论文标题
数字合作者：通过人工智能增强可视化设计中的任务抽象
Digital Collaborator: Augmenting Task Abstraction in Visualization Design with Artificial Intelligence
论文作者
论文摘要
在可视化设计过程的任务抽象阶段，包括在“设计研究”中，从业者将观察到的域目标映射到使用可视化理论的可推广的抽象任务，以便更好地理解和满足用户需求。我们认为，由于设计师的偏见和缺乏领域的背景和知识，这种手动任务抽象过程容易出现错误。在这种情况下，合作者可以在这个重要的任务抽象阶段为可视化从业人员验证和提供理智检查。但是，拥有人类的合作者并不总是可行的，并且可能存在相同的偏见和陷阱。在本文中，我们首先描述与任务抽象相关的挑战。然后，我们提出了一个概念性数字合作者：一个人工智能系统，旨在通过增强其验证和理由的任务抽象输出的能力来帮助可视化从业者。我们还讨论了设计和实施此类系统的几个实用设计挑战
In the task abstraction phase of the visualization design process, including in "design studies", a practitioner maps the observed domain goals to generalizable abstract tasks using visualization theory in order to better understand and address the users needs. We argue that this manual task abstraction process is prone to errors due to designer biases and a lack of domain background and knowledge. Under these circumstances, a collaborator can help validate and provide sanity checks to visualization practitioners during this important task abstraction stage. However, having a human collaborator is not always feasible and may be subject to the same biases and pitfalls. In this paper, we first describe the challenges associated with task abstraction. We then propose a conceptual Digital Collaborator: an artificial intelligence system that aims to help visualization practitioners by augmenting their ability to validate and reason about the output of task abstraction. We also discuss several practical design challenges of designing and implementing such systems
