This empirical study serves as a primer for interested service providers to determine if and how Large Language Models (LLMs) technology will be integrated for their practitioners and the broader community. We investigate the mutual learning journey of non-AI experts and AI through CoAGent, a service co-creation tool with LLM-based agents. Engaging in a three-stage participatory design processes, we work with with 23 domain experts from public libraries across the U.S., uncovering their fundamental challenges of integrating AI into human workflows. Our findings provide 23 actionable "heuristics for service co-creation with AI", highlighting the nuanced shared responsibilities between humans and AI. We further exemplar 9 foundational agency aspects for AI, emphasizing essentials like ownership, fair treatment, and freedom of expression. Our innovative approach enriches the participatory design model by incorporating AI as crucial stakeholders and utilizing AI-AI interaction to identify blind spots. Collectively, these insights pave the way for synergistic and ethical human-AI co-creation in service contexts, preparing for workforce ecosystems where AI coexists.

翻译：本实证研究旨在为感兴趣的服务提供商提供初步指导，帮助他们判断是否以及如何将大语言模型（LLM）技术融入其从业者及更广泛社区的工作中。我们通过CoAGent（一种基于LLM智能体的服务共创工具）探究非AI专家与AI之间的相互学习过程。通过三阶段参与式设计流程，我们与美国各地公共图书馆的23位领域专家合作，揭示了将AI整合到人类工作流程中的根本性挑战。研究发现提炼出23条可操作的"AI服务共创启发式指南"，阐明了人类与AI之间微妙的共同责任关系。我们进一步归纳出AI应具备的9项基础能动性要素，强调所有权、公平待遇和表达自由等关键特质。通过将AI视为关键利益相关者并利用AI-AI交互识别盲点，我们的创新方法丰富了参与式设计模型。这些洞见共同为服务场景中协同且合乎伦理的人机共创铺平道路，助力构建AI与人类共存的劳动力生态系统。