Competency
Ethics and Responsibility in AI
Examine the ethical foundations, societal responsibilities, and governance strategies essential to trustworthy AI development. This competency guides learners through the principles of ethical design, mitigation of bias and discrimination, explainability, and transparency in AI systems.
5 Trainers
Course Overview
This competency focuses on the ethical foundations and societal responsibilities in the development and deployment of artificial intelligence. It explores core ethical principles, the impact of bias and discrimination in AI models, and the significance of explainability and transparency. The course also covers how to design responsible AI frameworks, implement governance structures, and mitigate risks associated with AI systems.
About
What You'll Learn:
The ethical principles behind AI development and governance
How to identify and mitigate bias and discrimination in AI models
Techniques for improving explainability and transparency in AI systems
How to build responsible AI frameworks and governance structures
Strategies for addressing the societal and legal implications of AI technologies
Who Should Take This Course?
This course is perfect for:
AI and Machine Learning Developers looking to understand the ethical implications of their work and build more responsible AI systems
Data Scientists and Engineers who want to learn how to identify and mitigate bias in AI models
Compliance and Risk Management Professionals focused on ensuring ethical standards and legal compliance in AI applications
Ethics Consultants and Auditors who work with organizations to evaluate the fairness and transparency of AI systems
AI Product Managers and Designers aiming to implement transparent, accountable, and ethical practices in AI system development
Researchers and Academics exploring the ethical dimensions of AI and its societal impact
Corporate Leaders and Decision Makers responsible for overseeing AI initiatives and ensuring ethical governance and risk management within their organizations
What You'll Get:
Certification upon completion
A comprehensive understanding of the ethical principles guiding AI development and governance
Practical knowledge on how to identify and mitigate bias and discrimination in AI systems
Tools and techniques for improving explainability and transparency in AI models
An understanding of how to build responsible AI frameworks and governance structures
Insights into the societal, legal, and moral implications of AI technologies
Strategies for incorporating ethical AI practices into development processes
Module 1
Principles of Ethical AI
Foundations (16 mins)
Historical Evolution of AI (12 mins)
Core Ethical Principles (16 mins)
Global Standards and Trends (15 mins)
Take the Practice Quiz
Module 2
Bias and Discrimination in AI Models
Data and Model Bias (11 mins)
The Dynamics of Discrimination (13 mins)
Impact Assessment (12 mins)
Mitigating Risks (10 mins)
Take the Practice Quiz
Module 3
Explainability and Transparency in AI
Understanding Explainability (12 mins)
Transparency Mechanisms (12 mins)
Tools and Techniques (13 mins)
Challenges and Opportunities (14 mins)
Take the Practice Quiz
Module 4
Building Responsible AI Frameworks
Introduction to Framework Design (13 mins)
Governance Structures (12 mins)
Operational Guidance (11 mins)
Future Perspectives (10 mins)
Take the Practice Quiz
About the Trainer
Alex Carroll
GDPR and Privacy Consulting Manager
Alex Carroll is a specialist in GDPR compliance and privacy-by-design strategies for tech product teams. Drawing on a strong background in learning, knowledge transfer, and quality management, Alex helps developers and product owners build GDPR-compliant solutions autonomously—without constant reliance on legal teams. He supports organizations across sectors like Fintech, Healthtech, retail, and social impact to integrate compliance into development processes and use it as a market differentiator. Through targeted training and practical guidance, Alex enables teams to meet regulatory expectations while accelerating secure, compliant product delivery.
