Fishing and hunting workers

Record daily activities in ship's log

Recording standardized information about location, catch volumes, weather, and activities is highly structured data entry that AI could largely automate through integration with vessel sensors, GPS, and catch monitoring systems. Voice-to-text or automated logging could handle most entries with minimal human review.

BLS evidence: Fishing boat captains 'record daily activities in the ship's log.'

Plan fishing operations including species, location, and method of capture

AI can analyze historical catch data, weather patterns, migration patterns, and regulatory information to suggest optimal fishing plans. However, experienced fishers integrate tacit knowledge about local conditions, vessel capabilities, crew skills, and market factors that AI cannot fully capture, requiring human decision-making with AI assistance.

BLS evidence: Fishing boat captains 'plan and oversee the fishing operation including the species of fish to be caught, the location of the best fishing grounds, the method of capture, trip length, and sale of the catch.'

Measure fish to ensure legal size and return illegal catches

AI vision systems could measure fish and identify species with reasonable accuracy, potentially flagging undersized catches. However, the physical handling of live, moving fish on a wet deck and the judgment calls about borderline cases mean humans still do most of the work, though AI could provide substantial assistance.

BLS evidence: Fishers 'measure fish to ensure that they are of legal size' and 'return undesirable or illegal catches to the water.'

Sort and pack the catch with ice and freezing methods

AI vision systems could assist with sorting by species and size, but the physical manipulation of slippery fish in cramped, moving spaces and the packing process require dexterity and adaptability that current robotics cannot match. Humans must execute most of the physical work.

BLS evidence: Workers 'sort, pack, and store the catch in holds with ice and other freezing methods.'

Steer vessels and operate navigational instruments

While autopilot systems exist for vessels, steering in active fishing operations requires constant adaptation to weather, obstacles, gear deployment, and crew safety in ways that demand human judgment. Navigation instruments can be AI-assisted but the dynamic decision-making in variable conditions keeps this largely human.

BLS evidence: Fishers 'steer vessels and operate navigational instruments' and captains 'use electronic navigational equipment, including Global Positioning System (GPS) instruments.'

Supervise crew and coordinate movement of catch loads

Supervising crew on a fishing vessel requires real-time coordination of people working in dangerous, dynamic conditions, reading body language and morale, and making safety-critical decisions. Coordinating catch loads involves physical oversight in cramped spaces. This remains fundamentally human work.

BLS evidence: Captains 'supervise the crew' and workers 'signal other workers to move, hoist, and position loads of the catch.'

Maintain engines, fishing gear, and onboard equipment by making minor repairs

Requires diagnosing mechanical problems in harsh marine environments, accessing cramped engine spaces, and performing repairs with tools in unstable conditions. While AI could provide diagnostic guidance, the physical repair work in these non-standard settings is beyond current robotic capabilities.

BLS evidence: Fishers 'maintain engines, fishing gear, and other onboard equipment by making minor repairs.'

Locate fish or wild animals using fish-finding or animal-finding equipment

While AI can process sonar and sensor data, the task requires operating equipment in unpredictable marine environments, interpreting real-time environmental conditions, and making dynamic adjustments based on weather, currents, and vessel movement that current systems cannot reliably handle autonomously.

BLS evidence: Fishers 'locate fish with the use of fish-finding equipment' and hunters 'locate wild animals with the use of animal-finding equipment.'

Catch fish using nets, traps, lines, or dredges

This is highly physical work requiring fine and gross motor control in chaotic, wet, moving environments with unpredictable conditions. Current robotics cannot match the dexterity, adaptability, and real-time problem-solving needed to deploy and retrieve nets, set traps, or manage lines on a working vessel.

BLS evidence: Fishers 'use pots and traps to catch fish or shellfish' and 'guide nets, traps, and lines onto vessels.'

Catch or kill wild animals using weapons or traps

Requires tracking and engaging moving targets in unstructured outdoor environments, operating weapons or traps across varied terrain and conditions, and making split-second decisions about safety and legality. AI-enabled robotics are nowhere near capable of this level of physical autonomy in wilderness settings.

BLS evidence: Hunters and trappers 'catch wild animals with weapons, such as rifles or bows, or with traps, such as snares.'