Knowledge Center
Learn everything you need to know about AI safety, deepfakes, scams, fact-checking, and online security.
Learning Paths
Structured courses designed for different interests and skill levels
AI Safety Academy
Comprehensive intro to AI systems, limitations, and best practices
Deepfake Masterclass
Understand deepfakes, detection methods, and how to spot fakes
Scam Awareness Center
Learn about current scams and how to protect yourself
Fact-Checking Guide
Master techniques to verify claims and identify false information
Digital Forensics Basics
Learn how experts detect image and video manipulation
Security & Privacy Guide
Comprehensive guide to online safety and privacy protection
Featured Guides
In-depth articles and guides on key topics
Understanding AI Hallucinations
What are AI hallucinations and why do they happen? Learn to identify them.
How to Spot a Deepfake
Practical techniques to identify manipulated videos and images.
Phishing Scams 101
Complete guide to recognizing and avoiding phishing emails.
The Verification Workflow
Step-by-step process to verify any claim or piece of information.
Understanding Image Metadata
How EXIF data reveals information about images and their origins.
Protecting Your Privacy Online
Tools and techniques to maintain your digital privacy and security.
Glossary
Common terms and definitions related to AI, security, and verification
Recommended Tools & Resources
Third-party tools and websites recommended by AI Trust Check
Fact-Checking Sites
Security Tools
Image Analysis
Research & References
Academic papers, reports, and research on AI safety and verification
The Problem of AI Hallucinations
Understanding why language models produce false information and current mitigation strategies.
2024 State of AI Report
Comprehensive analysis of AI trends, safety concerns, and industry developments.
How Humans Detect Deepfakes
Human capability studies on deepfake detection and implications for verification tools.
Misinformation Detection at Scale
Advanced techniques for identifying false information in large datasets.