Hybrid Intelligence for Effective Digital Governance
AI in Administration
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Beschreibung
The algorithmic Leviathan has arrived. Artificial intelligence (AI) is already transforming how governments operate, make decisions, and serve citizens, and there is no turning back. The question is no longer whether AI will reshape public administration, but whether that transformation will produce effective governance or institutional failure.
Recent federal automation initiatives and AI governance reforms lacked meaningful oversight, transparency, and accountability, most notably in the failed Department of Government Efficiency (DOGE). The result was chaos rather than modernization. Meanwhile, nations such as Singapore, South Korea, Japan, Estonia, Sweden, Norway, and Denmark demonstrate that a different path is possible, one grounded in what this book refers to as hybrid intelligence.
Hybrid intelligence offers a dynamic framework for AI governance that maintains accountability, transparency, and ethical safeguards while enabling the proper integration of algorithmic capabilities into public administration. Instead of choosing between unchecked automation and resistance to technological change, hybrid intelligence structures human judgment and machine processing as complementary forces, preventing societal harms while capturing the benefits AI can deliver.
Drawing on evidence from federal initiatives, state legislatures, and municipal implementations across more than fifty countries, this book reveals why some AI deployments succeed while others fail catastrophically, and what separates them. Offering practical guidance for policymakers, administrators, educators, and technology leaders, it charts a responsible course for effective governance in an algorithmic age.
The algorithmic Leviathan has arrived. Artificial intelligence (AI) is already transforming how governments operate, make decisions, and serve citizens, and there is no turning back. The question is no longer whether AI will reshape public administration, but whether that transformation will produce effective governance or institutional failure.
Recent federal automation initiatives and AI governance reforms lacked meaningful oversight, transparency, and accountability, most notably in the failed Department of Government Efficiency (DOGE). The result was chaos rather than modernization. Meanwhile, nations such as Singapore, South Korea, Japan, Estonia, Sweden, Norway, and Denmark demonstrate that a different path is possible, one grounded in what this book refers to as hybrid intelligence.
Hybrid intelligence offers a dynamic framework for AI governance that maintains accountability, transparency, and ethical safeguards while enabling the proper integration of algorithmic capabilities into public administration. Instead of choosing between unchecked automation and resistance to technological change, hybrid intelligence structures human judgment and machine processing as complementary forces, preventing societal harms while capturing the benefits AI can deliver.
Drawing on evidence from federal initiatives, state legislatures, and municipal implementations across more than fifty countries, this book reveals why some AI deployments succeed while others fail catastrophically, and what separates them. Offering practical guidance for policymakers, administrators, educators, and technology leaders, it charts a responsible course for effective governance in an algorithmic age.
Explores the intersection of AI and machine learning with public policy, administration, and governance Includes case studies showcasing successful implementations of AI and ML across different governmental functions Delivers detailed guidelines for ethical AI usage in public sectors
Autor*in
Haris Alibašić
Themen in »Hybrid Intelligence for Effective Digital Governance«
AI machine learning public service delivery Chevron doctrine anti-administrative state citizen engagement natural language processing data privacy policy formulation data governance user-centered design GDPR AI ethics