In order to reduce the likelihood of misinterpretation, we have updated the AI indicator button in the Similarity Report to contain an asterisk for percentages less than 20% to call attention to the fact that the score is less reliable. We learned that our AI writing detection scores under 20% have a higher incidence of false positives.This is inconsistent behavior, and we will continue to test to understand the root cause. Added an additional indicator for documents with less than 20% AI writing detected.Based on the results of these tests, we made the below updates to our model in May to ensure we hold steadfast on our objective of keeping our false positive rate below 1% for a document. Since the launch of our solution in April, we tested 800,000 academic papers that were written before the release of ChatGPT. We will continue to adapt and optimize our model based on our learnings from real-world document submissions, and as large language models evolve to ensure we maintain this less than 1% false positive rate. We’re committed to safeguarding the interests of students while helping institutions maintain high standards of academic integrity. For example, if we identify that 50% of a document is likely written by an AI tool, it could contain as much as 65% AI writing. We’re comfortable with that since we do not want to incorrectly highlight human-written text as AI-written. In order to maintain this low rate of 1% for false positives, there is a chance that we might miss 15% of AI written text in a document. To bolster our testing framework and diagnose statistical trends of false positives, in April 2023 we performed additional tests on 800,000 additional academic papers that were written before the release of ChatGPT to further validate our less than 1% false positive rate. In other words, we might flag a human-written document as AI-written for one out of every 100 fully-human written documents. We strive to maximize the effectiveness of our detector while keeping our false positive rate - incorrectly identifying fully human-written text as AI-generated - under 1% for documents with over 20% of AI writing. We are actively working on expanding our model to enable us to better detect content from other AI language models.'. Because the writing characteristics of GPT-4 are consistent with earlier model versions, our detector is able to detect content from GPT-4 (ChatGPT Plus) most of the time. Using the average scores of all the segments within the document, the model then generates an overall prediction of how much text in the submission we believe has been generated by AI.Ĭurrently, Turnitin’s AI writing detection model is trained to detect content from the GPT-3 and GPT-3.5 language models, which includes ChatGPT.
If it determines the entirety of the sentence was generated by AI it will receive a score of 1. If our model determines that a sentence was not generated by AI, it will receive a score of 0. The segments are run against our AI detection model and we give each sentence a score between 0 and 1 to determine whether it is written by a human or by AI. Those segments are then overlapped with each other to capture each sentence in context. When a paper is submitted to Turnitin, the submission is first broken into segments of text that are roughly a few hundred words (about five to ten sentences).
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