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Algorithmic Governmentality, Digital Sovereignty, and Agency Affordances — Extending the Possible Fields of Action

Authors: POP STEFANIJA, Ana; PIERSON, Jo;

Algorithmic Governmentality, Digital Sovereignty, and Agency Affordances — Extending the Possible Fields of Action

Abstract

In today’s socio-technical constellations, our daily online and offline lives are increasingly governed by what can be termed algorithmic governmentality. Understood as the governing of the social based on the algorithmic processing of big data, algorithmic governmentality significantly limits human agency and individuals’ abilities to control data inputs and algorithmic outputs. An antidote and a solution to governance of this kind require assembling conditions for enabling digital sovereignty. Seen as a counter-conduct to governmentality, sovereignty concerns agency, control, autonomy, authority, self-reflection, and self-determination. Foregrounded on empirical research that relates specifically to platform algorithms, this article discusses the requirements for the digital sovereignty of individuals and the socio-technical conditions that should enable that sovereignty. By introducing and conceptualizing the notion of agency affordances, the article provides several illustrative examples of how this sovereignty can be inscribed through the technical and unfold via the societal.

The research was done as part of the project DELICIOS “An integrated ap-proach to study the delegation of conflict-of-interest decisions to autonomous agents” (G054919N), funded by the Fonds voor Wetenschappelijk Onderzoek –Vlaanderen (FWO).

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Belgium
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Keywords

algorithmic governmentality, digital sovereignty, agency affordances

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green