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

Anette Petersen, Lars Rune Christensen, Richard Harper, Thomas Hildebrandt

Research output: Journal Article or Conference Article in JournalConference articleResearchpeer-review


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 …
Original languageEnglish
Article number102
JournalProceedings of the ACM on Human-Computer Interaction - CSCW
Issue numberCSCW1
Pages (from-to)1
Number of pages26
Publication statusPublished - 22 Apr 2021

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