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This intensive two-day course provides participants with a comprehensive, multidisciplinary insight into data ethics, algorithmic accountability, and advanced AI governance. Going beyond just compliance, it connects critical theory, governance structures, and technical fairness techniques to support responsible design, evaluation, and deployment of data-driven systems within complex organisations and societies. Through a mix of theoretical discussions, hands-on exercises, quantitative assessments, and real-world case studies, attendees will build skills to identify ethical risks, implement governance strategies, and make well-informed decisions in influential data environments.
Learning Outcomes:
Analyse data and AI systems using ethical principles such as transparency, fairness, accountability, and power asymmetries
Evaluate and extend data governance practices beyond legal compliance
Assess and manage ethical, privacy, and security risks in both routine and crisis‑driven data environments
Design and justify robust AI governance strategies by conducting algorithmic audits, ensuring traceability and reproducibility, and making informed go/no‑go decisions for high‑stakes or potentially harmful data‑driven use cases.
Module 1: Critical Data Studies
Module 2: Beyond Legal Compliance
Module 3: Governance in Crisis
Module 4: Operationalising Ethics
Module 5: Algorithmic Fairness Metrics Algorithmic Fairness Metrics
Module 6: High- Stakes Governance
Module 7: Ops Management & Auditability
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