Course Objective & Scope
When Responsible AI remains a high-level corporate pledge, delivery teams under deadline pressure often cut corners that expose the organisation to reputational and regulatory harm. This course translates globally recognised Responsible AI principles (OECD, UNESCO, EU) into concrete decisions for business and project teams.
Participants explore fairness, transparency, accountability, privacy, robustness and human agency through real corporate failure and success stories. In a workshop tailored to the organisation, teams draft a practical Responsible AI Charter and a project-intake checklist aligned with their industry context.
Who Should Attend?
- Business unit managers sponsoring or deploying AI tools
- Corporate governance, ESG, compliance and corporate communications teams
- Product managers and leaders in HR, marketing and customer experience
- No technical prerequisites; suited to any team building a shared Responsible AI culture
Key Takeaways
- Connect the six core Responsible AI principles to concrete business scenarios
- Spot societal, legal and reputational risks across predictive ML and generative AI use cases
- Define disclosure and transparency requirements for customer- and employee-facing AI
- Balance speed of innovation with responsible guardrails using structured trade-off criteria
- Produce an actionable Responsible AI project checklist tailored to the organisation
Curriculum
Why Responsible AI Matters: Real-World Failures and Business Impact
- Case studies from recruitment, credit scoring, dynamic pricing and customer chatbots
- Reputational damage, regulatory fines and erosion of stakeholder trust
- Common ground across OECD, UNESCO and EU Responsible AI frameworks
The Six Core Principles in Business Terms
- Fairness, transparency, accountability, privacy, safety and human agency
- Disclosure rules when customers or employees interact with AI systems
- Ensuring clear human accountability for automated or AI-assisted outcomes
Responsible Use of Generative AI and Autonomous Agents
- Hallucinations, copyright infringement, synthetic media and overreliance risks
- Bounding agent authority and restricting irreversible autonomous actions
From Principles to Practice Across the Project Lifecycle
- Critical review questions at ideation, procurement, design, testing and launch
- Escalation paths for resolving ethical trade-offs
Workshop: Drafting a Responsible AI Charter and Intake Checklist
- Articulating organisation-specific Responsible AI commitments
- Applying the intake checklist to a live use case from the organisation
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