Course Objective & Scope
Users either over-trust an AI feature—rubber-stamping flawed outputs without checking—or lose faith in the entire product after a single visible mistake. This course covers product and UX patterns that calibrate user trust to actual model reliability while keeping humans firmly in control.
Participants work on their own products to design trust cues, review-and-edit workflows, one-click undo, transparent memory/privacy controls and escalation paths, delivering a complete failure/fallback/escalation UX plan.
Who Should Attend?
- Product managers and UX/UI designers building AI products
- Customer trust, privacy and Responsible AI teams
- Enterprise software and SaaS product leaders
- No technical prerequisites
Key Takeaways
- Set accurate mental models of capability and limitations during user onboarding
- Differentiate high-confidence and low-confidence outputs through clear visual hierarchy
- Design review–edit–approve flows, version history and effortless undo mechanisms
- Give users transparent visibility and control over what data is used in context and memory
- Design smooth escalation paths to human specialists when the model is uncertain or blocked
Curriculum
Calibrating Trust: Avoiding Over-Reliance and Abandonment
- Automation bias versus algorithm aversion in daily product use
- Setting accurate mental models through onboarding and microcopy
Communicating Uncertainty and Lowering Verification Cost
- Why raw probability percentages mislead users and how to design actionable cues
- Highlighting low-confidence spans so users know exactly what to verify
User Control: Drafting, Constraining and Undoing
- Draft-first defaults, staged commits and full version history
- Letting users pin sources, lock sections and constrain model edits
Data Transparency and Memory Controls
- Addressing 'Is my data training the model?' concerns directly in the UI
- Allowing users to inspect, edit and wipe stored preferences and agent memory
Failure, Fallback and Escalation UX Plan
- Constructive recovery paths when the model refuses, times out or fails
- Mapping a complete failure / fallback / escalation UX plan for your product
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