CEU Electronic Theses and Dissertations, 2021
| Author | Vaitkeviciute, Aiste |
|---|---|
| Title | Understanding The Digital Welfare State: The Failure Of Algorithmic Profiling Of Jobseekers In Austria And Poland |
| Summary | This thesis analyses the factors behind the termination of algorithmic profiling systems used in the public employment services in Austria and Poland. In both countries, the Ministries of Labour and Social Affairs adopted algorithmic profiling systems as innovative tools to modernise and optimise social protection services. Eventually, they had to terminate their use due to discriminatory impact and privacy violations. This thesis aims to shed light on the socio-technical factors that contributed to the failure of algorithmic profiling and thus contribute to the study of the risks related to the ‘digital welfare state.’ The public sector, especially the social protection and welfare domain, is often missing from automation and digitalisation discussions. This thesis uses J. Kingdon’s Multiple Streams Framework (MSF) to analyse how the three independent streams, problem framing, policy development, and political conditions, shaped the fate of algorithmic profiling systems in Austria and Poland. By comparing two cases, this thesis aims to understand the processes, events, and developments that led to the termination of algorithmic profiling rather than improved governance, regulations, and supervision of these tools. The analysis revealed that the lack of policy-makers’ attention to the problem largely contributed to the failure of these systems. |
| Supervisor | Ashraf, Cameran |
| Department | Public Policy MA |
| Full text | https://www.etd.ceu.edu/2021/vaitkeviciute_aiste.pdf |
Visit the CEU Library.
© 2007-2021, Central European University