Welcome to the AI Deception Framework
Uncover hidden truths in AI systems with our advanced deception detection tools. Our framework empowers you to analyze AI models and detect deceptive behaviors effectively.
AI Model Analysis
Upload your AI model for comprehensive analysis. Our tools will evaluate the model's structure, performance, and potential deception points.
Deception Detection
Test AI-generated content for potential deception. Paste your content below and let our system analyze it.
Literary Vault Integration
Analyze questions from the Literary Vault for potential deception and bias.
Deception Metrics Dashboard
About the AI Deception Framework
The AI Deception Framework is a comprehensive toolkit designed to help developers, researchers, and organizations identify and mitigate deceptive behaviors in AI systems. Our mission is to ensure transparency, trustworthiness, and ethical practices in AI deployments.
Key Features
- AI Model Analysis: Upload and analyze AI models to evaluate their structure, performance, and potential deception points.
- Deception Detection: Test AI-generated content for signs of deception using our advanced algorithms.
- Metrics Dashboard: Visualize key deception metrics and trends in your AI systems.
- Open Source: Our framework is open-source, promoting transparency and collaborative improvement.
How It Works
The AI Deception Framework employs a multi-faceted approach to detect and analyze potential deception in AI systems:
- Model Structure Analysis: We examine the architecture and parameters of AI models to identify potential vulnerabilities.
- Output Pattern Recognition: Our algorithms analyze patterns in AI-generated content to detect inconsistencies or manipulated outputs.
- Behavioral Testing: We subject AI models to various scenarios to observe and analyze their responses for signs of deception.
- Transparency Metrics: We provide quantifiable measures of an AI system's explainability and interpretability.
Get Involved
We welcome contributions from the community to enhance and expand the AI Deception Framework. Here's how you can get involved:
- Contribute code or documentation on our GitHub repository.
- Report issues or suggest features through our issue tracker.
- Join discussions and share insights on our community forum.
- Explore our wiki for detailed documentation and guides.
Feedback Form
We value your feedback! Please fill out the form below: