Decision-supporting algorithms in the public sector: The influence on caseworkers’ discretionary assessment and reasoning

Abstract

Caseworkers in the public administration must make decisions based on accurate and objective information and be able to explain their reasoning. They are increasingly relying on decision-supporting algorithms that prioritize output over reasoning. While these algorithms can streamline and improve workflows, they also challenge fundamental principles of legal certainty. Utilizing data from the ASTA report on caseworkers’ experiences with algorithms in risk assessments of newly unemployed individuals as a case, we examine how automation bias and the black box paradox can affect caseworkers’ reasoning and justification of decisions. While the decision-making process may become more efficient in handling large datasets, fundamental principles of the rule of law may be challenged.