Algorithmic configurations in caring arrangements

This article examines heterogeneous forms of human relationalities with algorithms envisioned in the development of a public algorithmic system and their anticipated effects. To do that, we focus on the distinct shapes given to both technologies and people by discourses and practices, together with...

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Bibliographic Details
Main Authors: Sonja Trifuljesko, Minna Ruckenstein
Format: Article
Language:English
Published: SAGE Publishing 2024-12-01
Series:Big Data & Society
Online Access:https://doi.org/10.1177/20539517241299726
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Summary:This article examines heterogeneous forms of human relationalities with algorithms envisioned in the development of a public algorithmic system and their anticipated effects. To do that, we focus on the distinct shapes given to both technologies and people by discourses and practices, together with their underlying logics and associated values. Analysing the blog posts documenting the emergence of Omaolo, a digital platform for healthcare and social welfare in Finland, we identify two algorithmic configurations: the ‘service engine’, which aligns with the public administration goals of standardising social and healthcare services in order to provide financial benefits; and the ‘treatment facilitator’, which advances the prevalent goals of social and healthcare professionals preoccupied with the fulfilment of situated care needs. We demonstrate that each of the configurations has different implications for social and healthcare organisations in which algorithmic technologies are deployed, for the professionals working there and for the people seeking public support. While the service engine might seem to undermine the collective bases of public service delivery, the treatment facilitator evidently supports them. Our findings remind us of the importance of research endeavours that acknowledge the complex and creative nature of development work, and consider the various parties and interests involved, in an attempt to attain more caring arrangements for the uses of data and algorithmic techniques in the public sector and beyond.
ISSN:2053-9517