Authors: Mayur Rajaram Chavan, Professor Abhishek Popat Bangar, Professor S. B. Bhosale, Professor Karad V. A.
Abstract: Generative artificial intelligence (GenAI) tools are now widely used to produce and support digital content such as stories, news items and social-media posts. Such tools can make a single piece of output look better, yet they also bring worries about originality, sameness across many outputs, bias, factual accuracy, creative control and ownership rights. This paper reviews five chosen scholarly works that look at creator responsibility, AI-supported story writing, prompting as a creative method, copyright, and bias in machine-written news. Read together, the studies indicate that a gain for one writer does not automatically become a gain for everyone: stories written with AI help may score higher while growing more alike. The remaining works point to the need for human fact-checking, the risk of skewed representation, the difficulty of turning unspoken creative know-how into written prompts, and unsettled questions about ownership and openness. We compare how the studies were carried out and what each contributes, draw out the shared challenges, and suggest where future work could head. Because only five hand-picked papers were examined and no exhaustive database search was run, this work is a focused narrative review rather than a systematic one.
