Knowledge Lineage from Isnad to AI: Reframing Authorship and Responsibility in the Generative AI Era

Generative artificial intelligence (AI) is rapidly transforming scholarly writing and research, raising urgent questions about authorship, intellectual ownership, and epistemic responsibility.This study aims to investigate how knowledge lineage-defined as the traceable chain of transmission, transformation, and attribution-connecting ideas to their origins-can be preserved in an era where AI increasingly mediates knowledge production.Adopting a theoretical-conceptual methodology, the paper integrates Western philosophy (Foucault's author-function, Kuhn's paradigm shifts), Floridi's concept of ectypes, and Islamic epistemology (isnd, amna, mas'liyya), alongside comparative analysis of institutional practices at Harvard, Oxford, and King Saud University.The analysis reveals that while AI accelerates content creation, it simultaneously introduces epistemic opacity, breaks attribution chains, and generates "orphaned" knowledge outputs that lack identifiable provenance.To address these risks, the study proposes a multi-tiered ethical framework that includes mandatory AI-use disclosure, human-in-the-loop verification, metadata-based "AI isnd," and institutional accountability mechanisms.This framework bridges global AI ethics (OECD, UNESCO) with culturally embedded models of moral responsibility, reinforcing that human scholars must remain the ethical custodians of knowledge.The paper concludes that preserving knowledge lineage is not merely a technical challenge but a moral and cultural imperative.By embedding transparency, traceability, and accountability into both technical systems and institutional policies, the integrity of scholarly communication can be sustained in an AI-saturated future.