In human computer interaction (HCI), it is common to evaluate the value of HCI designs, techniques, devices, and systems in terms of their benefit to users. It is less common to discuss the benefit of HCI to computers. Every HCI task allows a computer to receive some data from the user. In many situations, the data received by the computer embodies human knowledge and intelligence in handling complex problems, and/or some critical information without which the computer cannot proceed. In this paper, we present an information-theoretic framework for quantifying the knowledge received by the computer from its users via HCI. We apply information-theoretic measures to some common HCI tasks as well as HCI tasks in complex data intelligence processes. We formalize the methods for estimating such quantities analytically and measuring them empirically. Using theoretical reasoning, we can confirm the significant but often undervalued role of HCI in data intelligence workflows.

翻译：在人机交互（HCI）领域，通常根据HCI设计、技术、设备和系统对用户的益处来评估其价值，但很少讨论HCI对计算机的益处。每项HCI任务都使计算机能够从用户处接收数据。在许多情况下，计算机接收的数据蕴含了人类处理复杂问题的知识智慧，以及计算机无法继续运行所需的关键信息。本文提出了一种信息论框架，用于量化计算机通过HCI从用户处获取的知识。我们将信息论度量应用于常见HCI任务及复杂数据智能流程中的HCI任务，形式化了通过理论分析估算这些量及通过实证测量其数值的方法。通过理论推演，我们证实了HCI在数据智能工作流中具有重要但常被低估的作用。