Skip to search boxSkip to navigationSkip to main content

" We Would Never Write That Down" Classifications of Unemployed and Data Challenges for AI

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Open access

Abstract

This paper draws attention to new complexities of deploying artificial intelligence (AI) to sensitive contexts, such as welfare allocation. AI is increasingly used in public administration with the promise of improving decision-making through predictive modelling. To accurately predict, it needs all the agreed criteria used as part of decisions, formal and informal. This paper empirically explores the informal classifications used by caseworkers to make unemployed welfare seekers 'fit' into the formal categories applied in a Danish job centre. Our findings show that these classifications are documentable, and hence traceable to AI. However, to the caseworkers, they are at odds with the stable explanations assumed by any bureaucratic recording system as they involve negotiated and situated judgments of people's character. Thus, for moral reasons, caseworkers find them ill-suited for formal representation and predictive …

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Original language

English

Article number

102

Pages from-to (Number of pages)

Pages 1 (26 pages)

Journal (Volume, Issue Number)

Proceedings of the ACM on Human-Computer Interaction - CSCW (Volume 5, Issue CSCW1)

Publication milestones

  • Published - 22/04/2021

Publication status

Published - 22/04/2021

ISSN

2573-0142

Publication IDs

  • Scopus: 85112686825

Publication metrics

PlumX, opens in new tab

Citation count
36
Captures
68

Access to documents