Distributed Cognition for AI-supported Remote Operations: Challenges and Research Directions

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Main Authors: Jacobsen, Rune Møberg, Wester, Joel, Djernæs, Helena Bøjer, van Berkel, Niels
Format: Preprint
Published: 2025
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author Jacobsen, Rune Møberg
Wester, Joel
Djernæs, Helena Bøjer
van Berkel, Niels
author_facet Jacobsen, Rune Møberg
Wester, Joel
Djernæs, Helena Bøjer
van Berkel, Niels
contents This paper investigates the impact of artificial intelligence integration on remote operations, emphasising its influence on both distributed and team cognition. As remote operations increasingly rely on digital interfaces, sensors, and networked communication, AI-driven systems transform decision-making processes across domains such as air traffic control, industrial automation, and intelligent ports. However, the integration of AI introduces significant challenges, including the reconfiguration of human-AI team cognition, the need for adaptive AI memory that aligns with human distributed cognition, and the design of AI fallback operators to maintain continuity during communication disruptions. Drawing on theories of distributed and team cognition, we analyse how cognitive overload, loss of situational awareness, and impaired team coordination may arise in AI-supported environments. Based on real-world intelligent port scenarios, we propose research directions that aim to safeguard human reasoning and enhance collaborative decision-making in AI-augmented remote operations.
format Preprint
id arxiv_https___arxiv_org_abs_2504_14996
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Distributed Cognition for AI-supported Remote Operations: Challenges and Research Directions
Jacobsen, Rune Møberg
Wester, Joel
Djernæs, Helena Bøjer
van Berkel, Niels
Human-Computer Interaction
This paper investigates the impact of artificial intelligence integration on remote operations, emphasising its influence on both distributed and team cognition. As remote operations increasingly rely on digital interfaces, sensors, and networked communication, AI-driven systems transform decision-making processes across domains such as air traffic control, industrial automation, and intelligent ports. However, the integration of AI introduces significant challenges, including the reconfiguration of human-AI team cognition, the need for adaptive AI memory that aligns with human distributed cognition, and the design of AI fallback operators to maintain continuity during communication disruptions. Drawing on theories of distributed and team cognition, we analyse how cognitive overload, loss of situational awareness, and impaired team coordination may arise in AI-supported environments. Based on real-world intelligent port scenarios, we propose research directions that aim to safeguard human reasoning and enhance collaborative decision-making in AI-augmented remote operations.
title Distributed Cognition for AI-supported Remote Operations: Challenges and Research Directions
topic Human-Computer Interaction
url https://arxiv.org/abs/2504.14996