Generative AI's Impact on Knowledge Ownership: Ensuring Fair IP Attribution

Abstract

With the in-depth application of generative artificial intelligence (Gen AI) in the field of knowledge management (KM), the traditional intellectual property (IP) system is facing serious challenges. The AI-driven knowledge production model blurs the clear boundaries of traditional IP ownership, resulting in increased uncertainty in the distribution of rights and an aggravation of the imbalance in the pattern of interests. This dilemma is further amplified by Gen AI's unique "black box" and "autonomous" characteristics, and it is difficult to determine a clear ownership subject for its automatically generated content. These challenges have exposed the fundamental limitations of the traditional IP framework, which is based on an anthropocentric knowledge production paradigm that is difficult to adapt to the characteristics of knowledge innovation in the AI era. By systematically combing the solutions proposed by various countries in the field of KM, combined with the analysis of international typical cases, this study focuses on the mainstream coping strategies, including the separation of moral rights and economic rights, the collective management authorization model, the transformation of the safe harbour principle, and the exploration of patent paths. The results show that the existing schemes have significant limitations: they are insufficient in terms of technical adaptability, legal compatibility and ethical legitimacy. These solutions focus too much on rights segmentation and ignore dynamic collaboration; Emphasis is placed on post-event relief, and there is a lack of source governance. In order to overcome these limitations, this study innovatively proposes an optimization framework of "technology-law-governance": develop an interpretable contribution tracking algorithm at the technical level, and construct a causal mapping of data-model-knowledge assets; At the legal level, a mixed ownership structure is designed to balance private rights protection and public access through hierarchical rights confirmation. At the governance level, a global coordination mechanism has been established to use smart contracts to achieve real-time distribution of cross-border IP rights. This integrated solution aims to reconstruct the IP system in the AI era, promote technological innovation while maintaining the sustainability and fairness of the knowledge ecosystem.