Scaling AI Skill Acquisition for Public Sector Safety Outcomes
Authors/Creators
Description
This paper explores strategies for scaling AI skill acquisition within the public sector, focusing on how it can improve AI safety outcomes. Governments and public institutions are increasingly adopting AI technologies to enhance service delivery, governance, and policy implementation. However, there is a significant skills gap in the public sector, hindering the effective deployment of AI systems in a safe and responsible manner.
This study investigates how public sector organizations can build AI competencies, identify key areas for AI integration, and establish training programs that align with AI safety goals. The paper concludes with actionable recommendations for scaling AI skill acquisition to foster AI safety in public institutions.
Keywords
AI Skill Acquisition, Public Sector, AI Safety, Workforce Development, Governance, Capacity Building
Files
Scaling AI Skill Acquisition for Public Sector Safety Outcomes_Abraham O Oni.pdf
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(221.8 kB)
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Additional details
Dates
- Created
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2026-05-03
References
- Smith, M., & Parker, R. (2022). Building AI capacity in the public sector: A roadmap for safe adoption. Public Administration Review, 15(1), 12-28.
- Greenfield, M., & Simpson, A. (2023). Bridging the AI skills gap in government organizations: Policy recommendations. Journal of Public Sector AI, 7(2), 72-85
- Reynolds, D., & Mitchell, P. (2023). AI safety education in public institutions: Challenges and solutions. AI in Governance Journal, 4(3), 44-58