Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption
- Calzada, Igor 12345
- 1 School of Social Sciences, Social Science Research Park (Sbarc/Spark), Wales Institute of Social and Economic Research and Data (WISERD), Cardiff University, Maindy Road, Cathays, Cardiff CF24 4HQ, UK
- 2 Faculty of Social Sciences and Communication, University of the Basque Country, UPV-EHU, Barrio Sarriena s/n, 48940 Leioa, Spain
- 3 Basque Foundation for Science, Ikerbasque, Plaza Euskadi 5, 48009 Bilbao, Spain
- 4 Decentralization Research Centre, 545 King St. W, Toronto, ON W5V 1M1, Canada
- 5 Fulbright Scholar-In-Residence (S-I-R), US-UK Fulbright Commission, Unit 302, 3rd Floor Camelford House, 89 Albert Embankment, London SE1 7TP, UK
ISSN: 2504-2289
Argitalpen urtea: 2024
Alea: 8
Zenbakia: 3
Orrialdeak: 26
Mota: Artikulua
Beste argitalpen batzuk: Big Data and Cognitive Computing
Laburpena
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.
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