Author Accepted Manuscript (AAM)
Hanna Kreitem and Massimo Ragnedda (2020). Distributed Pool Mining and Digital Inequalities. From Cryptocurrency to Scientific Research, in Journal of Information, Communication and Ethics in Society
Introduction
This article ventures to explore the dynamic relations between consumption and production in novel technologies that utilise end-user computing resources, as an implementation of distributed computing and alternative of attention economy, and the promises and opportunities it provides from the perspective of digital inequalities to promote dialogue on the social aspects of distributed technologies. The discussion flows from setting the scene on digital inequalities in the age of widespread access to discussing distributed computing and later to examining cases of distributed computing provided by the masses of users and the promises of opportunities it offers. The cases were selected to represent different applications of distributed computing, including cryptocurrency distributed mining and contribution to scientific research. Finally, the article compiles lessons learned from the cases studied into a suggested model for a fair revenue model for content and online service providers that utilises user device computing resources, or computational power, rather than their data and attention.
Relations between content providers and consumers have changed dramatically since the inception of the Internet (Yuan et al., 1998). The relationship has shifted from an equal peer-to-peer network, to a more centralised and clearly defined dichotomy of content providers and content consumers or audience (Randall, 1997). In the second stage, Internet users started using the web as a means to share their own content production, in what was termed Web 2.0 (O’Reilly, 2005), with a plethora of platforms and services facilitating that (Constantinides and Fountain, 2008). The advent of Web 2.0 reshaped network power relations and gave user generated content an important value and power in driving Internet use, such as content genereted by users, and data generated about the users, as is the case with social media platforms (Kaplan and Haenlein, 2010).
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Full article here. Distributed pool mining. From Cryptocurrency to Scientific Research Please note that this article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record.
Massimo Ragnedda 