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@article{184321,
        author = {Aadya Ajit Deshmukh and Pranavkumar A Bhadane},
        title = {AI-Generated Content Detection A Cat-and-Mouse Game of Technology and Ethics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {1090-1095},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184321},
        abstract = {AI-generated content now appears across education, journalism, governance, and virtual environments. While it is great for efficiency and creativity, it also introduces risks of plagiarism, misinformation, and loss of trust. Detection methods have emerged to separate synthetic from human content, using statistical stylometry, linguistic and semantic analysis, image forensics, and large language models. But these systems are not perfect, as they show high false positive rates and limited adaptability to new generative models. This survey examines the technical basis of detection, its application in key domains, and the ethical concerns that accompany its application. Bias, privacy, and the danger of wrongful attribution are emphasized as critical challenges. The paper concludes with open problems and future directions for reliable and responsible detection.},
        keywords = {Educational Integrity, AI-Generated Content Detection, Large Language Model, Text Authenticity Verification, AI-generated Images, News and Journalism, Convolutional Neural Networks, Diffusion Models, Synthetic Image Detection, Metaverse},
        month = {September},
        }