Algorithmic Long-Term Unemployment Risk Assessment in Use

Counselors’ Perceptions and Use Practices

Journal article (2020)

Authors

Leid Zejnilović Nova School of Business and Economics, Universidade Nova de Lisboa
Susana Lavado Nova School of Business and Economics, Universidade Nova de Lisboa
I. Martinez de Rituerto de Troya Nova School of Business and Economics, Universidade Nova de Lisboa
Samantha Sim Nova School of Business and Economics, Universidade Nova de Lisboa
Andrew Bell Nova School of Business and Economics, Universidade Nova de Lisboa
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Published Date

2020

Language

English

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Abstract

The recent surge of interest in algorithmic decision-making among scholars across disciplines is associated with its potential to resolve the challenges common to administrative decision-making in the public sector, such as greater fairness and equal treatment of each individual, among others. However, algorithmic decision-making combined with human judgment may introduce new complexities with unclear consequences. This article offers evidence that contributes to the ongoing discussion about algorithmic decision-making and governance, contextualizing it within a public employment service. In particular, we discuss the use of a decision support system that employs an algorithm to assess individual risk of becoming long-term unemployed and that informs counselors to assign interventions accordingly. We study the human interaction with algorithms in this context using the lenses of human detachment from and attachment to decision-making. Employing a mixed-method research approach, we show the complexity of enacting the potentials of the data-driven decision-making in the context of a public agency.