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Skilled agricultural, forestry and fishery workers · code 6224

Hunters and trappers

Hunters and trappers catch and kill mammals, birds or reptiles mainly for meat, skin, feathers and other products for sale or delivery on a regular basis to wholesale buyers, marketing organizations or at markets. Tasks include - (a) setting traps to catch mammals, birds or reptiles; (b) killing trapped or free mammals, birds or reptiles with firearms or other weapons; (c) skinning and otherwise treating killed mammals, birds or reptiles to obtain desired products for sale or delivery; (d) delivering or selling trapped live mammals, birds or reptiles; (e) repairing and maintaining equipment. Examples of the occupations classified here: - Fur trapper - Seal hunter

None of this job's tasks scored high enough to count. It ranks 4 of 427 for holding up against AI.

Also known as

  • hunter

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

91
Holds up
against AI Not Exposed

AI could take on 9 of 100, on average
so it holds up at 100 − 9 = 91

That's the whole sum, and you can check it against the ILO's study.

68.9
How hands-on
out of 100

From O*NET, averaged across 2 US jobs

38.8
How fiddly
and cramped

finger skill 40.2 · hand skill 40.2 · cramped spaces 35.9 · averaged

Kind of hands-on work · hands-on 50+ · fiddly under 39.4 Hands-on, less fiddly work

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.7-work-setting measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

This number is probably too high

This score only looks at AI tools like chatbots. It doesn't look at robots at all — and this job rates 68.9 out of 100 for how hands-on it is, which is exactly where robots come in.

Have a look at the tasks below and judge for yourself. The ILO scored them low because a chatbot can't do them. Whether a machine with hands could is a different question, and we can't answer it yet.

The tasks behind the score

The score is the average of these. A job is really a bundle of tasks, and an average can hide how uneven that bundle is.

The task AI could do most of scores 13.8, while the average is 9. A big gap means some of this job is wide open to AI and some of it barely at all. That's quite different from a job where everything sits somewhere in the middle, even when the averages match.

  1. 13.8

    Repairing and maintaining equipment.

    Very Low
  2. 10.4

    Delivering or selling trapped live mammals, birds or reptiles

    Very Low
  3. 8.5

    Skinning and otherwise treating killed mammals, birds or reptiles to obtain desired products for sale or delivery

    Very Low
  4. 6.3

    Setting traps to catch mammals, birds or reptiles

    Very Low
  5. 6

    Killing trapped or free mammals, birds or reptiles with firearms or other weapons

    Very Low

5 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.7-work-setting

Compared with similar jobs

There are 18 jobs in the “Skilled agricultural, forestry and fishery workers” group, averaging 83.2. This one is above that.