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Automating Welfare

Automating Welfare

Doris Allhutter (ORCID: 0000-0002-0820-8186)
  • Grant DOI 10.55776/I6075
  • Funding program International - Multilateral Initiatives
  • Status ongoing
  • Start November 1, 2022
  • End December 31, 2025
  • Funding amount € 306,074

ERA-Net: HERA

Disciplines

Other Social Sciences (50%); Other Technical Sciences (40%); Political Science (10%)

Keywords

    Automated Decision-Making, Public Sector, Welfare, Sociotechnical Systems

Abstract

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 automated decision-making. There is a vision that welfare can be radically transformed through data-driven decision-support and enhancement with artificial intelligence. In many areas, automation is thought to increase productivity with less effort and lower costs. What happens to human flourishing, social justice, and equity when this logic is deployed to support decisions in the welfare sector? AUTO-WELF investigates the extensive implementation of automated decision-making (ADM) in the welfare sector across Europe. It is the first project to provide an analysis of automated welfare provision across different European welfare regimes. It examines the implications of algorithms and artificial intelligence for the future of European citizens and societies. Emerging ADM systems perform many functions in societysome of which are mundane and perceived as relatively unproblematic and beneficial for citizens. Still, others can disrupt and change living circumstances. Data-based infrastructures for public administration have an impact on human agency within complex socio-technical systems. This prompts many ethical and political questions regarding transparency and accountability, as well as systemic biases and social inequalities. ADM systems are shaping not only welfare provision and public management but also how citizens encounter and are addressed by the state and how the relationship between citizens and the state is transformed. AUTO-WELF foregrounds 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 people whose data feed the systems and who are targeted in processes of enhancing welfare through automation. 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 and Germany, Italy and Portugal, Estonia and Poland, and, Denmark and Sweden represent different types of the welfare state and different stages of automated decision-making. With its interdisciplinary approach, AUTO-WELF will provide an in-depth and cutting-edge understanding of automating welfare from a European perspective. The project will deliver highly relevant insights into how automated decision-making can support but also harm human flourishing.

Research institution(s)
  • Österreichische Akademie der Wissenschaften - 100%
International project participants
  • Anu Masso, Tallinn University of Technology - Estonia
  • Alice Mattoni, University of Bologna - Italy
  • Ana Jorge, Universidade Lusofona - Portugal

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(Entrance Wiesingerstraße 4)
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office(at)fwf.ac.at
+43 1 505 67 40

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