Overview

As AI becomes increasingly embedded in everyday business operations, using it responsibly is no longer optional - it's a compliance, governance, and reputational imperative. This course introduces the foundations of Responsible AI, exploring how AI systems rely on data quality and the risks that arise from bias, weak oversight, poor governance, and unethical AI practices. Through practical examples and real-world contexts, learners gain awareness of ethical AI principles, transparency, fairness, accountability, and secure data management across the AI lifecycle.

Learning Objectives:

• Explain the core principles of Responsible AI including fairness, transparency, and accountability
• Recognise risks related to bias, fairness, and data quality in AI systems
• Understand the importance of transparency and governance in AI decision-making
• Apply responsible practices when using or interacting with AI technologies at work

Target Audience:

All employees interacting with AI systems, as well as managers, data teams, compliance officers, and anyone involved in procuring, deploying, or governing AI tools within the organisation.

Features & Benefits:

• Covers AI bias, data quality, governance, transparency, and ethical AI lifecycle
• Practical workplace examples grounding abstract principles in real decisions
• Relevant to employees at all levels, not just technical teams
• Built to neurodiverse-friendly design standards
• AI-enhanced visuals, avatars, and voiceovers
• SCORM compliant