AI Text Detection

AI text detection focuses on distinguishing computer-generated text from human-written text, primarily addressing concerns about plagiarism, misinformation, and the integrity of academic and professional work. Current research explores various approaches, including traditional machine learning models (e.g., Naive Bayes, Random Forests) and more advanced deep learning architectures like Transformers and Convolutional Neural Networks, often incorporating techniques like adversarial learning to improve robustness. The development of accurate and reliable AI text detection methods is crucial for maintaining academic integrity, combating the spread of misinformation, and ensuring trust in online content.