Quin

Role: UX Design, UX Research

Duration: 8 weeks

Tools: Figma

Platform: Mobile IOS App & Responsive Web

A Blockchain-Backed Photo Verification Platform for Journalistic Integrity

Misinformation spreads faster than facts—especially when weaponized through images. QUIN is a cross-platform system that empowers journalists to source authentic, tamper-proof visuals at speed.

I led the user research and UX design for this project, done on a team of two designers during the Master’s program at California College of the Arts.

The Problem

The Crisis in Visual Credibility: In the race to break news, journalists often rely on user-generated content. But current verification methods, such as reverse image searches, metadata inspection, are slow, manual, and prone to failure.

Discovery & Research

To understand this global challenge, we interviewed journalists and media professionals.

Key Insights:

  1. Speed vs. Trust Trade-off: Verification slows reporting

  2. No Source Trail: Images spread without provenance

  3. Lack of Standardization: Verification varies wildly across outlets

  4. Reader Fatigue: Low public trust in what they see

The Opportunity

How might we…

  • Create tamper-proof visual evidence that’s immediately verifiable?

  • Enable real-time capture and validation by trusted sources on the ground?

  • Build a transparent, scalable system that integrates into journalism workflows?

The Solution

A secure cross-platform system to capture, verify, and source authentic images with speed and integrity.

Mobile App: Capture & Authenticate

Camera-first UX: Users capture photos directly in-app

Metadata Lock: Time, GPS, and device info automatically captured

Blockchain Integration: Photo + metadata recorded instantly, creating a digital fingerprint

Contributor Tools: Tag location, topic, or events to aid discovery

User Types: Citizen journalists, field photographers, freelancers

Design Principle: Verification by default, not afterthought.

Web Portal: Discover & Source

Browse By Need: Filter by hashtag, location, or incident

Image Requests: Newsrooms can post geo-tagged content requests

Download Packages: Images come bundled with verified metadata + audit trail

User Types: Editors, newsroom leads, investigative journalists.

Validation & Iteration

From Concept Generation to Early Testing

We created 3 vision posters to test conceptual framing (trust-first, speed-first, citizen-first). These helped align with journalists’ values and mental models.

We tested early flows with journalists, validating tasks like image tagging, uploading, and sourcing content.

Impact & Feedback

System Outcomes

  • End-to-end flow from real-time capture → verification → newsroom usage

  • Balanced credibility and speed for global news cycles

  • Closed the loop between field contributors and publishers

“This gives us speed without sacrificing trust. It could change how we source breaking visuals.” — Editor

Learnings & Next Steps

Learnings

  • UX decisions must align with trust models: Users need to feel verification without doing more work.

  • Scalability requires nuance: Local contributors need global validation frameworks.

Next Steps

  • DSLR compatibility for high-fidelity field work

  • Subscription tier for newsrooms to expedite licensing

  • Content moderation layer to flag manipulated content