Automate, Assist, Avoid: Caseworkers’ Perspectives on Applying Large Language Model-Based Assistance in Public Sector Decision-Making Processes

Abstract

Large language models (LLMs) are being introduced into the public sector – for example, to assist caseworkers in making decisions on citizens’ cases. However, there is limited knowledge of how LLM tools can be used effectively in this complex task, including legal and cultural variables. This qualitative study foregrounds the perspectives of caseworkers from a Finnish public institution to dismantle their decision-making process and to build nuanced understanding on which sub-tasks of the process could benefit from the use of LLMs and how. To suggest meaningful uses for LLMs in the public sector, decision-making needs to be understood as a process that consists of several parts and that varies considerably in different contexts. We contribute to the fields of human–computer interaction and public administration by detailing the decision-making process of caseworkers and their perspectives on technological assistance, to suggest practical integration possibilities for LLM tools.