Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations
A survey of maritime professionals finds positive but scenario-sensitive attitudes toward AI collision-avoidance assistants, urging design for calibrated reliance.
The study surveyed maritime stakeholders on attitudes toward AI-supported collision-avoidance assistants for Maritime Autonomous Surface Ships, measuring technology anxiety, trust in automation, and explanation quality with established questionnaires plus thematic analysis of open responses. Results show generally positive disposition, no clear age-related openness differences, stable trust across scenarios, and multidimensional, scenario-sensitive explanation ratings. Participants valued decision support and situation awareness but worried about AI reliability, over-reliance, and skill loss; the authors recommend designing for calibrated reliance with domain experts in the loop rather than maximizing automation or trust.
- Survey of maritime professionals on AI collision-avoidance assistants using validated scales.
- Generally positive attitudes; no clear age-related differences in openness.
- Explanation quality ratings were scenario-sensitive and multidimensional.
- Concerns raised about AI reliability, over-reliance, and loss of expertise.
- Recommendation: support calibrated reliance through transparent, operationally meaningful design.
Full article155 words · extracted from arxiv.org · click to collapse
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.
Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.11805