AI or NOT
Team consisting of Boyu Niu (Inalco NLP researcher, PhD/CIFRE — LLMs/VLMs) and Abhinav Singh (HEC Paris PM, Ledger; blockchain, product/LLM strategy).
Project Description
“AI or Not?” is a gamified mobile platform where users swipe right/left on hyper-realistic AI-generated videos to classify them as real or fake -similar to Tinder but for media authenticity. Users compete on a global leaderboard, earn rewards, and monetize their analytical data through B2B partnerships with AI video model companies.
Core Problem: As AI video generation becomes indistinguishable from reality, society needs scalable human training data to improve detection models. Current solutions lack engagement.
Target Customer:
- Primary: Gen Z/millennial gamers (18-35) seeking entertainment + income
- Secondary: AI model companies needing real-time training data
Market Impact: Creates a self-reinforcing loop - the more users play, the better AI video models become, the more valuable the data is to sponsors.
Main Features
- Swipe-to-Classify Interface – Intuitive Tinder-like UX for rapid video classification
- Dynamic Leaderboard – Real-time ranking by accuracy score
- Dual Monetization:
- B2B Data Sales – Sell anonymized user classification patterns + confidence metrics to video generation companies
- Reward System – Points → redeemable rewards funded by AI model sponsors
- Analytics Dashboard – Track personal accuracy rates, time-per-classification, confidence levels, and earned rewards
User flow:
- User lands on app → sees leaderboard
- User swipes through 5-10 videos (real/AI mix)
- Gets instant feedback on correctness
- Climbs leaderboard in real-time
- Can invite for referral rewards
- Backend aggregates: classification patterns, confidence metrics, demographic trends, and video-specific difficulty data flowing to sponsor dashboard
Business Model:
B2B Data Sales: AI companies sponsor rewards in exchange for anonymized classification data (accuracy rates, time-to-decision, video difficulty metrics, confidence distributions).
User Engagement Loop: Users earn points for accurate/fast classifications, share achievements on social media, bringing new players organically with near-zero CAC.
Scaling: As a one-person operation, the platform scales through user-generated engagement with no moderation overhead. More users = more valuable data = higher sponsor deals.
Prior Work
None, we started from scratch