![]() The chance for content written by a human to be falsely labeled as AI-generated content is 0.2%, the lowest of any AI content detection platform. Once our internal team testing reaches a high confidence threshold, we leverage beta testers, giving an additional layer of assurance. – We only introduce new model detection after thorough testing. This allows us to continually use examples of false positives, rare as they may be, to improve. – To help accelerate our learning and refine the models used, we implemented a feedback loop where users can rate their results’ accuracy. – Our detection and the algorithms that power it is designed for detecting human-generated text, versus AI-generated text, the latter of which gives less accurate detection and increases the likelihood of false positives. To address this, we have taken several precautions, including: And with that comes the responsibility to ensure complete accuracy, particularly around false accusations. We strive to inspire authenticity and digital trust by creating secure environments to confidently share ideas and learn.
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