Promotionstandem 5: Machine decision support in welfare state institutions: Usage options, implications, and regulatory needs
Modern artificial intelligence and machine learning techniques are increasingly being applied in complex decision-making situations to support or even replace human decisions. Machine- and evidence-based decision support offers the opportunity to improve the quality and legitimacy of decisions. However, the use of machine decision systems often comes at the expense of transparency and understandable decision criteria. Particularly in (welfare) state application contexts, this would jeopardize fundamental democratic principles. Based on this tension, the MAEWIN project aims to examine the opportunities and risks of automated text and data analysis for evidence-based recommendations in the field of social services. In the prototypical utilization, democratic principles such as inclusion, participation, equal rights, and the autonomy of decision-makers in the decision-making and balancing process should be sustainably ensured.