In an era where synthetic media is increasingly sophisticated, tools for detecting AI-generated images have become essential. However, these tools – while powerful – are not without their limitations. Understanding these blind spots is crucial.
Screenshots
When someone takes a screenshot of a synthetic image, they essentially flatten the image’s metadata and model-specific fingerprints. Most detectors rely on subtle traces left by generative models, such as GANs or diffusion techniques. A screenshot removes these, replacing them with metadata from the device that captured the screenshot – making it nearly impossible to trace the image back to its synthetic origin.
Re-Photos
Similarly, taking a photo of an image using another phone or camera strips the digital clues. Once an image is re-captured through a lens, it’s effectively transformed into a new image. Artifacts from the screen, lighting conditions, and the new device’s camera all contribute to masking the original synthetic nature of the image.
Social Media Processing
When images are uploaded to platforms like Instagram, Facebook, or X (formerly Twitter), they often undergo a series of automated changes:
- Compression: Reduces file size and quality, blurring telltale signs.
- Scaling: Alters resolution, which may affect pixel-level traces.
- Cropping/Zooming: Removes parts of the image that could be critical for detection.
These transformations make it difficult to reliably flag synthetic content. The image you upload isn’t the same one someone sees or downloads later.
Please keep in mind these limitations while using the Image Inspector!