Aldosari Bakheet, Aldosari Hanan, Alanazi Abdullah
College of Public Health and Health Informatics, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Stud Health Technol Inform. 2025 Apr 8;323:16-20. doi: 10.3233/SHTI250039.
Artificial Intelligence (AI) holds great promise for healthcare, promising improved patient outcomes and streamlining processes. Nevertheless, this transformational journey comes with numerous potential pitfalls that warrant attention. This comprehensive review explores some key challenges involved with integrating AI into medicine. First and foremost is the risk of over-reliance on AI systems. Users often rely on recommendations provided by AI to follow without question, potentially causing automation bias. Human oversight is essential to avoid mistakes and patient harm; failure to provide such oversight could have serious repercussions that necessitate having someone in control at all times - emphasizing the necessity for having a human-in-the-loop approach. Ethical considerations must always come first when developing AI systems, with privacy, informed consent, and data protection as non-negotiable obligations for patients and organizations. Transparency and accountability within AI systems are necessary to quickly identify biases or errors to enable AI development with integrity that mitigates bias, ensures fairness, and maintains transparency. Ethical AI development involves ongoing efforts made with great diligence by developers to mitigate any bias, ensure fairness, and maintain transparency. These principles form the bedrock upon which ethical development depends. Collaboration between healthcare providers and AI developers is of utmost importance for patient safety and well-being; healthcare providers must protect patient data while developers must ensure AI systems adhere to legal and ethical requirements. AI and healthcare present significant challenges. Ethical frameworks, bias mitigation techniques, and transparency measures must all be pursued to advance AI's role within healthcare delivery systems. We can unleash AI's full potential by overcoming such hurdles while upholding patient safety, ethics, and quality care as the cornerstones of healthcare innovation.
人工智能（AI）在医疗保健领域前景广阔，有望改善患者治疗效果并简化流程。然而，这一变革之旅伴随着诸多潜在陷阱，值得关注。本全面综述探讨了将人工智能融入医学所涉及的一些关键挑战。首先也是最重要的是过度依赖人工智能系统的风险。用户常常不假思索地遵循人工智能提供的建议，这可能导致自动化偏差。人为监督对于避免错误和患者伤害至关重要；未能提供这种监督可能会产生严重后果，这就需要始终有人进行掌控——强调了采用“人在回路”方法的必要性。在开发人工智能系统时，伦理考量必须始终放在首位，隐私、知情同意和数据保护是患者及组织不可协商的义务。人工智能系统内部的透明度和问责制对于快速识别偏差或错误至关重要，以便能够进行具有完整性的人工智能开发，减轻偏差、确保公平并保持透明度。符合伦理的人工智能开发需要开发者持续不懈地努力，以减轻任何偏差、确保公平并保持透明度。这些原则构成了符合伦理的开发所依赖的基石。医疗保健提供者与人工智能开发者之间的合作对于患者安全和福祉至关重要；医疗保健提供者必须保护患者数据，而开发者必须确保人工智能系统符合法律和伦理要求。人工智能与医疗保健带来了重大挑战。必须推行伦理框架、偏差缓解技术和透明度措施，以提升人工智能在医疗服务系统中的作用。通过克服这些障碍，同时将患者安全、伦理和优质护理作为医疗保健创新的基石，我们能够释放人工智能的全部潜力。
