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Discovering the Sweet Spot of Human-Computer Configurations: A Case Study in Information Extraction

Level of Automation in the ICV Process

Level of Automation in the ICV Process
Image Credit: Maximilian Mackeprang

Maximilian Mackeprang, Claudia Müller-Birn, Maximilian Timo Stauss – 2019

Interactive intelligent systems, i.e., interactive systems that employ AI technologies, are currently present in many parts of our social, public and political life. An issue reoccurring often in the development of these systems is the question regarding the level of appropriate human and computer contributions. Engineers and designers lack a way of systematically defining and delimiting possible options for designing such systems in terms of levels of automation. In this paper, we propose, apply and reflect on a method for human-computer configuration design. It supports the systematic investigation of the design space for developing an interactive intelligent system. We illustrate our method with a use case in the context of collaborative ideation. Here, we developed a tool for information extraction from idea content. A challenge was to find the right level of algorithmic support, whereby the quality of the information extraction should be as high as possible, but, at the same time, the human effort should be low. Such contradicting goals are often an issue in system development; thus, our method proposed helped us to conceptualize and explore the design space. Based on a critical reflection on our method application, we want to offer a complementary perspective to the value-centered design of interactive intelligent systems. Our overarching goal is to contribute to the design of so-called hybrid systems where humans and computers are partners.

Title
Discovering the Sweet Spot of Human-Computer Configurations: A Case Study in Information Extraction
Author
Publisher
ACM
Location
New York
Keywords
Ideas to Market, I2M
Date
2019
Identifier
DOI: 10.1145/3359297
Source(s)
Appeared in
Proceedings of the ACM on Human-Computer Interaction
Type
Text
BibTeX Code
@article{mackeprang_discovering_2019,
author = {Mackeprang, Maximilian and M\"{u}ller-Birn, Claudia and Stauss, Maximilian Timo},
title = {Discovering the Sweet Spot of Human-Computer Configurations: A Case Study in Information Extraction},
year = {2019},
issue_date = {November 2019},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {3},
number = {CSCW},
url = {https://doi.org/10.1145/3359297},
doi = {10.1145/3359297},
journal = {Proc. ACM Hum.-Comput. Interact.},
month = {nov},
articleno = {195},
numpages = {30},
keywords = {large scale ideation, human-computer collaboration, semantic annotation}
}