Democratic erosion of data-opolies: Decentralized Web3 technological paradigm shift amidst AI disruption

Calzada, Igor ORCID: https://orcid.org/0000-0002-4269-830X 2024. Democratic erosion of data-opolies: Decentralized Web3 technological paradigm shift amidst AI disruption. Big Data and Cognitive Computing 8 (3) , 26. 10.3390/bdcc8030026

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Abstract

This article investigates the intricate dynamics of data monopolies, referred to as “data-opolies”, and their implications for democratic erosion. Data-opolies, typically embodied by large technology corporations, accumulate extensive datasets, affording them significant influence. The sustainability of such data practices is critically examined within the context of decentralized Web3 technologies amidst Artificial Intelligence (AI) disruption. Additionally, the article explores emancipatory datafication strategies to counterbalance the dominance of data-opolies. It presents an in-depth analysis of two emergent phenomena within the decentralized Web3 emerging landscape: People-Centered Smart Cities and Datafied Network States. The article investigates a paradigm shift in data governance and advocates for joint efforts to establish equitable data ecosystems, with an emphasis on prioritizing data sovereignty and achieving digital self-governance. It elucidates the remarkable roles of (i) blockchain, (ii) decentralized autonomous organizations (DAOs), and (iii) data cooperatives in empowering citizens to have control over their personal data. In conclusion, the article introduces a forward-looking examination of Web3 decentralized technologies, outlining a timely path toward a more transparent, inclusive, and emancipatory data-driven democracy. This approach challenges the prevailing dominance of data-opolies and offers a framework for regenerating datafied democracies through decentralized and emerging Web3 technologies.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Social Sciences (Includes Criminology and Education)
Additional Information:	License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by/4.0/, Type: open-access
Publisher:	MDPI
Date of First Compliant Deposit:	11 March 2024
Date of Acceptance:	21 February 2024
Last Modified:	11 Mar 2024 12:00
URI:	https://orca.cardiff.ac.uk/id/eprint/167084

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