A Comprehensive Approach to Responsible AI Development and Deployment

IF 5

Mayo Clinic Proceedings. Digital health Pub Date : 2025-12-01 Epub Date: 2025-10-10 DOI:10.1016/j.mcpdig.2025.100294

Sonya Makhni MD, MBA, MS , Jose Rico MBA , Paul Cerrato MA , Brenton Hill JD, MHA , Shauna Overgaard PhD , Jeffrey Wu MPH , Justin Fairbanks MS , Rachelann Tripp MPH , Justin Redziniak DPT , Roberto Blundo MPH , Clark Otley MD , John Halamka MD, MS

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Abstract

Integrating artificial intelligence (AI) into health care offers the potential to address critical challenges related to access to care, workforce burnout, and health inequities. Despite its promise, AI adoption remains limited due to safety, efficacy, and equity concerns. This paper presents a novel and comprehensive framework for responsible AI development, evaluation, and deployment in health care, encompassing four key phases: (1) AI Solution Design and Development, (2) AI Solution Qualification, (3) AI Solution Efficacy and Safety Evaluation, and (4) AI Solution Impact. By establishing rigorous standards for operational, clinical, and technical quality, the framework aims to guide AI developers and health care professionals toward creating AI solutions that are ethical, effective, and scalable. This structured approach fosters collaboration and mitigates risks to help AI achieve its full potential in improving patient outcomes and health care efficiency.

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负责任的人工智能开发和部署的综合方法

将人工智能（AI）整合到医疗保健中，有可能解决与获得医疗服务、劳动力倦怠和卫生不平等相关的关键挑战。尽管前景光明，但由于安全性、有效性和公平性问题，人工智能的应用仍然有限。本文提出了一个新的、全面的框架，用于负责任的人工智能开发、评估和部署在医疗保健中，包括四个关键阶段：(1)人工智能解决方案的设计和开发，(2)人工智能解决方案的鉴定，(3)人工智能解决方案的有效性和安全性评估，(4)人工智能解决方案的影响。通过建立严格的操作、临床和技术质量标准，该框架旨在指导人工智能开发人员和医疗保健专业人员创建合乎道德、有效和可扩展的人工智能解决方案。这种结构化的方法促进了协作，降低了风险，帮助人工智能充分发挥其在改善患者治疗结果和医疗效率方面的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mayo Clinic Proceedings. Digital health Medicine and Dentistry (General), Health Informatics, Public Health and Health Policy

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审稿时长

47 days