EXPOSED
The core work — disassembling a lens barrel, cleaning shutter mechanisms, replacing ribbon cables under a stereo microscope, recalibrating autofocus and sensor alignment — is fine-motor bench work that no current robot performs on unpredictable, decades-varied hardware. AI erodes only the paperwork edges: intake diagnostics from customer descriptions, parts lookup, service manual search, repair estimates. The real threat to this 1,650-person occupation is not AI but sealed electronics, cheap replacement, and phone cameras shrinking the repairable installed base.
Part 2020 shock, part continued decline in the years since.
Median pay $38,880 → $52,720 +8.5% 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
-15.1%
Percentage only. The projection counts a different population from the 1,650 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 -15.1% by 2034, but at 49/100 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.
~200 openings a year on average, including replacing people who leave.
RepairmanCamera MechanicCamera RepairerCamera MachinistCamera RepairmanRepair CameramanCamera TechnicianRepair TechnicianPhoto TechnologistCamera Tuning EngineerField Service EngineerCamera Repair SpecialistCamera Repair TechnicianDigital Service EngineerLathe Machine TechnicianDigital Camera TechnicianPhotographic TechnologistPhoto Equipment TechnicianCamera Prototyping EngineerDigital X-Ray Service EngineerSurveillance Camera TechnicianPhotographic Equipment MechanicPhotography Equipment TechnicianPhotographic Equipment Technician
Holding it up: task resistance . Weakest point: liability shield .
Tasks largely resist digitisation Collimating a rangefinder, re-greasing a helicoid, or reflowing a flex connector on a 1978 body with no service manual requires touch feedback and improvisation on parts that vary machine-to-machine, which is why this sits at 15 rather than higher — intake triage, parts sourcing, and estimate writing genuinely do move to software.
Hands-on in uncontrolled environments You work at a bench under a microscope with tweezers, spanners, and a soldering iron on objects whose internal geometry you discover as you open them, but it is a lit, static, dust-controlled indoor bench rather than a customer's roof or a factory floor, which caps this below the 18-20 field-service range.
No licence, no signature requirement There is no state licence, no board exam, and no statutory certification to repair a camera — manufacturer authorization (Canon, Nikon, Sony service programs) is a commercial contract that gates parts access, not a legal barrier that stops anyone else from opening a shop.
Meaningful discretion You decide whether a corroded main board is worth replacing against the used-body price, whether a shutter count means imminent failure, and when to tell a customer to stop spending — real calls with money attached, but the procedures for cleaning a mirror box or adjusting back-focus are established and the downside is a refund, not injury.
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 (15/20 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 (1/20) is whether the law requires a licensed human to sign. Trust premium (9/20) is whether buyers specifically pay for a person. Judgment and accountability (9/20) 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 49 points (39%).
Embodiment (15/20) 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.
Motorcycle Mechanics SAFE
Medical Equipment Repairers EXPOSED
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 63/100, still EXPOSED.
Continued growth of the film/analog revival and vintage-lens market pushes the repairable base toward mechanical bodies (Nikon F, Hasselblad, Leica) with no parts availability, forcing machining and hand-fitting of replacement parts rather than module swaps — bench work that is less scriptable, not more
If right-to-repair laws (Minnesota HB1032, EU Ecodesign/repairability index for cameras) force manufacturers to release calibration tools, firmware unlocks and parts to independents, sealed-unit swaps become genuine component-level repairs again, and the surviving work is the diagnostic/judgment tier after AI absorbs intake and manual lookup
Named-technician authorization programs — Leica, Hasselblad, or cine-rental houses certifying specific individuals for sensor-plane and PL-mount collimation, where the customer's insurer or production accepts only that named person's calibration certificate
Repair-vs-replace and irreversible-disassembly calls on high-value items (a $40k cine lens, a museum-collection camera) where a wrong call destroys the object; conservation bodies (AIC) extending documented-treatment standards to photographic apparatus would formalize this ownership
Cinema rental and broadcast insurers requiring a signed calibration/back-focus certificate from a designated technician before lens packages go on an insured production
The limit. The binding constraint is not AI capability but the shrinking repairable installed base — 1,650 workers against sealed electronics and cheap replacement. Every lever above raises resistance per surviving job while the number of jobs continues to fall; a higher score here does not mean more employment.
| New York-Newark-Jersey City, NY-NJ | 60 | $60,290 +14% |
| Atlanta-Sandy Springs-Roswell, GA | 40 | $49,960 -5% |
| New York-Newark-Jersey City, NY-NJ | 60 | $60,290 +14% |
| Atlanta-Sandy Springs-Roswell, GA | 40 | $49,960 -5% |
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 49. 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.