A tailored course, built for your situation
Faster path from AI ethics intent to working governance artefact using OECD AI Principles
Turn principles into production-grade policy outputs in days, not months
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Stuck translating AI ethics principles into real policy?
Who this is for
Senior AI/ML data science practitioner embedded in a cloud-scale data platform, responsible for shaping governance without formal authority.
Who this is not for
Individuals looking for introductory AI ethics overview or theoretical frameworks without implementation guidance.
What you walk away with
- First internal team to produce a working Statement of Applicability (SoA) mapped to OECD AI Principles
- Complete policy draft from intent to stakeholder review in under 10 days
- Reusable templates for AI risk registers, control summaries, and compliance narratives
- Faster alignment cycles with legal, risk, and engineering stakeholders
- Clear mapping from ethical principle to technical control in production systems
The 12 modules (with all 144 chapters)
Module 1. Defining AI governance scope using OECD principles
Map the five OECD AI Principles to specific domains within AI/ML workflows, understand where they apply and where they don’t.
12 chapters in this module
- Purpose of AI governance
- Human-centered values
- Fairness and non-discrimination
- Explainability scope
- Robustness and reliability
- Accountability mechanisms
- Public trust dimensions
- Risk tolerance by use case
- Sector-specific constraints
- Geographic application
- Private vs public sector implications
- Mapping to technical ownership
Module 2. From principle to first-draft policy
Build the first version of a compliant AI policy in under 48 hours using structured extraction from the OECD framework.
12 chapters in this module
- Identifying key clauses
- Clause prioritization matrix
- Stakeholder input triggers
- Policy ownership assignment
- Tone and audience calibration
- Version control setup
- Feedback loop design
- Risk tiering logic
- Approval workflow mapping
- Integration with data governance
- Linking to AI incident response
- Publishing standards
Module 3. Building the Statement of Applicability
Create the first internal SoA that aligns with OECD principles, tailored to AI/ML systems in production.
12 chapters in this module
- What is an SoA
- Structure of a working SoA
- Applicability rationale
- Exclusion justification
- Control mapping logic
- Evidence requirements
- Versioning approach
- Cross-system consistency
- Integration with audit
- Stakeholder sign-off path
- Living document maintenance
- SoA review cadence
Module 4. AI risk register design and deployment
Design a risk register that operationalizes OECD principles into measurable AI risks.
12 chapters in this module
- Risk taxonomy structure
- Inherent vs residual risk
- Likelihood calibration
- Impact scoring method
- Risk owner assignment
- Mitigation tracking
- Automated monitoring integration
- Incident linkage
- Third-party vendor risk
- Model lifecycle exposure
- Drift and degradation flags
- Quarterly review process
Module 5. Control implementation tracking
Map abstract OECD principles to concrete technical controls in ML pipelines.
12 chapters in this module
- Data provenance enforcement
- Bias detection integration
- Model explainability standards
- Human oversight thresholds
- Fail-safe mechanisms
- Version rollback readiness
- Access control alignment
- Logging completeness
- Monitoring coverage
- Incident response linkage
- Audit trail durability
- Control ownership matrix
Module 6. Stakeholder alignment workflows
Secure faster sign-off from legal, risk, and engineering teams using OECD-aligned artefacts.
12 chapters in this module
- Identifying decision makers
- Tailoring communication style
- Feedback collection mechanism
- Conflict resolution paths
- Simplification without dilution
- Executive summary design
- Legal review integration
- Risk committee engagement
- Engineering adoption incentives
- Cross-functional templates
- Escalation protocols
- Change impact assessment
Module 7. Accelerating review cycles
Cut policy review time in half using structured templates and pre-emptive validation.
12 chapters in this module
- Pre-submission checklist
- Common objection catalogue
- Version comparison tools
- Change rationale documentation
- Review timeline benchmarks
- Parallel review design
- Automated gap detection
- Reviewer assignment logic
- Feedback aggregation
- Consensus tracking
- Version approval rules
- Post-review audit trail
Module 8. Reusable artefact design
Build templates that compound across AI governance projects and reduce future effort.
12 chapters in this module
- Template modularity
- Version inheritance
- Contextual adaptation rules
- Automated field population
- Cross-project reuse
- Ownership documentation
- Change tracking integration
- Approval inheritance
- Metadata tagging
- Searchability optimization
- Archive strategy
- Template retirement
Module 9. Evidence collection workflow
Establish a repeatable process for collecting and presenting compliance evidence.
12 chapters in this module
- Evidence typology
- Collection frequency
- Storage location mapping
- Access control rules
- Chain of custody
- Timestamp standards
- Automated capture
- Manual submission design
- Validation checks
- Audit readiness checklist
- Retention rules
- Evidence versioning
Module 10. Compliance narrative construction
Build compelling, accurate stories for auditors and regulators using OECD principles.
12 chapters in this module
- Narrative structure
- Timeline creation
- Stakeholder roles
- Incident linkage
- Control effectiveness claims
- Risk acceptance justification
- Improvement roadmap
- Lessons learned
- Evidence citation
- Tone calibration
- Clarity vs completeness
- Narrative versioning
Module 11. Governance automation foundations
Lay the groundwork for automated compliance checks based on OECD principles.
12 chapters in this module
- Policy as code design
- Automated control testing
- Model drift alerts
- Access violation detection
- Logging completeness check
- Bias monitoring automation
- Explainability threshold alerts
- Version rollback verification
- Incident reporting automation
- Third-party audit integration
- Dashboard creation
- Alert triage workflow
Module 12. Scaling governance across teams
Extend OECD-based governance practices to other AI/ML teams without slowing innovation.
12 chapters in this module
- Onboarding process
- Training material creation
- Internal certification
- Peer review design
- Mentorship model
- Cross-team consistency
- Innovation protection
- Feedback loop integration
- Governance debt tracking
- Performance metric alignment
- Resource allocation
- Maturity assessment
How this maps to your situation
- When first drafting AI policy
- During stakeholder review phase
- Before audit preparation
- After incident response
Before vs. after
Before
AI governance efforts take months to move from principle to artefact, with repeated review cycles and stakeholder misalignment.
After
Produce complete, stakeholder-approved governance outputs in days, using reusable templates grounded in OECD AI Principles.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed for completion in 6-8 weeks with flexible pacing.
If nothing changes
Continuing with manual, ad-hoc AI governance slows innovation, increases audit risk, and reduces trust in AI systems.
How this compares to the alternatives
Unlike generic AI ethics courses, this program focuses specifically on accelerating the creation of auditable governance artefacts using the OECD AI Principles, providing actionable templates and real-world implementation logic.
Frequently asked
Is this course technical or policy-focused?
It bridges both, designed for technical practitioners shaping governance policy, with concrete mappings to code, controls, and compliance.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I use this if my organization hasn’t adopted OECD AI Principles?
Yes, the framework is widely recognized and provides a strong foundation even if not formally adopted; the implementation logic transfers.
$199 one-time. Approximately 3 hours per module, designed for completion in 6-8 weeks with flexible pacing..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours