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Collaborative Work with Highly Automated Marine Navigation Systems

In navigation applications, Artificial Intelligence (AI) can improve efficiency and decision making. It is not clear, however, how designers should account for human cooperation when integrating AI systems in navigation work. In a novel empirical study, we examine the transition in the maritime doma...

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Autores principales: Veitch, Erik, Dybvik, Henrikke, Steinert, Martin, Alsos, Ole Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547091/
https://www.ncbi.nlm.nih.gov/pubmed/36250043
http://dx.doi.org/10.1007/s10606-022-09450-7
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author Veitch, Erik
Dybvik, Henrikke
Steinert, Martin
Alsos, Ole Andreas
author_facet Veitch, Erik
Dybvik, Henrikke
Steinert, Martin
Alsos, Ole Andreas
author_sort Veitch, Erik
collection PubMed
description In navigation applications, Artificial Intelligence (AI) can improve efficiency and decision making. It is not clear, however, how designers should account for human cooperation when integrating AI systems in navigation work. In a novel empirical study, we examine the transition in the maritime domain towards higher levels of machine autonomy. Our method involved interviewing technology designers (n = 9) and navigators aboard two partially automated ferries (n = 5), as well as collecting field observations aboard one of the ferries. The results indicated a discrepancy between how designers construed human-AI collaboration compared to navigators’ own accounts in the field. Navigators reflected upon their role as one of ‘backup,’ defined by ad-hoc control takeovers from the automation. Designers positioned navigators ‘in the loop’ of a larger control system but discounted the role of in-situ skills and heuristic decision making in all but the most controlled takeover actions. The discrepancy shed light on how integration of AI systems may be better aligned to human cooperation in navigation. This included designing AI systems that render computational activities more visible and that incorporate social cues that articulate human work in its natural setting. Positioned within the field of AI alignment research, the main contribution is a formulation of human-AI interaction design insights for future navigation and control room work.
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spelling pubmed-95470912022-10-11 Collaborative Work with Highly Automated Marine Navigation Systems Veitch, Erik Dybvik, Henrikke Steinert, Martin Alsos, Ole Andreas Comput Support Coop Work Research Article In navigation applications, Artificial Intelligence (AI) can improve efficiency and decision making. It is not clear, however, how designers should account for human cooperation when integrating AI systems in navigation work. In a novel empirical study, we examine the transition in the maritime domain towards higher levels of machine autonomy. Our method involved interviewing technology designers (n = 9) and navigators aboard two partially automated ferries (n = 5), as well as collecting field observations aboard one of the ferries. The results indicated a discrepancy between how designers construed human-AI collaboration compared to navigators’ own accounts in the field. Navigators reflected upon their role as one of ‘backup,’ defined by ad-hoc control takeovers from the automation. Designers positioned navigators ‘in the loop’ of a larger control system but discounted the role of in-situ skills and heuristic decision making in all but the most controlled takeover actions. The discrepancy shed light on how integration of AI systems may be better aligned to human cooperation in navigation. This included designing AI systems that render computational activities more visible and that incorporate social cues that articulate human work in its natural setting. Positioned within the field of AI alignment research, the main contribution is a formulation of human-AI interaction design insights for future navigation and control room work. Springer Netherlands 2022-10-08 /pmc/articles/PMC9547091/ /pubmed/36250043 http://dx.doi.org/10.1007/s10606-022-09450-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Veitch, Erik
Dybvik, Henrikke
Steinert, Martin
Alsos, Ole Andreas
Collaborative Work with Highly Automated Marine Navigation Systems
title Collaborative Work with Highly Automated Marine Navigation Systems
title_full Collaborative Work with Highly Automated Marine Navigation Systems
title_fullStr Collaborative Work with Highly Automated Marine Navigation Systems
title_full_unstemmed Collaborative Work with Highly Automated Marine Navigation Systems
title_short Collaborative Work with Highly Automated Marine Navigation Systems
title_sort collaborative work with highly automated marine navigation systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547091/
https://www.ncbi.nlm.nih.gov/pubmed/36250043
http://dx.doi.org/10.1007/s10606-022-09450-7
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