Ethical and Security Implications of Generative AI in E-Government: A Study of Data Protection, Model Security and Responsible AI

The integration of generative AI in e-government platforms offers transformative benefits, including improved efficiency and citizen engagement. Generative Artificial Intelligence (AI) models such as Large Language Models (LLMs) and Generative Adversarial Networks (GANs) hold transformative potential in e-government by enhancing service delivery, automating administrative tasks, and improving citizen engagement. However, their deployment raises pressing ethical, security, and governance challenges, including data privacy violations, algorithmic bias, and adversarial vulnerabilities. This study explores the responsible integration of generative AI in the UK public sector through a mixed-methods approach. It combines practical case studies with primary data from a structured questionnaire distributed to stakeholders in public administration and technology. In addition, test code and simulated scenarios were developed to evaluate how generative AI systems could function within public service contexts. These simulations illustrate how generative AI could be used in administrative workflows while surfacing vulnerabilities such as adversarial manipulation, data leakage, and bias propagation. Findings reveal that while frameworks such as General Data Protection Regulation (GDPR) and the UK, National AI Strategy offer baseline guidance, however, they do not address the model-specific risks associated with generative AI technologies. The paper proposes a comprehensive governance framework that integrates AI ethics, data protection standards, and public administration principles. This model aims to guide policymakers and practitioners in deploying AI systems that are fair, secure, and transparent. By combining theoretical simulations, stakeholder perspectives, and regulatory analysis, this paper contributes to the discourse on trustworthy AI in public services. It advocates for context-specific governance mechanisms to ensure generative AI technologies are deployed responsibly, maintaining public trust and reinforcing the integrity of digital government initiatives.