The Value of Interaction in Data Intelligence
Abstract
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.
Cite
@article{arxiv.1812.06051,
title = {The Value of Interaction in Data Intelligence},
author = {Min Chen},
journal= {arXiv preprint arXiv:1812.06051},
year = {2023}
}
Comments
This paper was first submitted to CHI2019 on 21 Sept. 2018. Version 2 was submitted to CHI2023 on 10 Sept. 2022. Although it was not accepted in either case, the author believes that it may still be a useful contribution to the field of HCI. Version 3 includes the correction of a typo (in Eq. 3) identified by a CHI2023 reviewer. Version 4 was submitted to TOCHI on 3 Sept 2023 and 6 Nov. 2023