Current models within AI detection
Text
Image
Video
Open AI classifier
Vision transformer model
Microsoft video authenticator
RoBERTa large OpenAI detector
GAN detector
Stable attribution (rendered) out of use by legal issues)
Giant language model test room
One example of a model uses a classifier method to give the text a label — “real” or “fake” — and a percentage score associated with it. An output is displayed below.
Fractal GenAI Text Dectector This tool uses the RoBERTa model to detect generative AI written text. It is best at detecting text using GPT-2
Additional Tools
Human evaluation The most proficient method for identifying attribution and copyright concerns within GenAI's output remains human assessment. A human reviewer can thoroughly examine the content and pinpoint any resemblances to copyrighted materials.
Machine learning approach Leveraging machine learning, we can formulate models designed to identify instances of copyright violation. By training these models on a data set comprising established copyrighted materials, they can subsequently be employed
Statistical examination Statistical analysis serves as an effective means to unveil text patterns indicative of copyright infringement. This methodology detects works likely to be derivative of others, even when no exact matches are present.
to scan novel works for potential infringement.
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