Case Study # 1 - Trust-Centered AI Decision Support

KEY POINTS

Challenge: How do you design AI that operators trust with mission-critical decisions?
Design Thinking Focus: Empathize + Test phases
Key Insight: "Trust isn't built through perfect AI—it's built through transparent AI"

While I can’t share specifics from current client work due to NDAs,
I can demonstrate my approach through these conceptual frameworks.
Each represents real challenges I encounter in government AI automation—
and how human-centered design thinking solves them.

 
 

AI Recommendation Flow

Step-by-step progression from data input to action confirmation with transparency

FLOW PRINCIPLES:

• Transparency—Show what AI is doing during processing
• Confidence Scoring—Always display AI confidence levels
• Human Choice—Multiple action options at each step

why this matters:

Government operations require high trust and accountability. This flow ensures users understand AI reasoning and maintain control over critical decisions.

AI Decision Support Dashboard

Clean interface prioritizing human decision points with transparent
AI Insights

design decisions:

• AI Confidence Display—Prominently shows AI confidence level to build trust and inform human decisions
• Human Override —Always accessible override button maintains human agency and control
• Visual Hierarchy —Critical actions and AI insights are prioritized in the interface layout

key principles:

  • Clear AI confidence indicators

  • Immediate human override access

  • Status-first information hierarchy

  • Government-appropriate aesthetics

Error & Uncertainty Handling

Graceful degradation when AI confidence drops or systems fail

graceful degradation:

• Clear Communication—Explain why AI is uncertain or failing
• Alternative Paths —Always provide manual overrides and escalation
• Audit Trail —Log all decisions for compliance

Government requirements:

Government systems must continue operating even when AI fails. These wire-frames show how the interface maintains functionality and preserves decision accountability.

design lessons:

  • Never hide system limitations

  • Provide clear escalation paths

  • Maintain human agency at all times

  • Design for failure scenarios

case study #2
 

Living My Methodology: True to my approach of AI-human collaboration, this entire website was created as a partnership between human insight and AI capability. My ideas, experiences, and professional insights are entirely my own, but I collaborated with Claude AI to structure and refine my thinking, used Figma Make to rapidly prototype design concepts, and leveraged Midjourney for visual storytelling. This demonstrates the transparency and human-AI partnership I advocate for in all my work.