数据和数字情报共享(为其社区所有权提出理由)

P. Singh
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引用次数: 2

摘要

数字技术曾经有望成为一个伟大的均衡器。然而,随着数字经济的形成,全球不平等现象正在急剧加剧。垂直整合的全球数字企业将以对数据的独家控制为基础,统治经济的各个领域,从而进一步集中经济力量。对这类数字公司的监管存在政治瘫痪。主导的数字模式和实践向更大的公平性和可持续性的任何转变,首先都需要对数据的政治经济学及其贡献的数字智能进行检查。显然,世界各地的政策制定者都渴望探索广泛共享数据的方法,以便国内企业能够轻松获得这些数据。但是,在最高层缺乏理解和政治意愿,无法为此目的制定所需的新政策和法律,也缺乏可行的实际数据共享模式。很少有理论工作探索数据经济治理的替代模型。本文在这方面尝试了一些新的方向。数字经济可以被理解为包括运行整个部门的智能系统,利用基于数据的数字智能来重新组织和协调它们。在这样的宏观理解下,有可能应用埃莉诺·奥斯特罗姆(Elinor Ostrom)开发的制度分析与发展(IAD)框架,在主导模式下检查特定部门(如交通)社区层面的数据和数字情报资源管理。这样的分析表明,几乎所有关键IAD评估参数的结果都非常不理想;从效率和公平到问责制和可持续性。然后,论文建议将数据和数字智能视为共同财产制度下的公共资源池。它简要地考虑了稳健和公平的数字经济可能和必要的数据治理安排。讨论还包含了关键的当代数据相关问题,如围绕数据的全球自由流动和依赖平台的行动者(如出租车司机和交易员)的数据权利的争论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data and Digital Intelligence Commons (Making a Case for their Community Ownership)
Digital technologies once held the promise to be a great equalizer. As a digital economy takes shape, global inequalities however are rising sharply. Vertically integrated global digital corporations are set to rule every sector of the economy based on their exclusive control over its data, further concentrating economic power. There exists a political paralysis over regulation of such digital corporations. Any shift in the dominant digital model and practices towards greater fairness and sustainability requires first of all an examination of the political economy of data, and the digital intelligence that it contributes. Policy makers around the world are evidently becoming eager to explore ways for wide data sharing, with a view to its easy availability for domestic businesses.

But there is a dearth of understanding and political will at the highest levels to develop the required new policies and laws for this purpose, as well as of viable practical models for data sharing. Very little theoretical work explores alternative models for economic governance of data. This paper attempts some new directions in this regard.

The digital economy can be understood as comprising intelligent systems running whole sectors, employing data based digital intelligence to re-organize and coordinate them. Within such a macro understanding, it is possible to apply the framework of Institutional Analysis and Development (IAD) developed by Elinor Ostrom to examine the management of data and digital intelligence resources at the community level in a given sector, like transport, under the dominant model. Such an analysis reveals very suboptimal results on almost all the key IAD evaluation parameters; from efficiency and equity to accountability and sustainability. The paper then proposes treating data and digital intelligence as common pool resources, under common property regimes.

It briefly considers the kind of data governance arrangements that may be possible and necessary for a robust and fair digital economy. The discussion also subsumes key contemporary data related issues like the contestations around free global flows of data and the data rights of platform dependent actors, like taxi drivers and traders.
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