Artificial Intelligence (AI) for Research Lifecycle: Challenges and Opportunities

Abstract

Objective. This article aims to review the progress of AI technologies concerning their potential impact on academia, research processes, scientific communication, and libraries. Methods. AI tools for research lifecycle and their potential impact on academia and libraries were identified from various sources, mostly from the most influential recent scientific publications. Results. AI has become a driving force nowadays, creating both opportunities and challenges. Transformative AI-powered tools, exemplified by advanced models like ChatGPT, Llama-2, Google Bard, Microsoft Bing, and Jasper Chat, among others, find versatile utility across a broad spectrum of contexts, extending their impact to research process and publishing, as well as to librarianship. The enthusiastic embrace of AI in research is tempered by a pervasive concern over the potential for data fabrication, which can significantly compromise ethical standards and academic integrity. There is an urgent need to understand corresponding opportunities, challenges, and dangers. Some aspects of the use of AI tools for different stages of the research lifecycle are considered, and the main advantages and risks are analyzed. Conclusions. AI has the potential to drive innovation and progress in a wide range of fields and possesses significant potential to propel academia and librarianship into both exhilarating and challenging new frontiers. While AI-powered tools represent major advancements and potential to significantly impact academia, scholarly research, publishing, and university libraries. Privacy and bias are just two examples of the ethical considerations that need to be made.

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