Curriculum
- 5 Sections
- 32 Lessons
- 1 Day
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- Cyber-Risk in the Age of AI6
- 1.1Shift from traditional IT security to AI-enabled cyber threats
- 1.2Vulnerabilities in ML models, data pipelines, APIs, and IoT systems
- 1.3Real-world cases: Deepfake scams, adversarial attacks, data poisoning, prompt injections
- 1.4Frameworks and standards: NIST CSF, MITRE ATT&CK, Zero Trust Architecture
- 1.5Business impact: cyber incidents on brand, compliance, and financial resilience
- 1.6Case Study: SolarWinds, ChatGPT prompt leak, WannaCry
- AI Ethics & Responsible Innovation6
- 2.1Core ethical pillars: Fairness, Accountability, Transparency, Explainability (FATE)
- 2.2Sources and mitigation of bias in datasets and algorithms
- 2.3Ethical dilemmas: surveillance, discrimination, misinformation, and automated decision-making
- 2.4Global frameworks: OECD AI Principles, UNESCO AI Ethics, IEEE Ethically Aligned Design
- 2.5Building: Ethics-by-Design and establishing AI Ethics Committees
- 2.6Discussion: AI gone wrong scenarios (e.g., COMPAS, Amazon HR algorithm bias)
- Global Regulatory Landscape & Risk Compliance8
- 3.1Overview of key AI and data regulations: EU AI Act – risk-based classification, transparency obligations
- 3.2NIST AI RMF – governance, map-measure-manage framework
- 3.3India’s DPDPA 2023 – data protection and consent management
- 3.4China’s Algorithmic Regulation and US Executive Orders on AI
- 3.5Compliance overlaps and data localization mandates
- 3.6Role of governance, audit readiness, and documentation standards (ISO/IEC 42001, 27001)
- 3.7ESG & sustainability disclosures influencing ethical AI governance
- 3.8Case Study – how global companies adapted to the EU AI Act and GDPR transitions.
- Designing a Cyber-Ethics & Compliance Strategy6
- 4.1Building internal AI governance models — roles, accountability, and escalation
- 4.2Integrating security, privacy, and ethics into AI lifecycle (design → deploy → monitor)
- 4.3Governance tools: AI audit trails, red-teaming, bias testing, risk heatmaps
- 4.4Aligning with corporate policies, third-party vendor risk, and data ethics charters
- 4.5Creating a regulatory response plan for audits or incidents.
- 4.6Exercise: Design a “Responsible AI Playbook” for a hypothetical AI rollout (e.g., in financial services or healthcare)
- Boardroom Alignment & Future Trends6
- 5.1Cyber accountability and board-level governance frameworks.
- 5.2Translating cyber and AI risks into enterprise KPIs and dashboards.
- 5.3Emerging risk frontiers: quantum threats, AI-generated misinformation, liability laws.
- 5.4Governance as a competitive differentiator — trust, transparency, and resilience.
- 5.5Building an enterprise roadmap: Assess → Govern → Monitor → Report.
- 5.6Approach: Reflection, Q&A, and co-creation of leadership action plans.
Building an enterprise roadmap: Assess → Govern → Monitor → Report.
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