A realistic evaluation of the dark side of data in the digital ecosystem

IF 1.8 4区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Faten Jaber, Muneer Abbad
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引用次数: 0

Abstract

This article examines the negative consequences that can arise from the utilisation of innovative data practices implemented by organisations. While these technologies offer significant value, their improper implementation can lead to harmful practices that undermine the rights of individuals within societies. Through a systematic literature review of 383 articles employing the realistic evaluation theory, this study synthesises key findings to identify the contextual factors that contribute to these harmful practices. The results highlight the challenges posed by the characteristics of Big Data, often resulting in haphazard data implementation scenarios. Three critical mechanisms, namely data transparency, biases, and breaches, interact with these implementation contexts, leading to adverse outcomes that compromise individual empowerment, societal fairness, and personal privacy. In addition, this article identifies important areas for future research and provides recommendations for policymakers to effectively manage the negative aspects of data practices, ensuring sustainability within the digital ecosystem.
对数字生态系统中数据阴暗面的现实评估
本文探讨了利用组织实施的创新数据实践可能产生的负面后果。虽然这些技术提供了巨大的价值,但它们的不当实施可能导致损害社会中个人权利的有害做法。通过对采用现实评估理论的383篇文章的系统文献综述,本研究综合了关键发现,以确定导致这些有害做法的背景因素。研究结果凸显了大数据的特点所带来的挑战,往往导致数据实施场景的偶然性。三个关键机制,即数据透明度、偏见和违规,与这些实施环境相互作用,导致损害个人赋权、社会公平和个人隐私的不利结果。此外,本文还确定了未来研究的重要领域,并为政策制定者提供了有效管理数据实践负面影响的建议,以确保数字生态系统的可持续性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Information Science
Journal of Information Science 工程技术-计算机:信息系统
CiteScore
6.80
自引率
8.30%
发文量
121
审稿时长
4 months
期刊介绍: The Journal of Information Science is a peer-reviewed international journal of high repute covering topics of interest to all those researching and working in the sciences of information and knowledge management. The Editors welcome material on any aspect of information science theory, policy, application or practice that will advance thinking in the field.
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