# Sailors and Marine Oilers

> Stand watch to look for obstructions in path of vessel, measure water depth, turn wheel on bridge, or use emergency equipment as directed by captain, mate, or pilot. Break out, rig, overhaul, and store cargo-handling gear, stationary rigging, and running gear. Perform a variety of maintenance tasks to preserve the painted surface of the ship and to maintain line and ship equipment. Must hold government-issued certification and tankerman certification when working aboard liquid-carrying vessels. Includes able seamen and ordinary seamen.

- **SOC code:** 53-5011.00
- **Canonical URL:** https://singulariki.com/roles/role-53-5011-00
- **Also known as:** Able Bodied Seaman (AB Seaman), Able Seaman, Deck Hand, Deckhand, Able Bodied Watchman (AB Watchman), Boat Crew Deck Hand, Bosun, Deckhand Engineer
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Tie barges together into tow units for tugboats to handle, inspecting barges periodically during voyages and disconnecting them when destinations are reached.
- Attach hoses and operate pumps to transfer substances to and from liquid cargo tanks.
- Handle lines to moor vessels to wharfs, to tie up vessels to other vessels, or to rig towing lines.
- Read pressure and temperature gauges or displays and record data in engineering logs.
- Stand watch in ships' bows or bridge wings to look for obstructions in a ship's path or to locate navigational aids, such as buoys or lighthouses.
- Maintain government-issued certifications, as required.
- Examine machinery to verify specified pressures or lubricant flows.
- Maintain a ship's engines under the direction of the ship's engineering officers.
- Break out, rig, and stow cargo-handling gear, stationary rigging, or running gear.
- Lubricate machinery, equipment, or engine parts, such as gears, shafts, or bearings.
- Stand by wheels when ships are on automatic pilot, and verify accuracy of courses, using magnetic compasses.
- Steer ships under the direction of commanders or navigating officers or direct helmsmen to steer, following designated courses.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Far Vision _(ability)_
- Operations Monitoring _(transferable_skill)_
- Control Precision _(ability)_
- Oral Comprehension _(ability)_
- Problem Sensitivity _(ability)_
- Perceptual Speed _(ability)_
- Depth Perception _(ability)_
- Operation and Control _(transferable_skill)_
- Arm-Hand Steadiness _(ability)_
- Multilimb Coordination _(ability)_
- Auditory Attention _(ability)_
- Manual Dexterity _(ability)_

**Skills in demand:**
- Depth Perception _(Common Skill)_
- Visualization _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Time Management _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Computerized maintenance management system CMMS
- KNMI TurboWin
- Kongsberg Maritime K-Log Deck Logbook
- Log book software

## AI exposure & outlook

- **AI task-overlap index:** 8th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 12th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 9th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 15th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 68th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 2.3% growth (About average); 3.9k annual openings; 32.1k → 32.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $49,610; 31,360 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-53-5011-00_