← Risk register SOC 45-4023 · reviewed 2026-08-11

Log Graders and Scalers

3,070 US workers · median $46,330/yr · Agriculture

EXPOSED

The core of this job — measuring log diameter and length, computing board-foot volume from scaling rules, and spotting rot, sweep, crook and knots to assign a grade — is exactly what optical log scanners and 3D laser/X-ray systems in modern mills already do faster and more consistently than a human with a scale stick. What holds the job together is the log yard itself: working decks, trucks and landings in mud, snow and heat, where sensors are expensive to install and calibrate, plus the scaler's role as a neutral third party whose tally settles payment between logger and mill. Small operations, portable mills, and remote landings will keep hiring humans long after big integrated mills have stopped.

10-year outlook: Employment keeps shrinking as large mills complete the shift to automated optical scaling, with the remaining jobs concentrated in third-party scaling bureaus, remote landings, and small mills.

US employment, 2019–2025-7.0%
3,3003,070 workers

Most of this decline happened after 2021 — it is not the pandemic dip.

Median pay $37,280 → $46,330 -0.6% in real terms (nominal +24.3%, less ~25% US inflation over the period)

The job count is not the verdict

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

-0.7%

Percentage only. The projection counts a different population from the 3,070 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.

Exposed, and shrinking

Both signals point the same way: the tasks are largely automatable and the BLS projects -0.7% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.

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.

~600 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

DeckerScalerDeckmanPondmanLog BuyerLog GraderLog MarkerLog ScalerLog SorterDeck ScalerPond ScalerCheck ScalerTimber BuyerLumber GraderVeneer GraderLanding ScalerDeck SpecialistLog Check ScalerScale TechnicianTimber EstimatorCompounding ScalerMaterial InspectorRaw Materials InspectorWeighing Inspection Inspector

Score — 41/100 resistance

Holding it up: embodiment (14/20). Weakest point: liability shield (6/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 6 + 14 + 6 + 7 + 8 = 41. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 6/20

Core tasks are already automatable Applying Scribner or Doyle rules to a diameter and length reading is arithmetic a scanner does at chain speed, and defect deduction for rot, sweep and catface is now trained into 3D laser and X-ray merchandisers that already grade every stem entering a large mill — which is why this sits at 6 rather than mid-band: the measurement and grading tasks themselves, not just the paperwork, are done.

Embodiment 14/20

Hands-on in uncontrolled environments You are on the deck and in the truck bay with a scale stick, paint gun and tally book, climbing loads and reaching butt ends in mud, ice and log dust where footing and rolling stems are the real hazard — that uncontrolled yard is worth 14, held short of 17+ only because much of the day is spent at a fixed scaling station or ramp rather than roaming cutblocks.

Liability shield 6/20

Certification preferred, not legally required State and bureau scaling licences (Oregon, Washington, and third-party bureaus like Northwest Log Rules) require exams and periodic check-scaling, but that is a certification a mill can substitute with a calibrated scanner and an audited sampling program — no statute makes your signature the only lawful basis for the transaction, which keeps this at 6 instead of the 11+ a truly protected licence earns.

Trust premium 7/20

Some relationship component Loggers know which scalers give a fair tally and will complain to the mill when a load comes back light, so there is a working relationship worth defending — but at 7 it is trust in the neutrality of the process, not in you personally: replace the scaler with an audited scanner and the same haulers keep delivering.

Judgment & accountability 8/20

Meaningful discretion Deciding whether a butt is sound enough to grade #2 or gets a rot deduction, and how much to dock for sweep, is a real call that moves money on every load — but it is made inside published scaling rules and grade specs with check-scale reconciliation behind you, so at 8 the discretion is bounded and reviewable rather than an ambiguous high-stakes judgment you own alone.

Confidence: medium · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, trust

How to future-proof this job

Training paths for your skill gaps: Coursera — quality control and inspection courses, auditable free free to audit · Coursera — engineering and procurement courses, auditable without paying free to audit · Apprenticeship.gov — electrical, HVAC, plumbing and fitting programs that pay while you learn paid to train · Apprenticeship.gov — paid, employer-sponsored trade apprenticeships, searchable by trade and ZIP paid to train · Apprenticeship.gov — industrial maintenance and millwright programs paid to train · OSHA Outreach Training — the 10- and 30-hour cards most employers ask for low · MIT OpenCourseWare — operations management free

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Welders, Cutters, Solderers, and Brazers EXPOSED · 62/100 · you already have ~64% of the skill profile

Skills to close: Quality Control Analysis, Equipment Selection, Installation, Repairing

Tree Trimmers and Pruners SAFE · 70/100 · you already have ~59% of the skill profile

Skills to close: Equipment Maintenance, Equipment Selection, Operation and Control, Repairing

Furniture Finishers EXPOSED · 52/100 · you already have ~56% of the skill profile

Skills to close: Repairing, Equipment Maintenance, Equipment Selection, Operations Analysis

What would move this back up — beyond any one person

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 59/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening judgment accountability +4

    Task-mix shift: once scanners handle sound, uniform sawlogs, the remaining human work concentrates on defect-heavy, cull, salvage, fire-killed and hardwood/veneer logs where grade calls on stain, ring shake, hidden rot and merchantability determination drive large price swings and are contested.

  • already happening liability shield +3

    Check-scaling audit mandates: agency or bureau rules requiring a certified human check-scale of a statistical sample of any automated scan tally before payment, as already practiced for human scalers under USFS check-scale tolerance rules.

  • plausible liability shield +5

    State-authorized third-party scaling bureaus (e.g., Oregon/Washington log scaling bureaus operating under ORS 532/state scaling statutes, or Scaling & Grading Bureau certification) tightening rules so that a state-licensed scaler must personally certify the official tally used for stumpage payment and timber tax, with machine scan output admissible only when countersigned by that licensed scaler. Similar in USFS timber sale contracts requiring certified check-scalers on national forest volume.

  • plausible trust premium +4

    Loggers' associations or timber purchase contracts specifying independent bureau scale rather than mill-owned scanner output, because mill-controlled optical scaling creates a conflict of interest in payment disputes; a publicized dispute or lawsuit over scanner-derived tallies would harden this preference.

  • plausible embodiment +2

    Growth in post-fire salvage, small-tract and portable-mill scaling at remote landings where fixed scanner installation is uneconomic, plus tribal and state trust-land volume verification done in the field.

The limit. Ceiling is low: only ~3,000 workers, and the measurement core is already commoditized inside large mills. Even with full liability and trust levers, the job likely consolidates into a small cadre of certified bureau check-scalers and defect specialists rather than recovering headcount.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 1 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Longview-Kelso, WA 30 $61,030 +32%

Best paid

Longview-Kelso, WA 30 $61,030 +32%

Percentages are against this occupation's national median of $46,330. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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 41. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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Kept current

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