Responsible use of artificial intelligence: Authorship, transparency, privacy, and fact-checking

Generative artificial intelligence (AI) has made fluent text cheap, but it has not made responsibility cheap. This opinion paper conceptualises responsible AI use as a discipline of accountability structured around four questions: Who is responsible for the work? What role did the AI tool play? Whose information was provided? Is the output accurate? Drawing on publication ethics, international AI governance frameworks, Nigerian data protection law and research on language-model limitations, the paper argues that authorship entails answerability rather than mere text production; transparency should be an established research practice; privacy requires safeguards when information is submitted to AI systems; and fact-checking remains indispensable despite the fluency of generated content. It further contends that institutional responses should prioritise critical AI literacy and responsible practice rather than rely excessively on prohibition or unreliable detection tools. Given their expertise in information evaluation, provenance, confidentiality and information literacy, library and information science professionals are well positioned to advance responsible AI governance. The paper proposes integrating transparent disclosure, data protection, human accountability and systematic verification into institutional policies and information literacy programmes. It concludes that the integrity of AI-assisted scholarship depends on the responsible evaluation and communication of information, not merely the efficiency of its production.