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Going Beyond Obscurity: Organizational Approaches to Data Anonymization

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Publication milestones

  • Published - 2018

Publication status

Published - 2018

Volume

2

Publisher

Association for Computing Machinery, United States

Book series

  • Book series name: Proceedings of the ACM on Human-Computer Interaction - CSCW
    ISSN: 2573-0142

Publication IDs

  • Scopus: 85066421720

Host publication title

Proceedings of the ACM on Human-Computer Interaction - CSCW

Abstract

Anonymization is viewed as a solution to over-exposure of personal information in a data-driven society. Yet how organizations apply anonymization techniques to data for regulatory, ethical or commercial reasons remains underexplored. We investigate how such measures are applied in organizations, asking whether anonymization practices are used, what approaches are considered practical and adequate, and how decisions are made to protect the privacy of data subjects while preserving analytical value. Our findings demonstrate that anonymization is applied to data far less pervasively than expected. Organizations that do employ anonymization often view their practices as sensitive and resort to anonymity by obscurity alongside technical means. Rather than being a purely technical question of applying the right algorithms, anonymization in practice is a complex socio-technical process that relies on multi-stakeholder collaborations. Organizational decision-making about appropriate approaches and the management of responsibility can result in workarounds necessary to negotiate the technical complexit

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