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Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work

The roles of human operators are changing due to increased intelligence and autonomy of computer systems. Humans will interact with systems at a more overarching level or only in specific situations. This involves learning new practices and changing habitual ways of thinking and acting, including re...

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Autores principales: Lundberg, Jonas, Arvola, Mattias, Palmerius, Karljohan Lundin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329038/
https://www.ncbi.nlm.nih.gov/pubmed/34355166
http://dx.doi.org/10.3389/frai.2021.704082
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author Lundberg, Jonas
Arvola, Mattias
Palmerius, Karljohan Lundin
author_facet Lundberg, Jonas
Arvola, Mattias
Palmerius, Karljohan Lundin
author_sort Lundberg, Jonas
collection PubMed
description The roles of human operators are changing due to increased intelligence and autonomy of computer systems. Humans will interact with systems at a more overarching level or only in specific situations. This involves learning new practices and changing habitual ways of thinking and acting, including reconsidering human autonomy in relation to autonomous systems. This paper describes a design case of a future autonomous management system for drone traffic in cities in a key scenario we call The Computer in Brussels. Our approach to designing for human collaboration with autonomous systems builds on scenario-based design and cognitive work analysis facilitated by computer simulations. We use a temporal method, called the Joint Control Framework to describe human and automated work in an abstraction hierarchy labeled Levels of Autonomy in Cognitive Control. We use the Score notation to analyze patterns of temporal developments that span levels of the abstraction hierarchy and discuss implications for human-automation communication in traffic management. We discuss how autonomy at a lower level can prevent autonomy on higher levels, and vice versa. We also discuss the temporal nature of autonomy in minute-to-minute operative work. Our conclusion is that human autonomy in relation to autonomous systems is based on fundamental trade-offs between technological opportunities to automate and values of what human actors find meaningful.
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spelling pubmed-83290382021-08-04 Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work Lundberg, Jonas Arvola, Mattias Palmerius, Karljohan Lundin Front Artif Intell Artificial Intelligence The roles of human operators are changing due to increased intelligence and autonomy of computer systems. Humans will interact with systems at a more overarching level or only in specific situations. This involves learning new practices and changing habitual ways of thinking and acting, including reconsidering human autonomy in relation to autonomous systems. This paper describes a design case of a future autonomous management system for drone traffic in cities in a key scenario we call The Computer in Brussels. Our approach to designing for human collaboration with autonomous systems builds on scenario-based design and cognitive work analysis facilitated by computer simulations. We use a temporal method, called the Joint Control Framework to describe human and automated work in an abstraction hierarchy labeled Levels of Autonomy in Cognitive Control. We use the Score notation to analyze patterns of temporal developments that span levels of the abstraction hierarchy and discuss implications for human-automation communication in traffic management. We discuss how autonomy at a lower level can prevent autonomy on higher levels, and vice versa. We also discuss the temporal nature of autonomy in minute-to-minute operative work. Our conclusion is that human autonomy in relation to autonomous systems is based on fundamental trade-offs between technological opportunities to automate and values of what human actors find meaningful. Frontiers Media S.A. 2021-07-20 /pmc/articles/PMC8329038/ /pubmed/34355166 http://dx.doi.org/10.3389/frai.2021.704082 Text en Copyright © 2021 Lundberg, Arvola and Palmerius. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Lundberg, Jonas
Arvola, Mattias
Palmerius, Karljohan Lundin
Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work
title Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work
title_full Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work
title_fullStr Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work
title_full_unstemmed Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work
title_short Human Autonomy in Future Drone Traffic: Joint Human–AI Control in Temporal Cognitive Work
title_sort human autonomy in future drone traffic: joint human–ai control in temporal cognitive work
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329038/
https://www.ncbi.nlm.nih.gov/pubmed/34355166
http://dx.doi.org/10.3389/frai.2021.704082
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