Ships' Deck Crews and Related Workers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 6 task statements that define Ships' Deck Crews and Related Workers (ISCO-08 8350) score an average of 0.14 on a 0–1 exposure scale — more exposed than about 15% of the 427 placed occupations. Roughly 0% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Not exposed band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 6 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Steering ship according to instructions;”

Scores 0.17 on the 2025 scale. The task of "Steering ship according to instructions," coded as 8350, shares similarities with tasks like "Controlling the operation of the defrosting unit" and "Supervising the loading of a specific group or types of cargo onto the appropriate vehicle." These tasks involve the need for human judgment, real-time decision-making, and physical presence, which cannot be fully automated by current Generative AI capabilities. The semantically similar tasks had adjusted scores from 0.15 to 0.235, reflecting the limited automation potential due to the need for hands-on control and decision-making in dynamic environments. Although AI can assist with navigation planning and data analysis (similar to route optimization tasks which score slightly higher due to their repetitive nature), it cannot replicate the nuanced steering required in practical maritime settings. Considering the high-income context such as Poland, with ample technological infrastructure, AI can play a supportive role in providing real-time feedback and optimizing routing decisions, but the core steering actions require human oversight and expertise. Therefore, an adjusted score of 0.2 reflects the significant human involvement needed while acknowledging some supporting capabilities from AI.

Moving fastest, 2023 → 2025

“Performing deck and hull cleaning, scraping, painting and other maintenance duties as required;”

Model capability on this task changed by +0.06 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 8350, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Sailors and Marine Oilers
• Motorboat Operators

In context

Part of the 8 - Plant and machine operators, and assemblers major group. Return to the full gradient to see how the whole group sits.

Ships' Deck Crews and Related Workers sit at the 15th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Ships' Deck Crews and Related Workers rank in the 15th percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 0% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure rose by 0.02 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Steering ship according to instructions;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Ships' Deck Crews and Related Workers". https://singulariki.com/gradient/8350-ships-deck-crews-and-related-workers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.