Automating Welfare

Across Europe, the welfare sector is facing increasing demands and shrinking resources. Calls to mitigate social hardships more effectively and increase public administration's efficiency suggest introducing data-driven decision-support and enhancement with artificial intelligence (AI).

AUTO-WELF is the first project to analyze automated welfare provision across European welfare regimes. It examines the implications of algorithms and AI for the future of European citizens and societies. The project will provide profound insights into how automated decision-making can support but also harm human wellbeing.

Social Justice and Equity in Europe

Data-based infrastructures in public administration have a significant impact on the living circumstances of citizens and on human agency. ADM systems are shaping not only welfare provision and public management but also how citizens encounter, and are addressed by, the state. In short, they transform the relationship between citizens and the state. This prompts many ethical and political questions regarding transparency and accountability, as well as systemic biases and social inequalities.

AUTO-WELF focuses on the perspective of people implicated in the automation process —the system engineers and designers, the caseworkers who collaborate with ADM systems in making decisions about welfare and service provision, and the citizens whose data feed the systems.

The project will develop groundbreaking knowledge on the consequences of automating welfare in two domains: a) core welfare services, such as employment services, healthcare, and social benefits provision, and b) automation of communal welfare infrastructures and services, including smart city and smart village initiatives that aim at providing automated social infrastructures for community building and urban development. We explore these domains across eight European countries: Austria, Germany, Italy, Portugal, Estonia, Poland, Denmark and Sweden represent different types of the welfare state and various stages of automated decision-making.