Detecting AI Generated Text
Induri Chandana, Oruganti Mariya Reshma, Nerella Geetha Sree, Bommu Jagadeesh Reddy, Syed Shareefunnisa · 2024
The exponential progression in artificial intelligence (AI) technologies has spearheaded the evolution towards proliferation of AI-generated text across various online platforms. This phenomenon poses significant challenges in maintaining the integrity of information dissemination and combating misinformation. In response, this project proposes a comprehensive approach to detecting AI-generated text through ML methods. By leveraging a diverse dataset of both AI-generated and human-generated text, the project aims to develop robust models capable of accurately discerning AI-generated content. The methodology involves feature engineering, model training, and validation using state-of-the-art NLP frameworks. Additionally, the project explores the ethical implications of AI-generated content detection and considers potential countermeasures against adversarial attacks. The outcomes of this project have practical implications for enhancing content moderation systems, safeguarding against malicious use of AI, and fostering trust in online information ecosystems.