无法解释的人工智能的伦理:临床护士的概述
1Senior Lecturer, School of Nursing and Advanced Practice, Liverpool John Moores University, Liverpool.
概括
护理中的人工智能 (AI) 有助于决策,但不可解释的AI (NXAI) 引发了伦理问题. 使用结果验证和清晰沟通的平衡方法对于整合NXAI至关重要,同时保持护理价值观.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 护理信息学 在护理信息学.
- 生物伦理学生物伦理学
背景情况:
- 人工智能 (AI) 在医疗保健中越来越多地被用于改善临床决策并支持诊断和护理规划等护理任务.
- 缺乏透明机制的不可解释AI (NXAI) 的整合引发了对临床实践的问责制,自主性和信任的伦理问题.
研究的目的:
- 在护理专业中探索可解释AI (XAI) 和NXAI之间的伦理考虑和紧张关系.
- 倡导对人工智能在护理中的整合采取平衡的方法,优先考虑道德框架和患者福祉.
主要方法:
- 对人工智能在护理中的应用进行文献综述和伦理分析.
- 检查XAI与护理生物伦理原则与NXAI的优势之间的对齐.
主要成果:
- 可解释的人工智能 (XAI) 通过促进透明度和信任,与护理伦理保持一致.
- 无法解释的人工智能 (NXAI) 提供了卓越的预测准确性和效率,但也带来了重大的伦理挑战.
- 确定需要结果验证,共同问责制和透明的患者沟通.
结论:
- 护士可以通过采用以患者为中心,道德健全的框架,在道德上将NXAI纳入实践.
- 应对NXAI的挑战需要专注于验证结果并保持数字时代的核心护理价值观.
- 为了利用人工智能的好处,同时减轻护理行业的伦理风险,一个平衡的战略至关重要.
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