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AI+ Policy Maker Practitioner™

Course code: NPAP1001

Formerly known as AI+ Policy Maker™

Empower Your Leadership with AI: Master Policy Development and Implementation for the Future

  • AI-Driven Policy Design: Harness AI to reimagine policy development and enhance the efficiency of decision-making processes
  • Ethical Policy Making: Promote fairness and transparency by embedding AI within responsible and accountable policy frameworks
  • Impact-Centric Frameworks: Develop AI-informed policies that deliver measurable outcomes and strengthen governance effectiveness
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI in Governance and Public Policy

Gain insights into how AI can enhance governance, service delivery, and policy-making. Learn from case studies on AI in sectors like healthcare, education, and transportation.

Ethical, Social, and Human Rights Implications of AI

Understand the ethical considerations surrounding AI, including fairness, transparency, and accountability. Develop strategies to mitigate bias and protect human rights in AI systems.

Legal and Regulatory Frameworks for AI

Dive deep into global AI regulations, data privacy laws, and intellectual property considerations. Master the nuances of developing policies that ensure legal compliance and ethical AI deployment.

AI Strategy and Implementation

Learn to craft AI strategies at the national level, integrating AI with public sector policies, aligning stakeholders, and addressing economic inequalities through AI solutions.

Course structure

Module 1: Introduction to Artificial Intelligence

  • 1.1 Understanding AI: Definitions and Concepts
  • 1.2 Historical Development of AI
  • 1.3 Current AI Technologies and Applications
  • 1.4 AI Trends and Future Directions
  • 1.5 AI Terminology and Jargon for Policy Makers

Module 2: AI in Governance and Public Policy

  • 2.1 Role of AI in Government and Public Services
  • 2.2 Case Studies of AI in Public Administration
  • 2.3 AI for Regulatory Compliance and Enforcement
  • 2.4 Challenges of AI Adoption in Government
  • 2.5 Policy Considerations for AI Implementation

Module 3: Ethical, Social, and Human Rights Implications of AI

  • 3.1 Principles of AI Ethics
  • 3.2 Bias, Fairness, and Discrimination in AI Systems
  • 3.3 Privacy and Data Protection
  • 3.4 Socio-Economic Impacts of AI
  • 3.5 AI and Human Rights

Module 4: Legal and Regulatory Frameworks for AI

  • 4.1 Overview of AI Regulations Globally
  • 4.2 Data Governance and Privacy Laws
  • 4.3 Intellectual Property Rights in AI
  • 4.4 Liability and Accountability in AI Systems
  • 4.5 Developing AI Policies and Legislation

Module 5: AI Risk Management and Security

  • 5.1 AI Safety and Security Challenges
  • 5.2 Risk Assessment and Management Strategies
  • 5.3 Cybersecurity and AI
  • 5.4 Ensuring Reliability and Resilience
  • 5.5 Incident Response and Crisis Management

Module 6: Economic Impacts of AI

  • 6.1 AI and the Future of Work
  • 6.2 AI’s Role in Economic Growth
  • 6.3 Supporting AI Innovation and Entrepreneurship
  • 6.4 AI in Developing Economies
  • 6.5 Addressing Economic Inequalities

Module 7: AI Strategy, Implementation, and Collaboration

  • 7.1 Developing National AI Strategies
  • 7.2 Building AI Capabilities in the Public Sector
  • 7.3 Public-Private Partnerships in AI
  • 7.4 Funding and Investment in AI
  • 7.5 Monitoring, Evaluation, and Continuous Improvement

Module 8: Shaping the Future of AI Policy

  • 8.1 Emerging AI Technologies and Trends
  • 8.2 International Cooperation on AI Governance
  • 8.3 AI and the Sustainable Development Goals (SDGs)
  • 8.4 Public Engagement and Transparency
  • 8.5 The Future of AI Policy Making

Optional Module: AI Agents for Policy Maker

  • 1. Understanding AI Agents
  • 2. Case Study
  • 3. Hands-On Activity

Prerequisites

  • A foundational understanding of AI concepts, including machine learning and data science essentials
  • Familiarity with policy development processes and the structures of governance systems
  • Awareness of data privacy principles and the ethical considerations surrounding AI and technology adoption
  • The ability to interpret data-driven insights, which are integral to formulating effective AI-informed policies

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