SYSTEMATIC LITERATURE REVIEW ON INTELLECTUAL PROPERTY (IP) RIGHTS AND ROLE OF GENERATIVE ARTIFICIAL INTELLIGENCE (AI) – RESPONSIBLE AI (ACADEMIC SECTOR)

Abstract

Generative Artificial Intelligence (AI) has transformed the global technological landscape by developing the following kinds of systems: capable of creating texts, images, melodies, computer code, and research materials. Platforms such as OpenAI, Google AI and Microsoft AI have enabled numerous generative AI tools to quickly gain popularity among the educational and business communities, including ChatGPT, Gemini, and Copilot. The rapid generation of generative AI has posed serious problems in terms of intellectual property (IP) rights, copyright ownership, plagiarism, patentability, and ethical administration regardless of the benefits of automation, productivity, and creativeness. AI systems are usually trained on massive amounts of data, which may involve copyrighted material, and raise legal and ethical issues about the ownership, and unauthorized use of creative work. This SLR explores the connection between the intellectual property rights and the governing of AI responsibly in the academic field. It uses the SLR methodology which is built on PRISMA as the study questions scholarly articles published in 2021-26 based on the databases of Scopus, Web of Science, ScienceDirect, and Google Scholar. A few of the distinguishable themes laid out in the review are copyright infringement, misunderstanding about authorship, scholarly integrity, transparency, responsibility, and responsible AI practice. The results indicate that the current IP regulations are inadequate to cope with the complexity of the generative AI technologies. The challenge that faces the universities and policymakers is on how to strike a balance between innovation, academic productivity and legality. The article can be transferred to the existing literature on responsible AI since it sums up the recent developments in AI regulation, pinpoints the flaws of the regulation, and presents the recommendations of what should be done by the academia to utilize AI in a responsible and ethical way. The conclusion of the study is that new legal frameworks, institutional AI policies as well as international cooperation are crucial to create equilibrium between technological innovation and intellectual property protection.