医疗人工智能在带来诸多益处的同时，也存在新的风险。以下为您举例说明其风险及法律防范：
以自动化医疗分诊系统为例，其具有适应性和自主性。适应性方面，它能基于对医疗数据集、患者记录和实时健康数据的分析来预测患者病情；自主性方面，它能为医疗专业人员或直接为患者生成有关症状可能原因的信息，并推荐潜在的干预和治疗措施。
然而，这也带来了一些风险和监管问题。比如，若该系统提供了错误的医疗建议，导致患者出现负面健康结果，责任归属不明确，影响患者获得赔偿。
在法律防范方面，需要明确此类系统的责任界定，制定相关法律法规，确保患者在因错误建议受到损害时能够获得有效的救济。同时，应加强对医疗人工智能系统的监管和评估，确保其准确性和可靠性。
and adaptive characteristics.While many aspects of the technologies described in these casestudies will be covered by existing law,they illustrate how AI-specific characteristics introducenovel risks and regulatory implications.Figure 1:Illustration of our strategy for regulating AIcharacteristics ensure any current or future AI system that meets this criteria will be within scope.See A guide to using artificialintelligence in the public sector,Government Digital Service and Office for Artificial Intelligence,2019.A pro-innovation approach to AI regulationCase study 3.1:Natural language processing in customer service chatbotsAdaptivity:Provides responses to real-time customer messages,having been trained onhuge datasets to identify statistical patterns in ordinary human speech,potentiallyincreasing personalisation over time as the system learns from each new experience.Autonomy:Generates a human-like output based on the customer's text input,to answerqueries,help customers find products and services,or send targeted updates.Operateswith little need for human oversight or intervention.Illustrative AI-related regulatory implication:Unintentional inclusion of inaccurate ormisleading information in training data,producing harmful instructions or convincinglyspreading misinformation.Case study 3.2:Automated healthcare triage systemsAdaptivity:Predicts patient conditions based on the pathology,treatment and risk factorsassociated with health conditions from the analysis of medical datasets,patient recordsand real-time health data.Autonomy:Generates information about the likely causes of a patient’s symptoms andrecommends potential interventions and treatments,either to a medical professional orstraight to a patient.Illustrative AI-related regulatory implication:Unclear liability for an AI triage systemthat provides incorrect medical advice,leading to negative health outcomes for a patientand affecting the patient's ability to obtain redress.Case study 3.3:Text-to-image generatorsAdaptivity:Uses large amounts of online content to learn how to create rich,highlyspecific images on the basis of a short text prompt.Autonomy:Based on text input,these systems generate images that mimic the qualities
欧洲议会和欧盟理事会规定人工智能的统一规则，并修正300/2008号、167/2013号、168/2013号、2018/858号、2018/1139号和2019/214号条例以及2014/90/EU号、2016/797号和20(58)另一个值得特别考虑的,使用人工智能系统的领域,是获得和享受特定的必要的私人和公共服务和福利,这是人们充分参与社会或提高生活水平所必需的。特别是,申请或接受公共机关提供的基本公共援助福利和服务,即医疗保健服务、社会保障福利、在生育、疾病、工伤事故、依赖或年老和失业情况下提供的社会保护以及社会和住房援助的自然人,通常依赖于这些福利和服务,相对于负有权责的机关来说处于弱势地位。如果机关使用人工智能系统来决定是否应给予、拒绝、减少、取消或收回这些福利和服务,包括受益人是否合法享有这些福利或服务,这些系统可能会对人们的生计产生重大影响,并可能侵犯他们的基本权利,如社会保护权、不受歧视权、人的尊严权或有效补救权,因此应被列为高风险系统。尽管如此,本条例不应妨碍公共行政部门开发和使用创新方法,因为更广泛地使用合规和安全的人工智能系统将使公共行政部门受益,前提是这些系统不会给法人和自然人带来高风险。此外,用于评估自然人的信用分数或信用度的人工智能系统应被归类为高风险人工智能系统,因为它们决定了这些人获得金融资源或住房、电力和电信服务等基本服务的机会。用于此目的的人工智能系统可能会导致对个人或群体的歧视,并延续历史上的歧视模式,例如基于种族或民族血统、性别、残疾、年龄、性取向的歧视,或造成新形式的歧视性影响。然而,根据本条例,欧盟法律规定的用于检测提供金融服务过程中的欺诈行为以及用于计算信贷机构和保险企业资本要求的尽职审慎目的的人工智能系统不应视为高风险系统。此外,用于自然人健康和人寿保险风险评估和定价的人工智能系统也会对人们的生活产生重大影响,如果设计
the new risks that may arise from their use,nor the unease that the complexity of AItechnologies can produce in the wider public.We already know that some uses of AI couldThe use of AI in healthcare and medicine is booming,Insider Intelligence,2023.How to fight climate change using AI,Forbes,2022; Tackling Climate Change with Machine Learning,Rolnick et al.,2019.DeepMind’s protein-folding AI cracks biology’s biggest problem,New Scientist,2022; Improved protein structure predictionusing potentials from deep learning,Senior et al.,2020.The UK Science and Technology Framework,Department for Science,Innovation and Technology,2023.Six of the best future uses of Artificial Intelligence,Technology Magazine,2023; Multidisciplinary perspectives on emergingchallenges,opportunities,and agenda for research,practice and policy,Dwivedi et al.,2021.Large dedicated AI companies make a major contribution to the UK economy,with GVA(gross value added)per employeeestimated to be £400k,more than double that of comparable estimates of large dedicated firms in other sectors.See AI SectorStudy 2022,DSIT,2023.Pro-innovation Regulation of Technologies Review:Digital Technologies,HM Treasury,2023.A pro-innovation approach to AI regulationdamage ourphysical8and mentalhealth,9infringe on the privacy ofindividuals10and underminehumanrights.11