FairMove AI

FairMoveAI helps people verify overseas job offers and contracts using AI,detect scam risks, and understand their legal rights before moving abroad protecting workers from exploitation across borders.

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Inspiration

Every year, millions of people migrate overseas in search of better job opportunities. Unfortunately, overseas job fraud and visa scams have become extremely common, especially affecting first-time migrants and workers from developing regions.

While reading real-world scam reports and news articles, I noticed that many victims are not careless — they simply lack access to clear, reliable information. Job offers often use complex legal language, false urgency, or promises like “guaranteed visa” that are difficult for non-experts to evaluate.

This inspired me to build FairMove AI — a simple, accessible decision-support tool that helps people evaluate overseas job offers before they make life-changing decisions.

What it does

FairMove AI analyzes overseas job offers and employment contract text to identify scam risks before a user proceeds.

Users paste a job offer into the platform, and FairMove AI:

  • Detects financial, visa, and urgency-related scam indicators
  • Calculates an overall risk level and trust score
  • Provides category-wise risk breakdown
  • Identifies country-specific fraud warnings
  • Generates an actionable safety checklist
  • Explains the reasoning behind the risk assessment in plain language

The goal is not just detection, but helping users understand why an offer may be risky and what steps they should take next.

How we built it

FairMove AI was built as a lightweight web application using Python and Flask for the backend, and HTML/CSS for the frontend.

The system uses rule-based AI logic inspired by real scam patterns such as:

  • Requests for upfront payments
  • Guaranteed visa promises
  • No interview offers
  • Artificial urgency tactics
  • Region-specific scam trends

Instead of black-box predictions, FairMove AI focuses on explainable and ethical AI, ensuring users can clearly see how conclusions are reached.

Challenges we ran into

One of the biggest challenges was balancing simplicity with meaningful analysis. Overseas job scams vary widely, and overgeneralization can cause false alarms.

To solve this, the system was designed with:

  • Multi-category risk scoring
  • Confidence levels
  • Human-readable explanations
  • Clear disclaimers encouraging independent verification

Another challenge was designing the system to work without external APIs, ensuring reliability and ease of deployment during the hackathon.

Accomplishments that we're proud of

  • Built a complete, functional AI decision-support system within a short timeframe
  • Implemented explainable risk assessment instead of black-box scoring
  • Designed a user-friendly interface for non-technical users
  • Addressed a real-world social problem with large-scale impact potential
  • Created an ethical AI system focused on user safety and awareness

What we learned

This project reinforced the importance of human-centered AI design. Technology should not just provide outputs, but guide users toward safer decisions.

I also learned how explainability, clarity, and ethical considerations are just as important as technical complexity when building impactful AI systems.

What's next for FairMove AI

Future improvements include:

  • Integration with government and embassy verification portals
  • Machine learning models trained on real scam datasets
  • Multi-language support for global accessibility
  • PDF risk reports for documentation and legal reference
  • Mobile-friendly and offline versions for low-connectivity regions

FairMove AI has the potential to grow into a trusted public safety tool for global migrant workers.

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