The Automation Threat

Chapter 5 examines the dual nature of artificial intelligence (AI) automation in public administration, where technological advancement promises efficiency gains while threatening widespread job displacement among clerical, administrative, and middle-management roles. The analysis identifies critical systemic risks including reliance on outdated datasets, insufficient oversight mechanisms, and erosion of human accountability, illustrated through cautionary examples such as the UK Post Office Horizon scandal and Michigan’s MiDAS unemployment fraud detection system. The chapter explores implementation challenges spanning legacy system integration, data quality issues, and human resistance factors while highlighting fairness concerns that particularly affect marginalised communities through algorithmic bias and digital accessibility barriers. Economic implications vary significantly across regions, with examples ranging from South Korea’s redeployment strategies to the controversial U.S. Department of Government Efficiency reforms under President Trump. Despite these challenges, the chapter identifies opportunities for reimagining public service delivery through role redefinition and new governance positions. It concludes by advocating for a citizen-centric approach emphasising data quality investment, stakeholder engagement, transparency, worker transition support, and continuous evaluation systems to ensure AI automation enhances rather than undermines the social contract between governments and citizens.