Social Networks, Functional Differentiation of Society, and Data Protection
J\"org Pohle

TL;DR
This paper discusses how social networks threaten societal functional differentiation and individual autonomy by centralizing data, emphasizing the importance of structural data protections inspired by systems theory to prevent totalitarian risks.
Contribution
It applies systems theory to analyze data protection, highlighting the societal risks posed by social networks and proposing the need for structural limitations to safeguard societal functions.
Findings
Social networks threaten societal differentiation and individual autonomy.
Centralized data collection by social networks poses totalitarian risks.
Structural data protections are necessary to prevent societal harm.
Abstract
Most scholars, politicians, and activists are following individualistic theories of privacy and data protection. In contrast, some of the pioneers of the data protection legislation in Germany like Adalbert Podlech, Paul J. M\"uller, and Ulrich Dammann used a systems theory approach. Following Niklas Luhmann, the aim of data protection is (1) maintaining the functional differentiation of society against the threats posed by the possibilities of modern information processing, and (2) countering undue information power by organized social players. It could be, therefore, no surprise that the first data protection law in the German state of Hesse contained rules to protect the individual as well as the balance of power between the legislative and the executive body of the state. Social networks like Facebook or Google+ do not only endanger their users by exposing them to other users or the…
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Taxonomy
TopicsPublic Administration and Political Analysis · Sociology and Education Studies · Psychoanalysis and Social Critique
