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Participatory artificial intelligence in public social services = from bias to fairness in assessing beneficiaries /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Participatory artificial intelligence in public social services/ edited by Petra Ahrweiler.
Reminder of title:	from bias to fairness in assessing beneficiaries /
other author:	Ahrweiler, Petra.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xi, 306 p. :ill., digital ;24 cm.
[NT 15003449]:	Using a Case Study Approach for Investigating the Status Quo and Future Options of AI-based Social Assessment in Public Service Provision -- Inclusive Technology Co-Design for Participatory AI -- Ethical Aspects of Research on AI-based Social Assessment -- Participatory Action Research for AI in Social Services: An Example of Local Practices from Catalonia -- Specialists and Algorithms: Implementation of AI in the Delivery of Unemployment Services in Estonia -- AI Use in the Asylum Procedure in Germany: Exploring Perspectives with Refugees and Supporters on Assessment Criteria and Beyond -- Social Assessment for the Targeted Subsidies Plan as a Social Service Provision in Iran: AI Application in the Targeted Subsidies Plan -- Social Assessment and Cultural Resistance: The Public Distribution System in Tamil Nadu, India -- The Role of AI in Effective Social Protection Delivery: The National Cash Transfer Programme in Nigeria -- The Potential of Artificial Intelligence in the Assessment of System of Social Integration of Veterans of the Russian-Ukrainian War -- Assessment for AI in Social Services: Community Virtual Nursing Home in Shanghai, China -- AI Integration in Mental Health Services: Examining Trends in the US and Peoria, Illinois -- Towards Culture-Sensitive, Responsive and Participatory AI.
Contained By:	Springer Nature eBook
Subject:	Social service - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-71678-2
ISBN:	9783031716782

Participatory artificial intelligence in public social services = from bias to fairness in assessing beneficiaries /
Participatory artificial intelligence in public social servicesfrom bias to fairness in assessing beneficiaries /[electronic resource] :edited by Petra Ahrweiler. - Cham :Springer Nature Switzerland :2025. - xi, 306 p. :ill., digital ;24 cm. - Artificial intelligence, simulation and society,3004-9830. - Artificial intelligence, simulation and society..

Using a Case Study Approach for Investigating the Status Quo and Future Options of AI-based Social Assessment in Public Service Provision -- Inclusive Technology Co-Design for Participatory AI -- Ethical Aspects of Research on AI-based Social Assessment -- Participatory Action Research for AI in Social Services: An Example of Local Practices from Catalonia -- Specialists and Algorithms: Implementation of AI in the Delivery of Unemployment Services in Estonia -- AI Use in the Asylum Procedure in Germany: Exploring Perspectives with Refugees and Supporters on Assessment Criteria and Beyond -- Social Assessment for the Targeted Subsidies Plan as a Social Service Provision in Iran: AI Application in the Targeted Subsidies Plan -- Social Assessment and Cultural Resistance: The Public Distribution System in Tamil Nadu, India -- The Role of AI in Effective Social Protection Delivery: The National Cash Transfer Programme in Nigeria -- The Potential of Artificial Intelligence in the Assessment of System of Social Integration of Veterans of the Russian-Ukrainian War -- Assessment for AI in Social Services: Community Virtual Nursing Home in Shanghai, China -- AI Integration in Mental Health Services: Examining Trends in the US and Peoria, Illinois -- Towards Culture-Sensitive, Responsive and Participatory AI.

Open access.

This open access edited volume focuses on fairness issues concerning the use of artificial intelligence (AI) for social service provision in national welfare systems. With this, it touches upon important questions in the innovation agenda of countries across continents about the ethics, justice, quality, responsibility, accountability, and transparency to use AI for state functions. The volume shows that in many countries, AI, or at least data analytics methods, are already in place to support the assessment of beneficiaries for deciding on the value criteria to distinguish between legal /fraudulent, deserving/non-deserving, or needy/non-needy recipients. The book provides a cross-cultural comparison of AI-based social assessment among national welfare systems of 9 countries across 4 continents: Spain, Estonia, Germany, Iran, India, Nigeria, Ukraine, China and USA. Based on participatory research results from multi-stakeholder inputs, especially those from vulnerable groups, the chapters in this volume show that value criteria for fairness and social justice are context-bound and vary across the globe. Furthermore, they are in constant flux, aligned to social change. Thus, the volume looks at pathways to developing culture-sensitive, responsive and participatory AI for social assessment in public service provision. The contributions are interdisciplinary and introduce perspectives from the fields of sociology, computational social science, computer science and public policy. This topical volume is of interest to a wide readership.

ISBN: 9783031716782

Standard No.: 10.1007/978-3-031-71678-2doiSubjects--Topical Terms:

780691
Social service
--Data processing.

LC Class. No.: HV29.2

Dewey Class. No.: 361.0028563

Participatory artificial intelligence in public social services = from bias to fairness in assessing beneficiaries /
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