Online knowledge communities (OKC) such as Stack Exchange, Reddit, and Zhihu have long functioned as socio technical infrastructures for collective problem solving. The rapid adoption of Generative AI (GenAI) introduces both complementarity and substitution. Large language models (LLMs) offer faster, more accessible drafts, yet divert traffic and contributions away from OKC that also provided their training data. To understand how communities adapt under this systemic shock, we report a mixed-methods study combining an online survey (N=217) and interviews with 11 current users. Findings show that while users increasingly rely on AI for convenience, they still turn to OKC for complex, ambiguous, or trust sensitive questions. Participants express polarized attitudes toward AI, reflecting divergent hopes and uncertainties about its role. Yet across perspectives, sustaining sociability, empathy, and reciprocity emerges as essential for community resilience. We argue that GenAI's impact constitutes not a terminal decline but a design challenge: to reimagine socio-technical complementarities that balance automation's efficiency with human judgment, trust, and collective stewardship in the evolving knowledge commons. To decline or sustain, it is now or never to take action.

翻译：在线知识社区（OKC），如 Stack Exchange、Reddit 和知乎，长期以来一直作为集体问题解决的社会技术基础设施。生成式人工智能（GenAI）的迅速普及带来了互补性与替代性。大型语言模型（LLM）提供了更快速、更易获取的草稿，却分流了原本流向OKC的流量与贡献，而这些OKC正是其训练数据的来源。为理解社区如何在系统性冲击下适应，我们采用混合方法研究，结合在线调查（N=217）和11位现有用户的访谈。研究发现，尽管用户因便利性日益依赖AI，但他们仍会转向OKC寻求复杂、模糊或信任敏感的问题。参与者对AI持两极分化的态度，反映出对其角色的分歧性期望与不确定性。然而，在各种观点中，维持社交性、同理心和互惠性对社区韧性至关重要。我们认为，GenAI的影响并非终结性衰退，而是一个设计挑战：即重新构想社会技术互补性，在持续演进的知识公共空间中，平衡自动化的效率与人类判断、信任及集体管理。是走向衰落还是保持可持续，现在不行动，更待何时。