摘要：在科技日新月异的今天，AI医疗如同一股汹涌的浪潮，正以前所未有的速度席卷着医疗领域。从DeepSeek的火爆发布，到近百家医院的迅速接入，再到医疗领域上市公司的智能化转型加速，AI医疗似乎正以一种“未来已来”的姿态，向我们展示着其无限的潜力和可能。
在科技日新月异的今天，AI医疗如同一股汹涌的浪潮，正以前所未有的速度席卷着医疗领域。从DeepSeek的火爆发布，到近百家医院的迅速接入，再到医疗领域上市公司的智能化转型加速，AI医疗似乎正以一种“未来已来”的姿态，向我们展示着其无限的潜力和可能。
然而，在这股浪潮之中，也隐藏着不小的暗流。AI医疗的应用，虽然被寄予厚望，有望解决医疗资源分布不均、看病难等问题，但同时也引发了患者隐私、信息安全、伦理挑战等多方面的疑虑。其中，一个尤为富有争议的问题是：医院借助AI看病，误诊了谁负责？
这个问题，看似简单，实则复杂。医生作为AI设备的使用者，自然要对诊疗结果进行最终复核，并拥有“一锤定音”的权力，承担相应的责任。这是基本的共识，也是医疗行业的底线。然而，当AI诊疗设备被证明存在系统性缺陷，并最终导致了不良后果时，责任的划分就变得不再那么清晰。
有人可能会说，这有什么好争议的？按照《中华人民共和国民法典》第一千二百二十三条，患者或医疗机构可以要求AI设备的生产者进行赔偿。法律界人士也指出，涉及AI诊疗的医患纠纷，责任应“人机共担”。这看似是一个合理的解决方案，但实际操作起来却远非那么简单。
就拿2024年的那起AI误诊延误治疗案件来说，法院判决医院承担70%责任，AI供应商承担30%责任。这个判决看似公正，但实际上却掩盖了一个重要的问题：如何证明AI产品的缺陷与治疗失败的因果关系？AI诊疗设备，不同于一般的医疗器械，它往往是综合患者体征指标，通过算法和“经验”直接给出“答案”。尤其在面对复杂病情时，其运算过程可能已复杂到难以被人类完全理解。这种“技术黑箱”的存在，使得责任划分变得异常困难。
再来看欧盟的医疗AI误诊诉讼案，法院首次判定算法开发者需承担30%连带责任。这个判决看似为AI医疗的责任划分提供了一个先例，但实际上却也暴露出了法律在面对新技术时的尴尬和无力。因为AI技术的复杂性和不确定性，使得法律很难像对待一般医疗器械那样，对其责任进行明确的界定和划分。
明确技术边界与责任归属，是AI医疗发展中一个绕不开的话题。我们不能因为AI技术的先进性和便利性，就忽视了其可能带来的风险和挑战。每0.1%的失误，都可能成为解剖技术文明缺陷的手术刀，都可能让患者和家庭承受无法言说的痛苦和损失。
有人说，这个时代的责任划定，实质是在人机协同的迷雾中重新标定人性的坐标。这句话说得深刻而准确。因为AI医疗的发展，不仅仅是一个技术问题，更是一个伦理问题、一个法律问题、一个社会问题。它涉及到我们对人性的理解、对责任的认识、对法律的尊重、对社会的关怀。
我们不能因为技术的先进性，就忽视了其可能带来的伦理挑战；我们不能因为技术的便利性，就忽视了其可能带来的安全风险；我们不能因为技术的潜力，就忽视了其可能带来的法律困境。我们必须正视这些问题，勇敢地面对这些挑战，用我们的智慧和勇气，去标定这个时代人性的坐标。
医疗责任划分这块“绊脚石”，虽然可能会让AI在短时间内难以在医疗领域大展拳脚，但这也是我们必须要跨过的门槛。因为只有跨过了这个门槛，我们才能确保AI医疗的健康发展，才能确保患者的权益得到充分的保障，才能确保医疗行业的公平和正义。
所以，让我们勇敢地面对这个挑战吧！让我们用我们的智慧和勇气，去标定这个时代人性的坐标，去书写AI医疗发展的新篇章！
作者简介：梁世杰 中医高年资主治医师，本科学历，从事中医临床工作24年，积累了较丰富的临床经验。师从首都医科大学附属北京中医院肝病科主任医师、著名老中医陈勇，侍诊多载，深得器重，尽得真传！擅用“商汤经方分类疗法”、专病专方结合“焦树德学术思想”“关幼波十纲辨证”学术思想治疗疑难杂症为特色。现任北京树德堂中医研究院研究员，北京中医药薪火传承新3+3工程—焦树德门人（陈勇）传承工作站研究员，国际易联易学与养生专委会常务理事，中国中医药研究促进会焦树德学术传承专业委员会委员，中国药文化研究会中医药慢病防治分会首批癌症领域入库专家。荣获2020年中国中医药研究促进会仲景医学分会举办的第八届医圣仲景南阳论坛“经方名医”荣誉称号。2023年首届京津冀“扁鹊杯”燕赵医学研究主题征文优秀奖获得者。事迹入选《当代科学家》杂志、《中华英才》杂志。
Liang Shijie: How to establish technical boundaries and responsibilities in AI medical care?
In today's rapidly changing technology, AI medical is like a surging wave, sweeping the medical field at an unprecedented speed. From the hot release of DeepSeek, to the rapid access of nearly 100 hospitals, to the acceleration of the intelligent transformation of listed companies in the medical field, AI medical seems to be showing us its infinite potential and possibilities in a "future has come" attitude.
However, there are also not many undercurrents hidden in this wave. Although AI medical applications are expected to solve problems such as uneven distribution of medical resources and difficulty in getting medical treatment, they also raise concerns about patient privacy, information security, and ethical challenges. Among them, one issue is particularly controversial: who is responsible for misdiagnosis if a hospital uses AI to diagnose patients?
This problem, while seemingly simple, is complex. As users of AI devices, doctors are naturally responsible for the final review of diagnosis results and have the authority to make the final decision and bear the corresponding responsibility. This is the basic consensus and the bottom line of the healthcare industry. However, when AI diagnostic equipment is proven to have systemic defects and ultimately leads to adverse consequences, the division of responsibility becomes less clear.
One might say, what's so controversial about this? According to Article 1223 of the Civil Code of the People's Republic of China, patients or medical institutions can request compensation from the manufacturer of AI equipment. Legal experts also pointed out that in medical disputes involving AI diagnosis, the responsibility should be shared between humans and machines. This may seem like a reasonable solution, but it's far from simple in practice.
For example, in the case of AI misdiagnosis and delayed treatment in 2024, the court ruled that the hospital should bear 70% of the responsibility and the AI supplier should bear 30% of the responsibility. This judgment seems fair, but it actually conceals an important issue: how to prove the causal relationship between the defects of AI products and the failure of treatment? AI diagnostic equipment, unlike ordinary medical equipment, often directly gives "answers" through algorithms and "experience" by integrating patient signs and indicators. Especially in the case of complex diseases, the algorithms may be too complex to be fully understood by humans. The existence of such "technical black boxes" makes the division of responsibility extremely difficult.
Looking at the EU's medical AI misdiagnosis lawsuit case, the court first determined that the algorithm developer should bear 30% joint liability. This judgment seems to provide a precedent for the division of responsibility for AI medical treatment, but in fact, it also exposes the awkwardness and inability of the law to deal with new technologies. Because of the complexity and uncertainty of AI technology, it is difficult for the law to clearly define and divide its responsibilities in the same way as it does for general medical devices.
It is a topic that cannot be avoided in the development of AI in the medical field to clarify the technical boundary and responsibility attribution. We cannot ignore the risks and challenges that AI technology may bring because of its advancedness and convenience. Every 0.1% of errors can be a scalpel that is flawed in anatomical civilization, and can cause untold pain and loss to patients and families.
Some say that the definition of responsibility in this era is essentially a remapping of the coordinates of humanity in the fog of human-machine synergy. This is a profound and accurate statement. Because the development of AI in the medical field is not only a technical issue, but also an ethical issue, a legal issue and a social issue. It involves our understanding of human nature, our awareness of responsibility, our respect for the law, our concern for society.
We must not lose sight of the ethical challenges that technology may pose because of its advanced nature; We cannot ignore the security risks that technology poses because of its convenience; We cannot ignore the legal dilemmas that technology may pose because of its potential. We must face these problems, face these challenges bravely, and use our wisdom and courage to map the coordinates of humanity in this era.
This "obstacle" in the division of medical responsibility may make it difficult for AI to make great strides in the medical field in the short term, but it is also a threshold that we must cross. Because only by crossing this threshold can we ensure the healthy development of AI in healthcare, can we ensure that the rights and interests of patients are fully protected, and can we ensure fairness and justice in the healthcare industry.
So let's face this challenge bravely! Let us use our wisdom and courage to mark the coordinates of human nature in this era and write a new chapter in the development of AI medical care!
Author Bio: Liang Shijie is a senior medical practitioner in traditional Chinese medicine with an undergraduate degree. He has been engaged in traditional medicine clinical work for 24 years and has accumulated a wealth of clinical experience. Following Chen Yong, chief physician of liver disease at Beijing Traditional Medicine Hospital, affiliated with Capital Medical University, and renowned old Chinese medicine, he has been treated for many years and received great attention. He specializes in the treatment of difficult diseases using "conversational traditional therapy" and special treatments combined with the academic ideas of Jiao Shude and Guan Yubo's ten-level diagnosis.He is currently a researcher at the Shude Tang TCM Research Institute in Beijing, a fellow at the new 3 + 3 project of traditional Chinese medicine flame inheritance in Beijing - a scholar at the inheritance workstation of Jiao Shude's protégés (Chen Yong),He is a standing committee member of the International Expert Committee on E-learning and Health Care, a member of the Jiao Shude Academic Heritage Special Committee of the Chinese Association for the Advancement of Chinese Medicine Research, and the first cancer specialist to be included in the chapter of the Chinese Pharmaceutical Culture Research Association. Won the 2020 China Association for the Promotion of Traditional Chinese Medicine Zhongjing Medical Branch held the eighth session of the Medical Saint Zhongjing Nanyang Forum "Classic Prescription Famous Doctor" honorary title. The winner of the first Beijing-Tianjin-Hebei "Pingui Cup" Yanzhao Medical Research Essay Award in 2023. His work was featured in the journal Current Scientist and the journal Chinese Talent.
来源：首都专家梁世杰一点号
