Paper Number

ICIS2025-1565

Paper Type

Short

Abstract

Drawing on an autoethnographic study in a public employment service (PES), we reveal how developers, users, and managers of AI experience the fuzziness associated with AI’s specific characteristics of autonomy, learning capacity, and inscrutability. We unpack how this fuzziness manifests at different organizational levels and how the PES copes with AI-generated fuzziness—by accepting, constraining, and leveraging it. Our study highlights that fuzziness in AI systems is not a purely technical phenomenon—it is a socio-technical issue that shapes and is shaped by organizational practices.

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Dec 14th, 12:00 AM

What’s All the Fuzz About? An Ethnographic Study of AI-generated Fuzziness on a Development, Usage, and Managerial Level

Drawing on an autoethnographic study in a public employment service (PES), we reveal how developers, users, and managers of AI experience the fuzziness associated with AI’s specific characteristics of autonomy, learning capacity, and inscrutability. We unpack how this fuzziness manifests at different organizational levels and how the PES copes with AI-generated fuzziness—by accepting, constraining, and leveraging it. Our study highlights that fuzziness in AI systems is not a purely technical phenomenon—it is a socio-technical issue that shapes and is shaped by organizational practices.

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