聪明的腐败:游戏问责的讽刺策略

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Ritwick Ghosh, H. Faxon
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引用次数: 1

摘要

尽管新形式的数据可以用来追究权力的责任,但它们也为游戏问责制提供了强大的新资源。我们将后一种行为称为“聪明的腐败”。这一概念强调了挪用算法、基础设施和数据公众来积累利益和掩盖责任的可能性,同时倾向于透明度的积极关联。与传统形式的腐败不同,聪明的腐败被伪装成进步的,因此很难通过现有的法律或道德框架来发现或分析。为了说明这一点,我们概述了一个游戏问责制的讽刺策略。确定在数据驱动的透明度的幌子下进行的违法活动的特定机制和结果,以及在博弈问责制中最积极的关键行为者和组织,是一个重要的研究和政治项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart corruption: Satirical strategies for gaming accountability
Although new forms of data can be used to hold power to account, they also grant the powerful new resources to game accountability. We dub the latter behavior “smart corruption.” The concept highlights the possibility of appropriating algorithms, infrastructures, and data publics to accumulate benefits and obscure responsibility while leaning into the positive associations of transparency. Unlike conventional forms of corruption, smart corruption is disguised as progressive, and is thus difficult to spot or analyze through existing legal or ethical frameworks. To illustrate, we outline a satirical strategy for gaming accountability. Identifying the particular mechanisms and outcomes of transgressive activities carried out under the veneer of data-driven transparency, as well as the key actors and organizations most active in gaming accountability, is an important research and political project.
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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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