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：在人类计算机互动(HCI)中,评估HCI设计、技术、装置和系统对用户的好处的价值是常见的,讨论HCI对计算机的好处是不常见的,讨论HCI对计算机的好处是不太常见的,每一项HCI任务都使计算机能够从用户那里获得一些数据,在许多情况下,计算机收到的数据体现了人类在处理复杂问题时的知识和情报,以及/或计算机无法着手处理的一些关键信息。在本文件中,我们提出了一个信息理论框架,用以量化计算机通过HCI从用户那里获得的知识。我们对某些共同的HCI任务以及复杂的数据情报程序中的HCI任务采取了信息理论措施。我们正式确定了分析估计这类数量和从经验上衡量这些数量的方法。我们可以通过理论推理来证实HCI在数据情报工作流程中的重大但往往被低估的作用。