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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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Detalles Bibliográficos
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
Descripción
Sumario: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.