Introduction

The transformative power of Artificial Intelligence (AI) is undeniable, promising breakthroughs across every sector. Yet, its rapid evolution brings forth complex ethical dilemmas and societal challenges, demanding a proactive and responsible approach to its development and deployment. Concerns around algorithmic bias, data privacy, transparency, accountability, and the potential for unintended consequences underscore the critical need for robust Ethical AI Development and Deployment Governance. This essential training course focuses on Ethical AI Development and Deployment Governance, equipping professionals with the critical knowledge and practical methodologies to embed ethical principles throughout the entire AI lifecycle, from conceptualization and design to implementation, monitoring, and eventual decommissioning. You will learn to navigate the intricate landscape of AI ethics, ensuring that your organization's AI initiatives are not only innovative and efficient but also fair, trustworthy, and aligned with human values and regulatory expectations.

This intensive training course delves into the core principles of ethical AI, including fairness, transparency, accountability, privacy, and human oversight. We will explore various AI governance frameworks and best practices from leading global organizations, examining how to establish clear policies, conduct AI ethics risk assessments, implement bias mitigation strategies, and ensure regulatory compliance with emerging AI regulations (e.g., the EU AI Act). Participants will gain hands-on experience in evaluating AI systems for ethical compliance, identifying potential harms, developing responsible AI development practices, and preparing comprehensive governance reports that demonstrate a commitment to ethical AI. By the end of this training course, you will possess the expertise to confidently lead Ethical AI Development and Deployment Governance initiatives, fostering responsible innovation and building public trust in your organization's AI capabilities.

Target Audience

• AI Ethics Officers & Specialists
• Data Scientists & AI Engineers
• Compliance Officers
• Legal & Regulatory Affairs Professionals
• Risk Management Professionals
• Product Managers (AI/ML)
• Senior Leadership & Executives overseeing AI initiatives
• Internal & External Auditors

Course Objectives

• Understand the fundamental concepts of Ethical AI and its societal impact.
• Learn about the core principles of responsible AI development and deployment.
• Master methodologies for identifying and mitigating algorithmic bias in AI systems.
• Develop skills in ensuring data privacy and security for AI-driven applications.
• Understand the importance of transparency and explainability (XAI) in AI decision-making.
• Learn about techniques for establishing accountability and human oversight in AI systems.
• Explore best practices for conducting AI ethics risk assessments.
• Master techniques for developing and implementing AI governance frameworks.
• Understand the requirements of emerging AI regulations (e.g., EU AI Act, NIST AI RMF).
• Learn about strategies for fostering an ethical AI culture within an organization.
• Apply practical Ethical AI Development and Deployment Governance strategies to real-world scenarios.

Duration

5 Days

Course Content

Module 1: Foundations of Ethical AI

• Defining ethical AI and its critical importance.
• Exploring the core principles: fairness, accountability, transparency, privacy, safety.
• Understanding the societal implications of AI development.
• Overview of common ethical dilemmas in AI applications.
• The business case for responsible AI.

Module 2: Algorithmic Bias and Fairness Module

• Learning about the sources and types of algorithmic bias in AI systems.
• Mastering methodologies for identifying and measuring bias in data and models.
• Understanding techniques for mitigating bias (e.g., data balancing, debiasing algorithms).
• Exploring fairness metrics and their application.
• Ensuring equitable outcomes in AI deployment.

Module 3: Transparency, Explainability (XAI) & Interpretability Module

• Understanding the concepts of AI transparency and explainability (XAI).
• Learning about techniques for making "black box" AI models more interpretable.
• Mastering methodologies for generating model explanations (e.g., LIME, SHAP).
• Exploring the trade-offs between interpretability and model performance.
• Communicating AI decisions clearly and understandably.

Module 4: Data Privacy, Security & Human Rights Module

• Understanding the intersection of AI and data privacy regulations (e.g., GDPR, CCPA).
• Learning about privacy-preserving AI techniques (e.g., federated learning, differential privacy).
• Mastering methodologies for ensuring data security throughout the AI lifecycle.
• Exploring the impact of AI on fundamental human rights.
• Ethical considerations in AI data collection and usage.

Module 5: AI Governance Frameworks and Policies Module

• Understanding the components of a comprehensive AI governance framework.
• Learning about global AI governance models (e.g., NIST AI RMF, ISO 42001, EU AI Act).
• Mastering techniques for developing internal AI ethics policies and guidelines.
• Establishing roles, responsibilities, and oversight mechanisms for ethical AI.
• Integrating AI governance into existing GRC structures.

Module 6: Ethical AI Risk Assessment and Management Module

• Strategies for identifying and assessing AI ethics risks (e.g., reputational, legal, operational).
• Mastering techniques for conducting AI impact assessments (AIA) and ethics reviews.
• Developing mitigation strategies for identified AI risks.
• Understanding the concept of "acceptable risk" in AI deployment.
• Building resilience against AI-related incidents.

Module 7: Auditing Ethical AI Compliance & Continuous Improvement Module

• Learning how to conduct an ethical AI compliance audit.
• Mastering techniques for auditing AI systems for fairness, transparency, and accountability.
• Exploring methodologies for independent AI audits and certifications.
• Developing a process for continuous monitoring and evaluation of ethical AI performance.
• Fostering a culture of responsible AI innovation and ethical awareness.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.