Detect AI-Generated Images

Our AI detection system uses advanced machine learning algorithms trained on thousands of AI-generated and human-created images. While highly sophisticated, accuracy can vary depending on the image quality, resolution, and generation method. Currently, our system achieves approximately 85-92% accuracy on most popular AI art generators. We recommend using the tool as a helpful guide rather than a definitive assessment, especially for borderline cases.

Factors that affect accuracy include:

• Image resolution: Higher resolution images (above 1024px) yield better results
• Generation method: Some newer AI models are harder to detect than established ones
• Post-processing: Heavily edited or composited images may reduce detection accuracy
• Content type: Certain subjects (like abstract art) can be more challenging to classify

Our system can analyze images created by popular AI art generators including:

• DALL-E (versions 1, 2, and 3)
• Midjourney (all versions through v6)
• Stable Diffusion (including XL and various fine-tuned models)
• Leonardo AI
• Firefly
• Imagen
• Playground AI

The detector looks for common patterns, artifacts, and characteristics typically present in AI-generated artwork, including:

• Unnatural textures in hair, fur, or fabrics
• Symmetry issues in faces and objects
• Inconsistent lighting and shadows
• Artifacts in fine details like text, fingers, or teeth
• Repetitive patterns that lack organic variation

We continuously expand our detection capabilities as new AI models emerge.

Yes! Your privacy is our top priority. All image analysis is performed directly in your browser using client-side processing - we don't store, collect, or transmit your images to any external servers. No copies of your images are saved or used for training our models. You can check our Privacy Policy for more detailed information about our data handling practices.

Key security features:

• Local processing: All analysis happens in your browser
• No storage: Images are never saved to our servers
• No tracking: We don't log which images you analyze
• Encryption: All communications are secured with TLS 1.3

Our detection system combines multiple advanced techniques to identify AI-generated content:

1. Pixel-level analysis: Examines statistical patterns in pixel arrangements that differ between AI and human-created images
2. Frequency domain analysis: Uses Fourier transforms to detect unnatural frequency patterns characteristic of AI generation
3. Semantic analysis: Checks for logical inconsistencies in lighting, physics, and object relationships
4. Artifact detection: Identifies common generation artifacts like distorted textures or impossible geometries
5. Model fingerprinting: Recognizes signatures left by specific AI models during generation

The system synthesizes these analyses into a confidence score that reflects the likelihood of AI generation. Our models are trained on over 5 million verified images from both human and AI sources.

While our system detects most mainstream AI generators with high accuracy, there are some limitations:

• New models: Recently released AI systems may not be immediately detectable until we update our models
• Hybrid images: Compositions mixing AI and human-created elements can be challenging
• Low-quality inputs: Heavily compressed or small images reduce detection accuracy
• Specialized domains: Some medical or scientific AI imagery may require specialized detection

We maintain a 95%+ detection rate for major models like Midjourney and DALL-E, and continuously expand coverage to new generators. When uncertain, the system will provide a medium confidence score rather than a definitive judgment.

AI-generated images often exhibit several distinctive characteristics:

These differences stem from how AI systems construct images statistically rather than through intentional artistic choices. However, as AI improves, some of these tells are becoming more subtle.

Our system maintains significant detection capability even with modified images:

• Basic edits (cropping, filters): 85-90% detection accuracy
• Moderate edits (color grading, compositing): 75-85% accuracy
• Heavy edits (multiple AI sources combined): 60-75% accuracy
• AI+human hybrid art: Detection depends on the proportion of AI content

The system provides a confidence score rather than binary judgments for edited content. For borderline cases, we recommend:

1. Checking multiple sections of the image separately
2. Comparing against the original if available
3. Looking for telltale signs of editing like inconsistent compression artifacts

We maintain a rigorous update schedule to keep pace with advancing AI technology:

• Weekly: Minor adjustments and bug fixes
• Monthly: New model weights and detection improvements
• Quarterly: Major architecture updates
• Emergency updates: Deployed within 72 hours for critical new AI models

Our update process involves:

1. Collecting samples from new AI systems
2. Retraining detection models
3. Rigorous testing against validation sets
4. Gradual rollout with performance monitoring

Users automatically receive updates without needing to refresh their browsers, thanks to our progressive web app architecture.