From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911161897713664 |
|---|---|
| author | Jirak, Doreen Maes, Pieter Saroukanoff, Armeen van Rooy, Dirk |
| author_facet | Jirak, Doreen Maes, Pieter Saroukanoff, Armeen van Rooy, Dirk |
| contents | As autonomous technologies increasingly shape maritime operations, understanding why an AI system makes a decision becomes as crucial as what it decides. In complex and dynamic maritime environments, trust in AI depends not only on performance but also on transparency and interpretability. This paper highlights the importance of Explainable AI (XAI) as a foundation for effective human-machine teaming in the maritime domain, where informed oversight and shared understanding are essential. To support the user-centered integration of XAI, we propose a domain-specific survey designed to capture maritime professionals' perceptions of trust, usability, and explainability. Our aim is to foster awareness and guide the development of user-centric XAI systems tailored to the needs of seafarers and maritime teams. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15084 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support Jirak, Doreen Maes, Pieter Saroukanoff, Armeen van Rooy, Dirk Artificial Intelligence Computers and Society Human-Computer Interaction As autonomous technologies increasingly shape maritime operations, understanding why an AI system makes a decision becomes as crucial as what it decides. In complex and dynamic maritime environments, trust in AI depends not only on performance but also on transparency and interpretability. This paper highlights the importance of Explainable AI (XAI) as a foundation for effective human-machine teaming in the maritime domain, where informed oversight and shared understanding are essential. To support the user-centered integration of XAI, we propose a domain-specific survey designed to capture maritime professionals' perceptions of trust, usability, and explainability. Our aim is to foster awareness and guide the development of user-centric XAI systems tailored to the needs of seafarers and maritime teams. |
| title | From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support |
| topic | Artificial Intelligence Computers and Society Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.15084 |