The development of AI applications is a multidisciplinary effort, involving
multiple roles collaborating with the AI developers, an umbrella term we use to
include data scientists and other AI-adjacent roles on the same team. During
these collaborations, there is a knowledge mismatch between AI developers, who
are skilled in data science, and external stakeholders who are typically not.
This difference leads to communication gaps, and the onus falls on AI
developers to explain data science concepts to their collaborators. In this
paper, we report on a study including analyses of both interviews with AI
developers and artifacts they produced for communication. Using the analytic
lens of shared mental models, we report on the types of communication gaps that
AI developers face, how AI developers communicate across disciplinary and
organizational boundaries, and how they simultaneously manage issues regarding
trust and expectations.

多学科合作的 AI 开发中，通信差距与信任问题是重要挑战，通过分析智能开发人员的访谈和沟通产物，分享了智能开发人员面临的通信障碍类型、如何跨学科和组织沟通，以及如何同时管理信任和期望。