Misinformation Center

Misinformation exploits human bias: believe what confirms your views, share before verifying. After AI, the same problem arrived at a different scale — more believable, more volume, same fragile ecosystem.

Survey Results (n=2,000)

74% encountered misinformation weekly, 62% of parents felt overwhelmed, and <20% trusted existing fact-checkers.

The Generational Sandwich

Mothers filtering misinformation for kids while protecting elderly parents from scams — shaped the archetype strategy.

The Transparency Demand

Users wanted to see who benefits from content, beyond a fact-check label.

The Platform Trust Problem

Testing rejected a solution integrated into a major social platform immediately — the tool had to stand independent.

Three rounds before the four tools settled — a platform-embedded concept, a format head-to-head, and the full build at the capstone showcase.

Snopes is monetized; the free alternatives are nonprofits with text-heavy resources people ignore — two categories, neither worked:

The gap: users trusted established outlets, wanted multiple sources, inside apps they already used — leaving was fatal friction.

The integration insight. Professors waved this off as digging too deep, so I worked it through with my husband, an AI scientist outside product: a trusted utility in trusted surfaces — Safari share sheet, Apple News, native camera — backed by verifiable institutions, owned by none of the platforms it lives in.

Recruited through the UW Misinformation Center network — UW students and Seattle-area school networks.

Early testing surfaced ambiguous labels and slow search, prompting color-coded ratings.

The finding that changed the problem: families argue along specific channels — adults 55–80 scammed via WhatsApp from trusted contacts, teens 13–18 pressured into exposing data, 25–40 caught managing both.

The archetypes emerged from that chain:

Truth Seekers (18–30)

Already motivated, cross-referencing sources, want to be validators.

Overwhelmed Guardians (25–40)

Want verification tools, but any friction loses this group.

Vulnerable Believers (55–80)

Trust what comes from people they know — design means meeting existing behavior.

The strategy: design for the first two — they become the human layer protecting the third, like a mother who verifies before forwarding to her parent.

What Misinfo Day revealed that recruited testing couldn't. Live crowds reveal behavior that self-reports miss. Younger participants abandoned reading within seconds; older participants trusted Ask Us over automated ratings. Engagement spiked when framed as a skill rather than a correction.

This is also when Scan got decided — attendees wanted to check what was physically in front of them, too.

Misinfo Day — live testing with ~1,800 participants

Younger testers took to search and the quiz immediately. Older participants stayed out until Scan arrived — pointing a camera at a newspaper asked nothing new of them, and removed what they disliked most: asking a younger relative for help.

The final version was framed as a system utility — something that lives beside the compass and the calculator, not an app you remember to open.

TrueMedia.org built deepfake detection for the 2024 election; through UW I contributed research synthesis. Their tool served journalists, mine a teenager. They analyzed 60,000+ pieces of media before shutting down in January 2025, open-sourcing the tech instead of chasing funding.

TrueMedia's Head of Product reframed it: platforms are ambivalent about detection since it drives engagement, and personalized scams never reach anyone to verify them. Authenticating content at creation would be more efficient — but C2PA proposed that and stalled on incentives.

TrueMedia was research-grounded and mission-complete, yet closed on economics rather than design. The answer — integration into trusted surfaces — never had a business model.

What changed. Feedback pushed the quiz toward teaching why, and badges toward layered reveals — signal first, reasoning a tap away. By 2026, AI solves the staffing; the ecosystem question remains.