Format: Live instructor-led online training via Zoom / Microsoft Teams

AI Governance and Ethics Training Course

Course Introduction

Artificial Intelligence (AI) is revolutionizing industries by enhancing decision-making, automating processes, improving customer experiences, and driving innovation. However, the rapid adoption of AI technologies has introduced significant challenges related to ethics, accountability, transparency, fairness, privacy, security, and regulatory compliance. Organizations worldwide are increasingly recognizing the need for robust AI governance frameworks and ethical guidelines to ensure that AI systems operate responsibly and align with organizational values, legal requirements, and societal expectations. This AI Governance and Ethics Training Course provides participants with comprehensive knowledge and practical skills to establish effective AI governance structures and ethical AI practices.

The course explores key concepts of AI governance, responsible AI, ethical decision-making, algorithmic accountability, risk management, AI compliance, data governance, transparency, explainability, fairness, and stakeholder engagement. Participants will gain a deep understanding of how organizations can balance innovation with ethical responsibility while ensuring that AI systems are trustworthy, secure, inclusive, and aligned with international standards and emerging regulations. The training also examines the ethical implications of machine learning, generative AI, predictive analytics, and automated decision-making systems.

As governments, regulators, and international organizations continue to develop AI policies and regulations, organizations must proactively implement governance mechanisms that reduce risks and promote responsible AI deployment. This course provides practical approaches to developing AI governance frameworks, conducting AI risk assessments, implementing ethical review processes, establishing accountability mechanisms, and ensuring compliance with global AI standards. Participants will learn how to identify potential biases, mitigate unintended consequences, and create governance models that support sustainable and ethical AI innovation.

Through practical exercises, real-world case studies, governance simulations, policy development workshops, and risk assessment activities, participants will acquire the competencies needed to oversee AI initiatives effectively. The course emphasizes organizational readiness, ethical leadership, regulatory compliance, stakeholder trust, AI auditing, performance monitoring, and continuous improvement. By the end of the training, participants will be equipped to lead AI governance initiatives and foster a culture of ethical AI adoption across their organizations.

Course Objectives

By the end of this course, participants will be able to:

1.     Understand the principles and foundations of AI governance and ethics.

2.     Develop AI governance frameworks and organizational policies.

3.     Identify ethical risks associated with AI systems and applications.

4.     Implement accountability, transparency, and explainability mechanisms.

5.     Conduct AI risk assessments and impact evaluations.

6.     Ensure compliance with AI regulations, standards, and best practices.

7.     Address algorithmic bias, fairness, and discrimination issues.

8.     Strengthen privacy, cybersecurity, and data governance practices.

9.     Design monitoring, auditing, and oversight processes for AI systems.

10.  Promote responsible AI innovation and ethical organizational culture.

Organization Benefits

Organizations whose staff attend this training will benefit by:

1.     Strengthening AI governance and oversight capabilities.

2.     Reducing ethical, legal, operational, and reputational risks.

3.     Enhancing stakeholder trust in AI-powered decisions.

4.     Improving regulatory compliance and policy alignment.

5.     Establishing transparent and accountable AI practices.

6.     Enhancing data governance and privacy protection.

7.     Minimizing bias and discrimination in AI applications.

8.     Supporting sustainable and responsible AI innovation.

9.     Improving organizational readiness for AI transformation.

10.  Building competitive advantage through trustworthy AI systems.

Target Participants

·       Chief Executive Officers (CEOs)

·       Chief Information Officers (CIOs)

·       Chief Technology Officers (CTOs)

·       AI Governance Officers

·       Data Scientists and Analysts

·       Machine Learning Engineers

·       Digital Transformation Managers

·       Compliance Officers

·       Risk Management Professionals

·       Internal Auditors

·       Data Protection Officers

·       Legal and Regulatory Professionals

·       IT Managers and Specialists

·       Corporate Governance Professionals

·       Policy Makers

·       Public Sector Officials

·       Researchers and Academics

·       Human Resource Managers

·       Innovation Leaders

·       Project Managers

Course Outline

Module 1: Foundations of AI Governance and Ethics

1.     Introduction to Artificial Intelligence and Emerging Technologies

2.     Principles of AI Governance and Ethical AI

3.     Responsible AI Frameworks and Standards

4.     Trustworthy AI Concepts and Practices

5.     Global Trends in AI Governance

6.     Case Study: Ethical AI Adoption in a Global Organization

Module 2: AI Governance Frameworks and Organizational Structures

1.     Designing AI Governance Models

2.     Governance Roles and Responsibilities

3.     AI Policy Development and Implementation

4.     Decision-Making Structures for AI Oversight

5.     Governance Committees and Accountability Mechanisms

6.     Case Study: Enterprise AI Governance Framework Development

Module 3: AI Ethics and Responsible Innovation

1.     Ethical Principles in AI Development

2.     Human Rights and AI Applications

3.     Ethical Decision-Making Models

4.     Social and Economic Impacts of AI

5.     Responsible Innovation Practices

6.     Case Study: Ethical Challenges in AI-Powered Services

Module 4: AI Risk Management and Impact Assessment

1.     Identifying AI Risks and Vulnerabilities

2.     AI Risk Assessment Methodologies

3.     AI Impact Assessment Frameworks

4.     Managing Operational and Strategic Risks

5.     Mitigation Strategies for AI Risks

6.     Case Study: AI Risk Assessment in Financial Services

Module 5: Fairness, Bias and Accountability in AI

1.     Understanding Algorithmic Bias

2.     Measuring Fairness in AI Systems

3.     Bias Detection and Mitigation Techniques

4.     Accountability and Liability Considerations

5.     Human Oversight and Governance Controls

6.     Case Study: Bias Management in Recruitment Algorithms

Module 6: Transparency, Explainability and Trust

1.     Explainable AI Concepts and Methods

2.     Transparency Requirements for AI Systems

3.     Building Stakeholder Trust in AI

4.     Communicating AI Decisions Effectively

5.     Documentation and Reporting Standards

6.     Case Study: Explainable AI in Healthcare Applications

Module 7: Data Governance and Privacy in AI

1.     Data Governance Principles

2.     Data Quality and Integrity Management

3.     Privacy by Design in AI Systems

4.     Data Protection Regulations and Compliance

5.     Ethical Data Collection and Usage

6.     Case Study: Privacy Compliance in AI Projects

Module 8: AI Security and Cyber Risk Management

1.     AI Security Threat Landscape

2.     Adversarial Attacks on AI Systems

3.     Secure AI Development Practices

4.     Cybersecurity Controls for AI Applications

5.     Incident Response and Recovery Planning

6.     Case Study: Securing AI-Powered Infrastructure

Module 9: Regulatory Compliance and AI Standards

1.     Overview of Global AI Regulations

2.     International AI Governance Standards

3.     Compliance Management Frameworks

4.     Regulatory Reporting Requirements

5.     Auditing for AI Compliance

6.     Case Study: AI Compliance Program Implementation

Module 10: AI Auditing, Monitoring and Evaluation

1.     AI Audit Frameworks and Methodologies

2.     Performance Monitoring and Evaluation

3.     Model Validation and Verification

4.     Detecting Model Drift and Performance Issues

5.     Continuous Governance and Improvement

6.     Case Study: Organizational AI Audit Process

Module 11: Leadership and Organizational Culture for Ethical AI

1.     Leadership Responsibilities in AI Governance

2.     Building Ethical AI Culture

3.     Stakeholder Engagement and Communication

4.     Change Management for AI Adoption

5.     Training and Capacity Building Strategies

6.     Case Study: Organizational Transformation Through Responsible AI

Module 12: Strategic AI Governance and Future Trends

1.     Developing Long-Term AI Governance Strategies

2.     Emerging Technologies and Governance Challenges

3.     Governance of Generative AI Systems

4.     AI Sustainability and Social Responsibility

5.     Future Regulatory and Ethical Considerations

6.     Case Study: Strategic AI Governance Roadmap Development

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.