内容创意工作向来被认为是人类的专属和智慧的体现，但随着生成式人工智能技术（AIGC）的出现，人类的内容生产方式发生了巨大变革，人机共创已成为数字内容生成的重要趋势。研究以补偿性媒介为理论视角，该理论核心关注媒介的进化以及新旧媒介的交融和继承，与探讨AIGC技术如何赋能平台内容创作的议题具有较强的理论贴合性。研究基于参与式观察、扎根理论、深度访谈等方法，围绕AIGC在内容生产领域中的功能类别特征、补偿实现路径、媒介补偿维度、未来发展空间四个方面递进式展开。AIGC所带来的人机协作新范式在数字内容生产领域不断释放价值，内容平台试图打造出兼具个性化与实用性的AIGC功能以赋能平台内容创作。首先以202篇涉及我国主流内容平台AIGC功能的相关报道与宣传稿件为研究对象，运用扎根理论研究方法获得了66个开放式编码、32个主范畴和7个主类属。主类属又可被归纳为功能类别与作用、主体间互动行为和媒介补偿实现三个核心类属，三者的关系共同揭示了用户在内容平台运用AIGC功能进行内容生产并实现媒介补偿的机制。研究亦由此归纳出了内容平台AIGC功能的四种主要类别，分别是：内容创造、内容优化、实时互动、数字人制作。媒介补偿的实现还与用户和AIGC的交互行为息息相关，通过对11名内容创作者及相关从业者进行深度访谈，从用户的创作行为层面进一步厘清发生媒介补偿的路径。研究发现，媒介补偿的实现依赖于创作者、内容平台、AIGC技术三个主体的协同作用，又可具体分为三个阶段：双向触发的内容萌芽阶段、交互反馈的内容发展阶段、多维补偿的内容实现阶段。AI和人类创作者共同推动着创意内容的生产，从情感、内容、技术、身体等多个维度实现多元主体的补偿，具体补偿方式包括：社会关系补偿、娱乐体验补偿、生产模式重构、平台信息再组织、大模型能力跃升、机器学习与优化、身体时空补偿、劳动行为替代。AIGC作为一项前沿技术，仍具有广泛的进步空间。研究最后，从功能设计、内容质量、法律风险等层面，指出当前AIGC在内容创作应用中仍存在的问题，提出对于实现AIGC技术良性发展并继续提升其内容创作与补偿能力的思考。
Content creative work has always been regarded as a manifestation of human exclusivity and wisdom, but with the emergence of Generative Artificial Intelligence technology, human content production methods have tremendous changes, and human-machine co-creation has become an important trend in digital content generation. This study takes remedial medium as the theoretical perspective, and its theoretical core focuses on the evolution of media as well as the integration and inheritance of new and old media. It has strong theoretical relevance to exploring how AIGC empowers platform content creation. The research is based on grounded theory, participant observation and in-depth interviews, focusing on four progressive issues of AIGC in the field of content production: functional category and characteristics, compensation implementation paths, media compensation dimensions, and future development space.The new paradigm of human-machine collaboration brought about by AIGC continues to unleash value in the field of digital content production. Content platforms attempt to create various AIGC functions that combine personalization and practicality to empower platform content creation. This article first takes 202 relevant reports and promotional articles related to the AIGC function of China's mainstream content platform as the research object and uses grounded theory to obtain 66 open codes, 32 main categories, and 7 main categories. The main categories can be summarized as functional categories and roles, inter-subject interaction behavior, and media compensation implementation. The relationship between the three reveals the mechanism by which users use AIGC functions for content production and achieve media compensation on content platforms. This article also summarizes four core categories of AIGC functions on content platforms, namely: content creation, content optimization, real-time interaction, and digital human production.The implementation of media compensation is also closely related to the interaction behavior between users and AIGC. The study conducted in-depth interviews with 11 content creators and related practitioners with experience in using AIGC, starting from the user's creative behavior, to further clarify the specific paths through which media compensation occurs. Research has found that the implementation of media compensation relies on the collaborative efforts of human creators, content platforms, and AI, which can be further divided into three stages: the content germination stage triggered in both directions, the content development stage of interactive feedback, and the content implementation stage of multi-dimensional compensation. AI and human creators complement each other in the process of content creation, jointly promoting the production of creative content, and achieving compensation for multiple subjects from multiple dimensions such as emotion, content, technology, and body. Specific compensation methods include social relationship compensation, entertainment experience compensation, production mode reshaping, platform information reorganization, multi-modal technology integration, machine learning and optimization, body time and space compensation, and labor behavior substitution.As a cutting-edge technology, AIGC still has broad space for progress. Finally, from the aspects of functional design, content quality, and legal risks, the study points out the existing problems in the application of AIGC in content creation and proposes thoughts on achieving the healthy development of AIGC technology to continue improving its content creation and compensation capabilities.
