Journal article
Fahimeh Rajabiyazdi, G. Jamieson
IEEE International Conference on Systems, Man and Cybernetics, 2020
IEEE International Conference on Systems, Man and Cybernetics, 2020
Semantic Scholar
DBLP
DOI
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APA
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Rajabiyazdi, F., & Jamieson, G. (2020). A Review of Transparency (seeing-into) Models. IEEE International Conference on Systems, Man and Cybernetics.
Chicago/Turabian
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Rajabiyazdi, Fahimeh, and G. Jamieson. “A Review of Transparency (Seeing-into) Models.” IEEE International Conference on Systems, Man and Cybernetics (2020).
MLA
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Rajabiyazdi, Fahimeh, and G. Jamieson. “A Review of Transparency (Seeing-into) Models.” IEEE International Conference on Systems, Man and Cybernetics, 2020.
BibTeX Click to copy
@article{fahimeh2020a,
title = {A Review of Transparency (seeing-into) Models},
year = {2020},
journal = {IEEE International Conference on Systems, Man and Cybernetics},
author = {Rajabiyazdi, Fahimeh and Jamieson, G.}
}
Abstract
Humans often have difficulty accomplishing tasks in correspondence with automation with concealed inner workings. Researchers suggest that allowing humans to see into the inner workings of automation will lead to better understanding, trust in, reliance on, joint task completion with, and better situation awareness of the automation. We identified and compared four transparency models that assist researchers in designing and conducting empirical studies by guiding them on what, how, and when information on or about automation should be disclosed. The results of this review will assist researchers with understanding, identifying, and employing suitable transparency models to their applications.