A tailored course, built for your situation
Influence across more business lines with NIST AI RMF
A tailored path to extend your UX governance impact using the NIST AI Risk Management Framework
$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.
Who this is for
Senior UX practitioner in a high-velocity AI-driven tech environment who operates as an individual contributor but influences design governance across teams
Who this is not for
Entry-level designers, product managers without UX ownership, or practitioners focused solely on consumer-facing apps without AI integration
What you walk away with
- Articulate UX concerns using NIST AI RMF language that resonates with risk, compliance, and engineering teams
- Shape AI design standards before development begins, not after user testing reveals friction
- Contribute directly to cross-functional AI governance documentation used in audits and reviews
- Lead design input for AI impact assessments aligned with NIST AI RMF core functions
- Position yourself as a go-to voice when new AI tools are evaluated across business units
The 12 modules (with all 144 chapters)
Module 1. UX in the age of AI governance
Ground your design role in the expanding expectations of responsible AI. Understand how NIST AI RMF elevates design as a governance function, not just a styling layer.
12 chapters in this module
- Why design now shapes AI risk posture
- From pixels to policy influence
- The shift from reactive to preventive design
- Designers as first-line governance actors
- How NIST AI RMF changes team dynamics
- Real-world AI failures with UX roots
- Where designers have been excluded before
- The new scope of design ownership
- Balancing innovation and guardrails
- Designing with traceability in mind
- Speaking to compliance without jargon
- Positioning design as risk mitigation
Module 2. Core of NIST AI RMF
Break down the NIST AI RMF structure and map its components to UX decision points. Learn to identify where design inputs are most critical.
12 chapters in this module
- Map of NIST AI RMF functions
- Govern map to design workflows
- Map to user research phases
- Map to accessibility audits
- Govern function explained
- Map to consent patterns
- Map to error handling UX
- Map to model transparency screens
- Map to update notifications
- Map to user feedback loops
- Map to offboarding experiences
- Map to version history design
Module 3. Designing for trustworthy AI
Translate the principle of trustworthy AI into concrete interface patterns. Build designs that inherently support explainability, fairness, and safety.
12 chapters in this module
- Trustworthy AI defined by NIST
- Explainability in user flows
- Designing for model uncertainty
- Fairness signals in interface
- Bias mitigation through UX
- Safety patterns for edge cases
- User control over AI decisions
- Consent with clarity
- Feedback mechanisms that learn
- Transparency without overload
- Version tracking in UI
- Auditability by design
Module 4. Governance participation as a designer
Step into governance conversations with confidence. Learn to contribute meaningfully to AI review boards and cross-functional risk discussions.
12 chapters in this module
- When to speak up in AI reviews
- Preparing for governance meetings
- Documents designers should review
- Asking risk-aware questions
- Providing evidence from user research
- Flagging usability-risk tradeoffs
- Suggesting design mitigations
- Documenting design rationale
- Linking UX to risk controls
- Using NIST language in meetings
- Recommending user testing scope
- Escalating design red flags
Module 5. AI impact assessment inputs
Master how to contribute to AI impact assessments from a UX perspective. Turn usability findings into governance-grade evidence.
12 chapters in this module
- Structure of AI impact reports
- User research as risk data
- Mapping pain points to risk domains
- Documenting bias in testing
- Quantifying confusion rates
- Capturing accessibility gaps
- Reporting edge case behaviors
- Linking UX debt to risk
- Suggesting design controls
- Proposing user feedback layers
- Recommending update cadence
- Signing off on UX sections
Module 6. Design documentation for auditability
Create UX artefacts that survive leadership changes and support compliance. Build a defensible, traceable design process.
12 chapters in this module
- Why auditability matters now
- Design decisions as control evidence
- Version-controlled design files
- Changelog for interface changes
- User research repositories
- Accessibility conformance reports
- Bias testing documentation
- Transparency feature logs
- Feedback loop logs
- Update notification records
- Retention of design rationale
- Archiving deprecated patterns
Module 7. Cross-team influence strategies
Grow your influence beyond design teams. Learn how to align with legal, compliance, and engineering on shared AI governance goals.
12 chapters in this module
- Finding allies in compliance
- Building credibility with engineers
- Partnering with legal on disclosures
- Aligning with product on timelines
- Consulting with security teams
- Engaging with risk officers
- Co-developing playbooks
- Joint review sessions
- Shared documentation standards
- Design-led risk walkthroughs
- Cross-functional feedback loops
- Influence without authority
Module 8. AI transparency patterns
Design interfaces that make AI behavior understandable. Turn model opacity into user trust through intentional patterns.
12 chapters in this module
- Explainability vs transparency
- Model purpose disclosure
- Data source visibility
- Uncertainty indicators
- Confidence level displays
- Decision reasoning snippets
- User override options
- Right to human review
- Model update notifications
- Version change logs
- Feedback to model improvement
- Transparency testing with users
Module 9. Fairness in user experience
Identify and mitigate fairness issues in UX. Turn bias detection into design improvements that strengthen trust.
12 chapters in this module
- Defining fairness in UX
- Bias in personalization
- Language and tone disparities
- Accessibility as fairness
- Cultural assumptions in flows
- Testing across user segments
- Feedback loop fairness
- Error handling equity
- Onboarding inclusivity
- Support access parity
- Reporting bias observations
- Designing for edge users
Module 10. Safety and harm mitigation
Design to prevent user harm from AI. Anticipate misuse, misinterpretation, and edge behaviors in real-world contexts.
12 chapters in this module
- Harm types in AI systems
- User misunderstanding risks
- Misuse scenario planning
- Guardrails in interface
- Error prevention patterns
- Fallback experience design
- Human escalation paths
- Crisis mode UX
- Reporting abuse easily
- Limiting harmful outputs
- Context-aware defaults
- Safety testing protocols
Module 11. Accountability in design
Own the downstream effects of your designs. Build in traceability, versioning, and feedback to support organizational accountability.
12 chapters in this module
- Design ownership defined
- Linking choices to outcomes
- User feedback integration
- Version history in UI
- Change logs for users
- Design rationale documentation
- Post-launch monitoring
- User harm reporting UX
- Design debt tracking
- Audit trail participation
- Lessons from incident reviews
- Continuous improvement loop
Module 12. Scaling responsible design
Turn individual practices into repeatable systems. Enable your approach to spread across teams and product lines.
12 chapters in this module
- Reusable design components
- Pattern libraries with guardrails
- Governance checkpoints in design
- Onboarding new designers
- Cross-product alignment
- Centralized design reviews
- Automated design linting
- Design system governance
- Shared tooling for compliance
- Metrics for responsible UX
- Scaling through documentation
- Mentoring for governance
How this maps to your situation
- When joining an AI governance review meeting
- Before signing off on a new AI feature
- During the design phase of a regulated product
- When documenting design decisions for audit
Before vs. after
Before
Design decisions made in isolation from risk and compliance functions, with limited input into AI governance frameworks
After
Consistent influence across business lines, with UX integrated into AI governance documentation and cross-functional decision-making
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 3-4 hours per module, designed to be completed at your pace over 4-6 weeks
How this compares to the alternatives
Unlike generic AI ethics courses, this program focuses on actionable UX integration points within the NIST AI RMF, giving you specific language and artefacts to increase your sphere of influence.
Frequently asked
Is this course technical?
No. It’s designed for UX practitioners who need to engage confidently in AI governance discussions without becoming data scientists or engineers.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me work with compliance teams?
Yes. You’ll learn to speak their language and contribute directly to governance artefacts using NIST AI RMF terminology.
$199 one-time. Approximately 3-4 hours per module, designed to be completed at your pace over 4-6 weeks.
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