Ethics in AI e-Learning

Ethics in AI e-Learning

This interactive, tutor-led online training course is designed to explore the critical ethical considerations surrounding Artificial Intelligence (AI) in today’s rapidly evolving technology landscape.

Participants will gain a foundational understanding of AI ethics, delve into real-world cases, and develop practical strategies to identify and mitigate ethical risks in AI systems.

Through discussions, hands-on activities, and collaborative learning, this course equips professionals with the tools to ensure ethical AI development and deployment.

Key Benefits

  • Foundational Understanding – Learn the key principles of AI ethics, including fairness, accountability, transparency, privacy, and safety, and how they impact society and technology. 
  • Real-World Relevance – Explore practical applications of ethical principles and the consequences of unethical AI use through case studies.
  • Hands-On Learning – Gain experience detecting and mitigating bias in AI models through an interactive mini-demo.
  • Regulatory Insights – Understand the role of major AI regulations (e.g., GDPR, EU AI Act) and governance processes in shaping ethical AI.
  • Collaborative Problem-Solving – Engage in group activities, including ethical risk assessments, to apply your knowledge in realistic scenarios.

Who should complete this course

This course is ideal for professionals working in technology, data science, compliance, or policy making roles who are involved in the development, deployment, or oversight of AI systems. It is also valuable for educators, business leaders, and anyone interested in understanding and promoting ethical AI practices in their organisation or community.

Course syllabus

1. Introduction to AI Ethics

  • Definition and importance of AI ethics (ethics vs. compliance vs. morals).
  • The societal impact of AI and the need for public trust.
  • Overview of key ethical challenges: bias, transparency, privacy, and accountability.
  • Activities: Icebreaker introductions and agenda walkthrough.

2. Core Ethical Principles & Frameworks

  • Fairness, accountability, transparency, privacy, and safety in AI.
  • Introduction to AI ethics frameworks (IEEE, UNESCO, EU Commission).
  • Activities: Knowledge check via quiz and visual examples.

3. Real-World Cases & Impacts

  • Examples of biased AI systems and their societal consequences.
  • The role of public opinion, media, and regulation in ethical AI use.
  • Activities: Case study on a biased loan application AI, with group discussions on mitigation strategies.

4. Mitigating Bias & Hands-On Mini-Demo

  • Techniques for detecting and addressing bias in training data and models.
  • Demonstration of bias checks and mitigation techniques using a Jupyter notebook.
  • Activities: Practical walk through of model fairness and rebalancing methods.

5. Regulatory Landscape & Governance

  • Overview of key AI regulations (GDPR, EU AI Act proposals, U.S. guidelines).
  • Internal governance processes: ethics committees, audits, and crossfunctional teams.
  • Activities: Group reflection on governance gaps and scenario-based discussions.

6. Breakout Activity: Ethical Risk Assessment

  • Structured approach to identifying and mitigating ethical risks.
  • Stakeholder analysis and mitigation strategy development.
  • Activities: Group exercise on assessing risks in a public school AI system.

7. Quiz & Reflection

  • Recap of ethical principles, real-world cases, and mitigation strategies.
  • Personal reflection on lessons learned.

Course duration

  • This virtual class will be conducted on Zoom.
  • 2 hours.

System requirements

  • An internet connection – broadband wired or wireless (3G or 4G/LTE)
  • Speakers and a microphone – built-in, USB plug-in, or wireless Bluetooth
  • A webcam or HD webcam – built-in, USB plug-in, or:
  • An HD cam or HD camcorder with a video-capture card
  • Virtual camera software for use with broadcasting software like OBS or IP cameras

Note: On Windows devices, Zoom utilizes WebView2 and Chromium Embedded Framework
(CEF) for certain features. If not available, these are downloaded automatically by Zoom, but
admins should ensure these are whitelisted on managed devices.

Course costs

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