How the EU AI Act Seeks to Establish an Epistemic Environment of Trust.

IF 1.3 Q3 ETHICS Asian Bioethics Review Pub Date : 2024-06-24 eCollection Date: 2024-07-01 DOI:10.1007/s41649-024-00304-6
Calvin Wai-Loon Ho, Karel Caals
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Abstract

With focus on the development and use of artificial intelligence (AI) systems in the digital health context, we consider the following questions: How does the European Union (EU) seek to facilitate the development and uptake of trustworthy AI systems through the AI Act? What does trustworthiness and trust mean in the AI Act, and how are they linked to some of the ongoing discussions of these terms in bioethics, law, and philosophy? What are the normative components of trustworthiness? And how do the requirements of the AI Act relate to these components? We first explain how the EU seeks to create an epistemic environment of trust through the AI Act to facilitate the development and uptake of trustworthy AI systems. The legislation establishes a governance regime that operates as a socio-epistemological infrastructure of trust which enables a performative framing of trust and trustworthiness. The degree of success that performative acts of trust and trustworthiness have achieved in realising the legislative goals may then be assessed in terms of statutorily defined proxies of trustworthiness. We show that to be trustworthy, these performative acts should be consistent with the ethical principles endorsed by the legislation; these principles are also manifested in at least four key features of the governance regime. However, specified proxies of trustworthiness are not expected to be adequate for applications of AI systems within a regulatory sandbox or in real-world testing. We explain why different proxies of trustworthiness for these applications may be regarded as 'special' trust domains and why the nature of trust should be understood as participatory.

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欧盟人工智能法案如何寻求建立信任的知识环境?
我们重点关注数字医疗领域人工智能(AI)系统的开发和使用,并思考以下问题:欧盟(EU)如何通过《人工智能法》来促进可信赖的人工智能系统的开发和应用?在《人工智能法案》中,可信度和信任意味着什么,它们与生物伦理学、法律和哲学中正在进行的关于这些术语的讨论有什么联系?可信度的规范性要素是什么?人工智能法》的要求与这些要素有何关联?我们首先解释欧盟如何寻求通过《人工智能法》创造一个信任的认识论环境,以促进可信赖的人工智能系统的开发和应用。该法建立了一个治理制度,作为信任的社会认识论基础设施,它促成了对信任和可信度的执行框架。在实现立法目标的过程中,信任和可信度的执行行为所取得的成功程度可以通过法定的可信度代用指标来评估。我们的研究表明,这些执行行为要想值得信赖,就必须符合立法所认可的道德原则;这些原则也至少体现在治理制度的四个关键特征中。然而,对于人工智能系统在监管沙盒或真实世界测试中的应用来说,特定的可信度代理并不足够。我们解释了为什么这些应用中的不同可信度代理可被视为 "特殊 "信任域,以及为什么信任的本质应被理解为参与性。
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来源期刊
CiteScore
6.20
自引率
3.40%
发文量
32
期刊介绍: Asian Bioethics Review (ABR) is an international academic journal, based in Asia, providing a forum to express and exchange original ideas on all aspects of bioethics, especially those relevant to the region. Published quarterly, the journal seeks to promote collaborative research among scholars in Asia or with an interest in Asia, as well as multi-cultural and multi-disciplinary bioethical studies more generally. It will appeal to all working on bioethical issues in biomedicine, healthcare, caregiving and patient support, genetics, law and governance, health systems and policy, science studies and research. ABR provides analyses, perspectives and insights into new approaches in bioethics, recent changes in biomedical law and policy, developments in capacity building and professional training, and voices or essays from a student’s perspective. The journal includes articles, research studies, target articles, case evaluations and commentaries. It also publishes book reviews and correspondence to the editor. ABR welcomes original papers from all countries, particularly those that relate to Asia. ABR is the flagship publication of the Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore. The Centre for Biomedical Ethics is a collaborating centre on bioethics of the World Health Organization.
期刊最新文献
Governance of Medical AI. Leonardo D. de Castro, 1952–2024 How the EU AI Act Seeks to Establish an Epistemic Environment of Trust. Existing and Emerging Capabilities in the Governance of Medical AI. Moving beyond Technical Issues to Stakeholder Involvement: Key Areas for Consideration in the Development of Human-Centred and Trusted AI in Healthcare.
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