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AI Governance, Ethics and Responsible Innovation

As organizations adopt AI, they must ensure that systems are used responsibly, ethically and transparently. Poor AI governance can create risks related to privacy, bias, misinformation, accountability and public trust.

This Magna Skills course provides practical guidance on AI governance, responsible innovation, risk management, compliance, ethics and policy development for public and private sector organizations.

Participants will learn how to develop internal AI usage policies, assess risks, protect data, promote fairness and establish accountability structures for responsible AI adoption.

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AI Governance, Ethics and Responsible Innovation
Online fee from
$200 USD
Standard: $300 · Save $100
Course Outcomes

Expected learning outcomes

Course Outcomes

  1. Understand responsible AI principles, including fairness, transparency and accountability.
  2. Identify ethical, legal, operational and reputational risks linked to AI adoption.
  3. Develop practical AI governance structures, policies and acceptable-use guidelines.
  4. Protect institutional, personal and confidential data when using AI tools.
  5. Support responsible innovation while maintaining compliance, public trust and organizational accountability.
Curriculum

Course modules and outline

Course Outline

Module 1: Introduction to AI governance and responsible innovation
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 2: Ethics, fairness, bias and discrimination in AI
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 3: Privacy, data protection and confidentiality
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 4: AI risk management and compliance frameworks
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 5: Human oversight and accountability mechanisms
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 6: AI policies, staff guidelines and acceptable use rules
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 7: Transparency, explainability and documentation
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 8: Managing vendors and third-party AI tools
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 9: Governance for public sector and regulated environments
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Module 10: Developing an AI governance implementation plan
  • Key concepts, practical examples and sector-based discussion.
  • Workplace application activity, templates and implementation considerations.
Target Audience

Who should attend?

Target Audience

Compliance officers, legal officers, risk managers, auditors, ICT managers, policy makers, executives, governance professionals, data protection officers, regulators, public sector officials, internal control teams, HR managers, procurement teams and institutional policy developers.

Why Attend

Key course benefits

Practical capacity building approach
Designed for government, NGOs and public institutions
Real-world African case studies
Certificate of completion
Applicable tools and templates
Interactive facilitation and exercises
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