← Risk register SOC 51-9083 · reviewed 2026-08-11

Ophthalmic Laboratory Technicians

18,660 US workers · median $39,460/yr · Production

COOKED

The core work — reading an Rx and lab order, blocking and surfacing lenses, edging to frame trace, tinting and coating — has already been absorbed by digital surfacing labs and automated edgers, and the software side (Rx interpretation, layout calculation, job routing) is trivial for AI. What survives is hand work: mounting and drilling rimless and semi-rimless jobs, frame heating and adjustment, salvaging odd bases and high-power scripts, and final inspection against ANSI tolerance. There is no licensure requirement for the bench role in most states and the patient rarely meets the technician, so neither liability nor trust protects the job.

10-year outlook: Bench headcount keeps shrinking as prescription work consolidates into a handful of automated digital labs; the remaining jobs cluster in retail-adjacent finishing, frame repair, and equipment maintenance.

Score — 32/100 resistance

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 10 + 11 + 2 + 4 + 5 = 32.

Task resistance 10/20

Mixed — a routine tier and a judgment tier. How much of the day-to-day work current AI already does at usable quality.

Embodiment 11/20

Some physical or field component. Physical work in unpredictable environments. Robotics lags language models badly.

Liability shield 2/20

No licence, no signature requirement. Is a licensed human legally required to sign, and personally liable if it goes wrong?

Trust premium 4/20

Anonymous artifact production. Do buyers specifically pay for a human — presence, care, accountability?

Judgment & accountability 5/20

Executes defined procedures on defined inputs. Does the role own consequential calls made with incomplete information?

This verdict was revised after a second scoring. Two independent runs of the same rubric returned 34/100 and 30/100. The score above is their average, and the change of label held whichever way the rounding went — so it reflects the two runs genuinely disagreeing with the first published number, not a rounding artefact.

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

Tasks already automatable

What survives

Active moats: embodiment

How to future-proof this job

Escape hatches — adjacent fields with better verdicts

Computed from U.S. Dept. of Labor O*NET skill profiles: high overlap with what you already do, materially higher resistance score.

Model Makers, Metal and Plastic EXPOSED · 50/100 · you already have ~84% of the skill profile

Skills to close: Operations Analysis, Troubleshooting, Equipment Maintenance, Mathematics

Timing Device Assemblers and Adjusters EXPOSED · 49/100 · you already have ~81% of the skill profile

Skills to close: Troubleshooting, Repairing, Installation, Equipment Maintenance

Tool and Die Makers EXPOSED · 54/100 · you already have ~76% of the skill profile

Skills to close: Operations Analysis, Technology Design, Equipment Maintenance, Mathematics

Field report — do you do this job?

Has AI actually changed your work?

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

From people who do this job

Nobody has filed one yet. If you do this work, you know things the rubric can't see.

What has actually changed in your work?

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.