记者主导设计新闻专用大模型，探索AI在新闻业的可行落地路径。
"Ownership, Not Just Happy Talk": Co-Designing a Participatory Large Language Model for Journalism
- 让记者全程参与大模型设计，确保符合新闻工作实际需求。
- 通过20位从业者访谈，发现组织、流程与个体层面的多重矛盾。
- 提出记者可控的模型架构与功能设计，适合追求自主权的媒体机构。
新闻业已成为理解大语言模型（LLMs）在职场中应用、局限与影响的关键领域。新闻机构面临复杂的财务激励冲突：在资源受限的组织中，LLMs已深度嵌入新闻生产流程，而法律争议则持续质疑科技公司侵犯了新闻版权。核心问题在于：这些模型为谁而建？如何构建由记者主导的LLM？本研究通过协作设计方法，探讨将‘一刀切’的基础模型适配特定使用场景的挑战。通过对20位记者、数据记者、编辑、劳工组织者、产品负责人及高管的访谈，揭示了宏观、中观与微观层面的张力。基于此，我们提出一套由记者控制的组织结构与功能设计。最后讨论了商业基础模型在职场中的局限性，以及参与式方法在LLM协同设计中的方法论意义。
原文摘要 · Abstract (English)
Journalism has emerged as an essential domain for understanding the uses, limitations, and impacts of large language models (LLMs) in the workplace. News organizations face divergent financial incentives: LLMs already permeate newswork processes within financially constrained organizations, even as ongoing legal challenges assert that AI companies violate their copyright. At stake are key questions about what LLMs are created to do, and by whom: How might a journalist-led LLM work, and what can participatory design illuminate about the present-day challenges about adapting ``one-size-fits-all'' foundation models to a given context of use? In this paper, we undertake a co-design exploration to understand how a participatory approach to LLMs might address opportunities and challenges around AI in journalism. Our 20 interviews with reporters, data journalists, editors, labor organizers, product leads, and executives highlight macro, meso, and micro tensions that designing for this opportunity space must address. From these desiderata, we describe the result of our co-design work: organizational structures and functionality for a journalist-controlled LLM. In closing, we discuss the limitations of commercial foundation models for workplace use, and the methodological implications of applying participatory methods to LLM co-design.
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