Maritime operators emphasize trust and transparency in AI tools
Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations
Human-Computer InteractionArtificial Intelligence
Summary
Maritime professionals were asked how they feel about using AI helpers to avoid collisions at sea. The study found they generally trust and like technology but worry about losing their own skills or relying too much on AI. They want AI systems that explain their actions clearly and work reliably. The authors suggest designing AI that supports decision-making with expert oversight rather than just increasing automation.
What this means in practice
- •For maritime operations teams: Design AI tools for ship collision avoidance that build operator confidence through clear explanations and maintain expert involvement.
- •For human factors engineers: Develop AI interfaces that manage user trust and reduce technology anxiety by providing transparent and situation-aware decision support.
Authors
Doreen Jirak, Armeen Saroukanoff, Dirk van Rooy
Abstract
Maritime Autonomous Surface Ships (MASS) and AI- supported decision assistants are expected to transform maritime operations, but their safe integration depends on how maritime professionals perceive and trust such systems. This paper presents a survey study on maritime stakeholders' attitudes toward an AI-supported assistant in collision-avoidance scenarios. Participants evaluated technology anxiety, trust in automation, and explanation quality using established and adapted questionnaires, complemented by sentiment and thematic analysis of open-ended responses Results indicate a generally positive disposition toward maritime technology, no clear age-related differences in openness, stable trust across scenarios, and more scenario-sensitive, multidimensional explanation ratings. Open responses showed that participants valued support for decision-making, situation awareness, and confidence-building, while raising concerns about AI reliability, over- reliance and loss of expertise. The findings suggest that maritime AI systems should not focus solely on increasing automation or trust, but on supporting calibrated reliance through transparent, reliable, and operationally meaningful design with domain experts in the loop.