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State in Context of Dataism: Swarm of Political Agents and Data Management in Russia and the World

https://doi.org/10.26794/2226-7867-2023-13-6-30-37

Abstract

The article analyzes the transformation of the state in context of dataism. Dataism is a paradigm that (1) recognizes the crucial role of data in policy preparation and evaluation, (2) considers all systems as a structures of data exchange between decentralized agents for coordination and collective decision-making. In context of dataism the state implements information incentives through data policy to receive feedback from citizens and businesses in the form of engagement in management, value creation, production of local innovations. Dataism transforms the state in a swarm of political agents, where collective decision-making becomes possible through data exchange. The swarm model requires effective data management as the creation of organizational, regulatory and infrastructural conditions for the use of the data in policy implementation. The article presents a comparison of the data management results in Russia and different groups of countries within the framework of the global data management map. Russia has significant results in regulatory and structural measurements of data management, but additional solutions are needed in participatory and accountability/transparency measurements. The directions of improving data management in Russia include open data policy, transparency of automated systems, crowdsensing; intersectoral data exchange.

About the Author

D. R. Mukhametov
Financial University
Russian Federation

Daniyar R. Mukhametov —  research associate, Institute of Humanitarian Technologies and Social Engineering; assistant professor, Department of political Science.

Moscow



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Review

For citations:


Mukhametov D.R. State in Context of Dataism: Swarm of Political Agents and Data Management in Russia and the World. Humanities and Social Sciences. Bulletin of the Financial University. 2023;13(6):30-37. (In Russ.) https://doi.org/10.26794/2226-7867-2023-13-6-30-37

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ISSN 2226-7867 (Print)
ISSN 2619-1482 (Online)