🚀 AI-Powered Decentralized News Verifier¶

🗂️ Project Overview¶

Student ID: 20220934
Name: Belay Zeleke
Project Title: AI-Powered Decentralized News Verifier
Summary:
This project proposes an AI and blockchain–based solution to combat the spread of misinformation online. AI models will analyze news articles to detect potential fake or misleading content, while blockchain will provide a transparent, tamper-proof record of verification results. This combination aims to make fact-checking faster, more accessible, and immune to centralized control or manipulation.

1. 🧩 Problem:¶

Misinformation spreads rapidly through social media and news outlets, shaping public opinion and potentially leading to harmful real-world consequences.

Limitations of Traditional fact-checking processes:

Rely heavily on centralized fact-checking authorities.
Lack transparency in the verification process.
Updates or retractions can be hidden or altered over time.

Why worth solving: Misinformation undermines trust in institutions, polarizes communities, and can cause harm in areas like public health, elections, and finance. A transparent, decentralized approach can restore trust in information integrity.

2. 💡 Solution: The Proposed Approach¶

Proposed solution: To design a system where AI automatically scans articles, evaluates credibility using NLP-based fact-checking techniques, and stores a permanent verification record on the blockchain. Users can check any article’s trustworthiness in seconds.

How AI & Blockchain are combined:

AI handles content analysis: detecting misleading patterns, cross-referencing facts with trusted data sources.
Blockchain handles trust and permanence: storing the verification results and preventing tampering.

How Could AI Estimate the Credibility of Breaking News

Linguistic & Semantic Analysis

 NLP models detect writing patterns often associated with misinformation:

Overly emotional language
Clickbait-style headlines
Unsupported claims (“Scientists say…” without naming sources)
Logical inconsistencies
It uses semantic similarity to see if the content aligns with existing verified narratives.

Source Credibility Scoring

Reference to Credible Sources (Cross-Verification)

Workflow Diagram

3. 🔗 Why Blockchain (and Token)?¶

Why blockchain:

Ensures verification results cannot be altered or deleted.
Allows anyone to independently verify an article’s authenticity.

Blockchain’s role in this context:

Serves as a permanent, transparent ledger of fact-checking results.
Decentralizes trust so no single authority controls the verification process.

Token design:

A governance/reputation token could incentivize expert validators and community participation.
Token holders could vote on disputed AI decisions to refine accuracy.

4. 🛠️ MVP or Prototype¶

Current status:
☑ Idea only ☐ Prototype ☐ Working MVP

Planned key features:

NLP-based misinformation detection with AI models.
Blockchain smart contract to store verification data.
User-friendly web interface for submission and lookup.

Code repository: Will be created if the project is selected for further development.

5. 📬 Submission to Hackathons or Grant Programs¶

Name of the program: HackFinity
Submission link: [URL]
Summary: Proposal for an AI + blockchain fact-checking platform that provides a fast, transparent, and decentralized method for news verification.
Screenshot of the submission confirmation or page

6. 🤔 Reflection & Future Work¶

 What I expect to learn:

How to fine-tune NLP models for detecting misinformation.
How to design efficient blockchain smart contracts for public verification.
How to build trust and user adoption in fact-checking tools.

Biggest anticipated challenges:
Avoiding bias in AI model training.
Integrating human review for edge cases.

Future improvements:
Multi-language support.
Browser extension for real-time article verification.
Integrating AI-generating truth value to social media posts.

7. 📚 References¶

Ethereum Smart Contracts Documentation
Fact-Checking AI Models – Google AI Blog