Sensemaking in collaborative work and learning is increasingly supported by GenAI systems, however, emerging evidence suggests that poorly designed GenAI systems tend to provide explicit instruction that groups passively follow, fostering over-reliance and eroding autonomous sensemaking. Group awareness tools (GATs) address this challenge through implicit guidance: rather than instructing groups on what to do, GATs externalize observable collaboration data through visualizations that reveal differences between group members to create cognitive conflict, which triggers autonomous elaboration and discussion, thereby implicitly guiding autonomous sensemaking emergence. Drawing on an initial literature search of existing GAT systems, this paper explores the design of GenAI-augmented GATs to support autonomous sensemaking in collaborative work and learning, presenting preliminary design principles for discussion.

翻译：在协作工作与学习中，意义建构正日益得到生成式人工智能系统的支持。然而，新出现的证据表明，设计不佳的生成式人工智能系统倾向于提供明确的指令，使群体被动遵循，从而助长了过度依赖并削弱了自主意义建构能力。群体感知工具通过隐性指导应对这一挑战：它并非指导群体该做什么，而是通过可视化将可观察的协作数据外化，揭示群体成员间的差异以引发认知冲突，从而触发自主的阐述与讨论，以此隐性引导自主意义建构的涌现。基于对现有群体感知工具系统的初步文献检索，本文探讨了生成式人工智能增强型群体感知工具的设计，以支持协作工作与学习中的自主意义建构，并提出了初步的设计原则以供讨论。