Artificial intelligence holds transformative potential across various sectors by enhancing efficiency, consistency, and quality of services. However, realizing this potential is often challenged by concerns about the trustworthiness, fairness, and ethical use of AI systems. This course provides a comprehensive understanding of the ethical considerations and responsibilities associated with the deployment of AI, focusing on the following key areas: Understanding Algorithmic Trustworthiness, Ensuring Fairness in AI Applications, Enhancing Transparency and Explainability, Addressing Cognitive Bias in Human-AI Interaction, Educational Gaps and Their Implications. By the end of this course, participants will be equipped to navigate the ethical challenges of AI, ensuring that their applications are fair, transparent, and responsible, thereby fostering greater trust and equity in the use of AI technologies.

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learning objectives

By the end of this course, learners should be able to:

  • Explain the basic components of the life-cycle of machine learning systems

  • Explain key ethical concepts (e.g. fairness, justice, benevolence) with an inclusive approach

  • Evaluate ethical risks & benefits of using AI in in specific industry settings

  • Apply examples and models of widespread human decision-making biases to their own decisions

  • Weigh the benefits and risks of employing AI recommendation systems in their operative decisions

  • Understand the potential for AI tools to affect human biases in decision making, and to impact on fairness and equality.

  • Use AI to reach more accurate and more ethical decisions in their practice


  • Self-paced

  • 8 learning units

  • 3-5 learning hours

  • Customizable knowledge checks and final assessment

  • LMS and SCORM ready

topics of the course