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Data governance: Organizing data for trustworthy Artificial Intelligence
Government Information Quarterly ( IF 8.490 ) Pub Date : 2020-06-21 , DOI: 10.1016/j.giq.2020.101493
Marijn Janssen , Paul Brous , Elsa Estevez , Luis S. Barbosa , Tomasz Janowski

The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements. However, they all rely on data which is not only big, open and linked but varied, dynamic and streamed at high speeds in real-time. Managing such data is challenging. To overcome such challenges and utilize opportunities for BDAS, organizations are increasingly developing advanced data governance capabilities. This paper reviews challenges and approaches to data governance for such systems, and proposes a framework for data governance for trustworthy BDAS. The framework promotes the stewardship of data, processes and algorithms, the controlled opening of data and algorithms to enable external scrutiny, trusted information sharing within and between organizations, risk-based governance, system-level controls, and data control through shared ownership and self-sovereign identities. The framework is based on 13 design principles and is proposed incrementally, for a single organization and multiple networked organizations.



中文翻译:

数据治理:为可靠的人工智能组织数据

大数据,开放数据和链接数据(BOLD)的兴起使大数据算法系统(BDAS)经常基于机器学习,神经网络和其他形式的人工智能(AI)。随着人们越来越多地要求此类系统做出对个人,社区和整个社会而言重要的决定,其容忍的失败是不能容忍的,并且它们受到严格的法规和道德要求的约束。但是,它们都依赖于不仅是大的,开放的和链接的数据,而且是变化的,动态的和实时高速流式传输的数据。管理此类数据具有挑战性。为了克服这些挑战并利用BDAS的机会,组织越来越多地开发高级数据治理功能。本文回顾了此类系统的数据治理挑战和方法,并提出了可信赖的BDAS的数据治理框架。该框架促进数据,流程和算法的管理,数据和算法的受控开放,以实现外部审查,组织内部和组织之间的可信信息共享,基于风险的治理,系统级控制以及通过共享所有权和自我控制的数据控制-主权身份。该框架基于13个设计原则,并针对单个组织和多个网络组织逐步提出。通过共享所有权和自我主权身份进行数据控制。该框架基于13个设计原则,并针对单个组织和多个网络组织逐步提出。通过共享所有权和自我主权身份进行数据控制。该框架基于13个设计原则,并针对单个组织和多个网络组织逐步提出。

更新日期:2020-06-21
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