EXPOSED
This is chainsaw, cable, and log-deck work on uneven forest ground in weather — bucking, limbing, choker setting, rigging, running skidders and loaders, judging lean and hang-ups on the fly. Almost none of that is text or screen work, and field robotics cannot yet walk a steep unimproved slope and read a leaning tree. The real threat is mechanization — feller-bunchers, processor heads, and remote-controlled yarders that let three people do what eight used to — plus timber-market cycles, not language models; and there is no license or client relationship to slow that substitution down.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $39,780 → $50,840 +2.2% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-4.7%
Percentage only. The projection counts a different population from the 1,700 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Shrinking, but not obviously because of AI
The BLS projects -4.7% by 2034, but at 56/100 this work is only moderately exposed — not the profile of a job current AI can simply do. Occupations shrink for many reasons, and the score does not point at automation as this one's cause.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~400 openings a year on average, including replacing people who leave.
GoferPolerRiderRiverRoperBarkerBlazerBowmanCanterChaserChokerCutterDoggerDriverFeederFitterGopherJammerLimberPeelerPickerRafterRingerRosser
The BLS uses Logging Workers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Setting chokers on a turn of logs behind a stump, wedging a barber-chair-prone snag, and clearing a hang-up on a steep pitch are decided by what the ground and the fiber are doing that minute — an 18 rather than a 14 because even the recordkeeping side of the job (scale slips, load tickets) is a few minutes a shift, not the substance of it.
Hands-on in uncontrolled environments Nineteen because the work is performed on unimproved slope with a running saw or live cable in rain, mud, and cold, and there is no version of it done from a cab or a console — the only points off are the days spent on a landing or deck where the footing is at least graded.
No licence, no signature requirement There is no state license to cut timber; what you carry is a first-aid/CPR card and OSHA 1910.266 logging-standard training the employer is required to provide, and the citation for an unsafe felling area goes to the company, not to your name.
Meaningful discretion You call lean, escape route, notch depth, and whether a leaner comes down now or gets pulled — real calls with your own life in them, but they sit at 10 because the harvest plan, unit boundaries, and cutting prescription are handed to you by a forester or the state marking rules.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (18/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (4/20) is whether the law requires a licensed human to sign. Trust premium (5/20) is whether buyers specifically pay for a person. Judgment and accountability (10/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 19 of this occupation's 56 points (34%).
Embodiment (19/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 72/100 — SAFE.
Insurer or landowner contract terms requiring a named certified faller or rigging supervisor on site for cable/steep-slope operations before coverage attaches — already appearing in some large industrial timberland contractor prequalification and in tethered-harvesting steep-slope guidance
Task-mix shift as mechanization takes the flat, uniform, small-diameter ground: the residual manual job becomes the tier machines cannot enter — steep unimproved slopes above tether limits, large old-growth and salvage stems exceeding processor head capacity, fire-damaged and wind-thrown timber with unpredictable stored energy. This raises resistance without any new law, but shrinks headcount at the same time
State-level faller certification with personal sign-off duty: Washington L&I and Oregon OSHA already require documented qualified-faller competency for manual falling; if a state adopted a Canadian-style scheme (BC Forest Safety Council's certified/qualified faller card, where a named certified faller must assess and authorize each danger-tree/hang-up removal and carries personal accountability), the shield rises from a paperwork item to a licensed sign-off
Formal danger-tree assessment authority: if state OSHA or federal wildfire contracting (NWCG faller FAL1/FAL2 qualification, already used on incidents) becomes the required standard for hazard-tree removal on public land and post-fire salvage, the role owns a documented go/no-go call on tree lean, rot, and hang-ups under ambiguity
The limit. Task resistance and embodiment are already near ceiling — the threat is mechanization eliminating positions, not AI doing the work, so high scores here do not protect employment levels. There is no realistic trust-premium route: buyers purchase logs by volume and grade, and no end customer pays extra for hand-felled timber at any scale that matters. Licensing gains, if they came, would protect the remaining specialists' authority rather than the number of jobs.
| Eugene-Springfield, OR | 90 | $50,090 -1% |
| Albany, OR | 70 | $58,420 +15% |
| Portland-Vancouver-Hillsboro, OR-WA | 50 | $58,840 +16% |
| Salem, OR | 40 | $55,790 +10% |
| Corvallis, OR | 30 | $57,040 +12% |
| Portland-Vancouver-Hillsboro, OR-WA | 50 | $58,840 +16% |
| Albany, OR | 70 | $58,420 +15% |
| Corvallis, OR | 30 | $57,040 +12% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 56. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.