The promises and challenges of addressing artificial intelligence with human rights

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Onur Bakiner
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Abstract

This paper examines the potential promises and limitations of the human rights framework in the age of AI. It addresses the question: what, if anything, makes human rights well suited to face the challenges arising from new and emerging technologies like AI? It argues that the historical evolution of human rights as a series of legal norms and concrete practices has made it well placed to address AI-related challenges. The human rights framework should be understood comprehensively as a combination of legal remedies, moral justification, and political analysis that inform one another. Over time, the framework has evolved in ways that accommodate the balancing of contending rights claims, using multiple ex ante and ex post facto mechanisms, involving government and/or business actors, and in situations of diffuse responsibility that may or may not result from malicious intent. However, the widespread adoption of AI technologies pushes the moral, sociological, and political boundaries of the human rights framework in other ways. AI reproduces long-term, structural problems going beyond issue-by-issue regulation, is embedded within economic structures that produce cumulative negative effects, and introduces additional challenges that require a discussion about the relationship between human rights and science & technology. Some of the reasons for why AI produces problematic outcomes are deep rooted in technical intricacies that human rights practitioners should be more willing than before to get involved in.
用人权来解决人工智能的承诺和挑战
本文探讨了人工智能时代人权框架的潜在承诺和局限性。它解决了这样一个问题:如果有的话,是什么让人权非常适合面对人工智能等新兴技术带来的挑战?报告认为,人权作为一系列法律规范和具体实践的历史演变,使其能够很好地应对与人工智能相关的挑战。人权框架应被全面理解为法律补救、道德辩护和政治分析三者的结合,它们相互促进。随着时间的推移,该框架已演变成能够平衡相互冲突的权利要求的方式,使用多种事前和事后机制,涉及政府和/或商业行为者,以及可能或可能不是由恶意意图造成的责任分散的情况。然而,人工智能技术的广泛采用以其他方式推动了人权框架的道德、社会学和政治界限。人工智能再现了长期的结构性问题,超出了逐个问题的监管范围,嵌入了产生累积负面影响的经济结构中,并引入了额外的挑战,需要讨论人权与科学之间的关系。技术。人工智能产生问题结果的一些原因深深植根于技术的复杂性,人权从业者应该比以前更愿意参与其中。
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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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