Complex ecologies of trust in data practices and data-driven systems
Complex ecologies of trust in data practices and data-driven systems
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数据实践和数据驱动系统中的复杂信任生态
DOI：
10.1080/1369118x.2020.1748090
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发表时间：
2020-04
期刊：
影响因子：
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通讯作者：
Robin Steedman;H. Kennedy;Rhianne Jones
中科院分区：
文献类型：
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作者：
Robin Steedman;H. Kennedy;Rhianne Jones
对数据实践和数据驱动系统的信任被广泛认为既重要又难以捉摸。数据信任赤字已被确定，对此提出的解决方案通常是本地化或个性化的，重点是机构可以做些什么来增加用户对其数据实践的信任，或者是赋予个人用户权力的数据管理模型。关于信任的学术研究通常集中在信任的类型学上。本文将重点转移到那些做的信任，从实证研究，探讨用户的角度来看，BBC的数据实践的结果。这些发现挑战了本地化或个性化解决方案可能有效的假设。他们还建议，数据实践中信任的概念化需要考虑到与数据信任有关的一系列复杂因素，从而超越类型学的产生。在本文中，我们提出了“复杂的信任生态”的概念，作为解决所有这些问题的一种方式。
ABSTRACT Trust in data practices and data-driven systems is widely seen as both important and elusive. A data trust deficit has been identified, to which proposed solutions are often localised or individualised, focusing either on what institutions can do to increase user trust in their data practices or on data management models that empower the individual user. Scholarship on trust often focuses on typologies of trust. This paper shifts the emphasis to those doing the trusting, by presenting findings from empirical research which explored user perspectives on the data practices of the BBC. These findings challenge the assumption that localised or individualised solutions can be effective. They also suggest that conceptualisations of trust in data practices need to account for the complex range of factors which come into play in relation to trust in data and so move beyond the production of typologies. In this paper, we propose the concept of ‘complex ecologies of trust’ as a way of addressing all of these issues.