@inproceedings{chiyah-garcia-etal-2018-explainable,
title = "Explainable Autonomy: A Study of Explanation Styles for Building Clear Mental Models",
author = "Chiyah Garcia, Francisco Javier and
Robb, David A. and
Liu, Xingkun and
Laskov, Atanas and
Patron, Pedro and
Hastie, Helen",
editor = "Krahmer, Emiel and
Gatt, Albert and
Goudbeek, Martijn",
booktitle = "Proceedings of the 11th International Conference on Natural Language Generation",
month = nov,
year = "2018",
address = "Tilburg University, The Netherlands",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6511",
doi = "10.18653/v1/W18-6511",
pages = "99--108",
abstract = "As unmanned vehicles become more autonomous, it is important to maintain a high level of transparency regarding their behaviour and how they operate. This is particularly important in remote locations where they cannot be directly observed. Here, we describe a method for generating explanations in natural language of autonomous system behaviour and reasoning. Our method involves deriving an interpretable model of autonomy through having an expert {`}speak aloud{'} and providing various levels of detail based on this model. Through an online evaluation study with operators, we show it is best to generate explanations with multiple possible reasons but tersely worded. This work has implications for designing interfaces for autonomy as well as for explainable AI and operator training.",
}
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<abstract>As unmanned vehicles become more autonomous, it is important to maintain a high level of transparency regarding their behaviour and how they operate. This is particularly important in remote locations where they cannot be directly observed. Here, we describe a method for generating explanations in natural language of autonomous system behaviour and reasoning. Our method involves deriving an interpretable model of autonomy through having an expert ‘speak aloud’ and providing various levels of detail based on this model. Through an online evaluation study with operators, we show it is best to generate explanations with multiple possible reasons but tersely worded. This work has implications for designing interfaces for autonomy as well as for explainable AI and operator training.</abstract>
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%0 Conference Proceedings
%T Explainable Autonomy: A Study of Explanation Styles for Building Clear Mental Models
%A Chiyah Garcia, Francisco Javier
%A Robb, David A.
%A Liu, Xingkun
%A Laskov, Atanas
%A Patron, Pedro
%A Hastie, Helen
%Y Krahmer, Emiel
%Y Gatt, Albert
%Y Goudbeek, Martijn
%S Proceedings of the 11th International Conference on Natural Language Generation
%D 2018
%8 November
%I Association for Computational Linguistics
%C Tilburg University, The Netherlands
%F chiyah-garcia-etal-2018-explainable
%X As unmanned vehicles become more autonomous, it is important to maintain a high level of transparency regarding their behaviour and how they operate. This is particularly important in remote locations where they cannot be directly observed. Here, we describe a method for generating explanations in natural language of autonomous system behaviour and reasoning. Our method involves deriving an interpretable model of autonomy through having an expert ‘speak aloud’ and providing various levels of detail based on this model. Through an online evaluation study with operators, we show it is best to generate explanations with multiple possible reasons but tersely worded. This work has implications for designing interfaces for autonomy as well as for explainable AI and operator training.
%R 10.18653/v1/W18-6511
%U https://aclanthology.org/W18-6511
%U https://doi.org/10.18653/v1/W18-6511
%P 99-108
Markdown (Informal)
[Explainable Autonomy: A Study of Explanation Styles for Building Clear Mental Models](https://aclanthology.org/W18-6511) (Chiyah Garcia et al., INLG 2018)
ACL