疗方法的改进,使医疗环境发生了变革,但却存在伦理、法律和社会挑战。正在制定全球准则以确保人工智能的治理,但许多低收入和中等收入国家尚未制定具体国情的框架。必须制定立法,以确定由于机器人而产生的责任和过失,就像追究人类医疗保健提供者的责任一样。高收入和低收入环境之间的数字鸿沟很大,有可能加剧全球健康不平等。