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.
翻译：开发AI应用是一项多学科的工作,涉及与AI开发者合作的多重作用,我们使用这一总括术语,将数据科学家和其他AI对接者在同一团队中的角色包括在内。在这些协作中,掌握数据科学技能的AI开发者与通常不熟悉的外部利益攸关方之间存在知识不匹配。这种差异导致沟通差距,而AI开发者有责任向其合作者解释数据科学概念。在本文件中,我们报告一项研究,包括分析与AI开发者的访谈和他们制作的用于通信的工艺品。我们利用共享精神模型的分析视角,报告AI开发者面临的沟通差距类型,AI开发者如何跨学科和组织边界进行沟通,以及他们如何同时处理有关信任和期望的问题。
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