About the Project
This research project was developed as part of my Persuading Ethical UX Design course at the University of Washington, where I explored frameworks for designing technology that respects human values and prevents harm.
After studying ethical design principles and moral psychology throughout the course, I focused my final project on a critical real-world question: How can we predict and prevent moral outrage when implementing AI in healthcare?
I chose to apply Jonathan Haidt's Six Moral Foundations Theory - a psychological framework that explains why people have strong emotional reactions to ethical violations to anticipate potential PR crises before AI healthcare products launch.
📥 Download my full document here
The Problem & My Research Process
The Problem -
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AI in healthcare risks public backlash when ethical concerns aren't addressed
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Companies struggle to predict what will trigger moral outrage
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Two critical scenarios: AI-generated health content & patient data usage
My Research Process -
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Applied Haidt's Six Moral Foundations Theory to predict user reactions
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Mapped each foundation to AI healthcare scenarios
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Developed ethical UX framework with actionable design guidance
Six Moral Foundations: Risk Analysis
Care/Harm
Patient safety compromised
AI diagnoses need human review; security prevents breaches
❤️
Loyalty/Betrayal
Corporate interests over patients
Balance AI with human expertise; never sell data without consent
🤝
Sanctity/Degradation
Reducing patients to data
Consider emotions in advice; never automate life-death decisions
✨
Fairness/Cheating
Discriminatory decisions
Consistent advice across groups, diverse, audited training data
⚖️
Authority/Subversion
Bypassing regulations
Medical professionals approve content; strict regulatory compliance
👔
Liberty/Oppression
Forced consent patterns
Clear opt-out options; opt-in data sharing only
🗽
Ethical UX Framework: Key Deliverables
Pre-Launch Checklist
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Does feature prioritize patient safety?
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Tested for bias across diverse users?
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Transparent about data practices?
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Medical oversight & regulatory approval?
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Respects patient dignity & emotions?
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Users can opt out easily?
Red Flag Indicators
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No explanation for AI recommendations
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Dark patterns in consent flows
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Unclear accountability for errors
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Data practices hidden in ToS
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Different care quality by income
View Full Document
Reflection & Next Steps
Key Insight: Moral outrage is predictable if we analyze ethical dimensions beforehand. By grounding design decisions in moral psychology, we can create AI systems that feel trustworthy and human-centered from day one.
Limitations: While theory provides predictive power, real-world validation is essential. Recommended next steps include user testing with actual patients, stakeholder interviews with healthcare providers, and cross-cultural analysis of moral foundations.
Keywords: UX Research, Ethical Design, Healthcare UX, AI/ML Ethics, Risk Analysis, Framework Development, Moral Psychology