制度化的不信任和人类对人工智能的监督:根据欧盟人工智能法案实现人工智能治理的民主设计

IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Johann Laux
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引用次数: 0

摘要

人类的监督已经成为人工智能(AI)治理的关键机制。人类监督者应该提高人工智能系统的准确性和安全性,维护人类价值观,并建立对技术的信任。然而,实证研究表明,人类在完成监督任务时并不可靠。他们可能缺乏能力或受到有害的激励。这给人类监督的有效性带来了挑战。为了应对这一挑战,本文旨在做出三点贡献。首先,它调查了新兴的监管法律,最重要的是欧盟的人工智能法案(“AIA”)。它将表明,虽然AIA关注人类监督者的能力,但它并没有就如何实现有效的监督提供太多指导,并且对人工智能开发人员的监督义务没有明确定义。其次,本文提出了一种新的人类监督角色分类,根据人工干预是构成人工智能做出或支持的决定,还是纠正人工智能的决定来区分。分类法允许针对所讨论的监督类型提出改进效力的建议。第三,利用民主理论中的学术成果,本文制定了六项规范性原则,将人类对人工智能的监督的不信任制度化。历史上,不信任的制度化已经在民主治理中实践过。这些原则首次应用于人工智能治理,预测了人类监督者的错误,并寻求在制度设计层面减轻这种错误。它们旨在直接提高人类监督的可信度,并间接激发对人工智能治理的良好信任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Institutionalised distrust and human oversight of artificial intelligence: towards a democratic design of AI governance under the European Union AI Act
Abstract Human oversight has become a key mechanism for the governance of artificial intelligence (“AI”). Human overseers are supposed to increase the accuracy and safety of AI systems, uphold human values, and build trust in the technology. Empirical research suggests, however, that humans are not reliable in fulfilling their oversight tasks. They may be lacking in competence or be harmfully incentivised. This creates a challenge for human oversight to be effective. In addressing this challenge, this article aims to make three contributions. First, it surveys the emerging laws of oversight, most importantly the European Union’s Artificial Intelligence Act (“AIA”). It will be shown that while the AIA is concerned with the competence of human overseers, it does not provide much guidance on how to achieve effective oversight and leaves oversight obligations for AI developers underdefined. Second, this article presents a novel taxonomy of human oversight roles, differentiated along whether human intervention is constitutive to, or corrective of a decision made or supported by an AI. The taxonomy allows to propose suggestions for improving effectiveness tailored to the type of oversight in question. Third, drawing on scholarship within democratic theory, this article formulates six normative principles which institutionalise distrust in human oversight of AI. The institutionalisation of distrust has historically been practised in democratic governance. Applied for the first time to AI governance, the principles anticipate the fallibility of human overseers and seek to mitigate them at the level of institutional design. They aim to directly increase the trustworthiness of human oversight and to indirectly inspire well-placed trust in AI governance.
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来源期刊
AI & Society
AI & Society COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
8.00
自引率
20.00%
发文量
257
期刊介绍: AI & Society: Knowledge, Culture and Communication, is an International Journal publishing refereed scholarly articles, position papers, debates, short communications, and reviews of books and other publications. Established in 1987, the Journal focuses on societal issues including the design, use, management, and policy of information, communications and new media technologies, with a particular emphasis on cultural, social, cognitive, economic, ethical, and philosophical implications. AI & Society has a broad scope and is strongly interdisciplinary. We welcome contributions and participation from researchers and practitioners in a variety of fields including information technologies, humanities, social sciences, arts and sciences. This includes broader societal and cultural impacts, for example on governance, security, sustainability, identity, inclusion, working life, corporate and community welfare, and well-being of people. Co-authored articles from diverse disciplines are encouraged. AI & Society seeks to promote an understanding of the potential, transformative impacts and critical consequences of pervasive technology for societies. Technological innovations, including new sciences such as biotech, nanotech and neuroscience, offer a great potential for societies, but also pose existential risk. Rooted in the human-centred tradition of science and technology, the Journal acts as a catalyst, promoter and facilitator of engagement with diversity of voices and over-the-horizon issues of arts, science, technology and society. AI & Society expects that, in keeping with the ethos of the journal, submissions should provide a substantial and explicit argument on the societal dimension of research, particularly the benefits, impacts and implications for society. This may include factors such as trust, biases, privacy, reliability, responsibility, and competence of AI systems. Such arguments should be validated by critical comment on current research in this area. Curmudgeon Corner will retain its opinionated ethos. The journal is in three parts: a) full length scholarly articles; b) strategic ideas, critical reviews and reflections; c) Student Forum is for emerging researchers and new voices to communicate their ongoing research to the wider academic community, mentored by the Journal Advisory Board; Book Reviews and News; Curmudgeon Corner for the opinionated. Papers in the Original Section may include original papers, which are underpinned by theoretical, methodological, conceptual or philosophical foundations. The Open Forum Section may include strategic ideas, critical reviews and potential implications for society of current research. Network Research Section papers make substantial contributions to theoretical and methodological foundations within societal domains. These will be multi-authored papers that include a summary of the contribution of each author to the paper. Original, Open Forum and Network papers are peer reviewed. The Student Forum Section may include theoretical, methodological, and application orientations of ongoing research including case studies, as well as, contextual action research experiences. Papers in this section are normally single-authored and are also formally reviewed. Curmudgeon Corner is a short opinionated column on trends in technology, arts, science and society, commenting emphatically on issues of concern to the research community and wider society. Normal word length: Original and Network Articles 10k, Open Forum 8k, Student Forum 6k, Curmudgeon 1k. The exception to the co-author limit of Original and Open Forum (4), Network (10), Student (3) and Curmudgeon (2) articles will be considered for their special contributions. Please do not send your submissions by email but use the "Submit manuscript" button. NOTE TO AUTHORS: The Journal expects its authors to include, in their submissions: a) An acknowledgement of the pre-accept/pre-publication versions of their manuscripts on non-commercial and academic sites. b) Images: obtain permissions from the copyright holder/original sources. c) Formal permission from their ethics committees when conducting studies with people.
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