Algorithmic Decision‐Making and Harmonization in Multi‐Level Governance Welfare Practices: Empirical Evidence From Belgium

Abstract

Algorithmic decision‐making (ADM) is increasingly used by public organizations to allocate social benefits. However, it remains unclear whether ADM leads to more harmonized decisions, especially in multi‐level governance contexts like Belgium. Therefore, we ask whether, and to what extent, ADM is linked to the harmonization of welfare decisions across local social agencies. More specifically, we analyze decisions related to additional financial support in terms of (a) the likelihood of granting monthly financial support compared to other types of support, and (b) the amount of monthly support granted. In doing so, we focus on REDI, a digital rule‐based algorithmic system designed to assess families' financial needs in Belgium. We draw on an online survey with respondents from 344 public centers for social welfare (PCSW), 40 interviews with respondents from 20 PCSWs, and policy guidelines from 86 PCSWs. Our findings demonstrate that the adoption of REDI can be linked to harmonization, yet only regarding the form and height of support, with users being more inclined to grant support monthly and provide a higher amount. Nonetheless, variance in welfare decisions persists, indicating a half‐hearted harmonization. With both financial and normative considerations at the local level playing a significant role in how the ADM system is shaped and implemented, this study highlights the importance of examining the organizational and political context in which ADM systems are deployed to understand their influence on welfare decisions.