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Course Outline

AI Regulation in the Public Sector: An Introduction

  • The significance of AI policy for governmental bodies
  • A survey of AI applications and associated regulatory obstacles
  • The function of legal and compliance teams in supervising AI

The EU AI Act and GDPR

  • Framework and classifications within the EU AI Act
  • High-risk AI systems and their application in the public sector
  • Principles of AI transparency, human supervision, and accountability
  • Intersection with GDPR: consent, data minimization, and rights of data subjects

The North American AI Regulatory Environment

  • Canada’s AI and Data Act (AIDA)
  • U.S. Executive Order on Safe, Secure, and Trustworthy AI (2023)
  • State-level rules and industry-specific directives (e.g., healthcare, education)
  • Relevance to federal, provincial, and local government agencies

Ethical and Legal Risk Factors

  • Issues of bias, discrimination, and algorithmic explainability
  • Legal responsibility in algorithmic decision processes
  • Maintaining public trust and human-in-the-loop protections

AI Governance Structures and Supervisory Models

  • The NIST AI Risk Management Framework
  • OECD AI Principles and UNESCO recommendations
  • Creating internal policies and audit procedures

Strategies for Policy Formulation and Execution

  • Drafting responsible AI policies for public entities
  • Inter-departmental cooperation and alignment with procurement processes
  • Training initiatives, communication strategies, and compliance tracking

Conclusion and Recommended Next Steps

Requirements

  • A foundational grasp of legal and compliance structures in the public sector
  • A basic awareness of data protection laws, such as GDPR, is advantageous
  • No prior technical knowledge of AI is necessary

Target Audience

  • Legal counsel within public institutions
  • Compliance specialists and regulatory affairs staff
  • Government personnel engaged in AI procurement or risk assessment
 7 Hours

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