AI exposure: Camera and Photographic Equipment Repairers
Repair and adjust cameras and photographic equipment, including commercial video and motion picture camera equipment.
Reading this score
computedAt 18.5% of weighted task load, Camera and Photographic Equipment Repairers sits at the 32th percentile, below the point where a job's centre of gravity has moved. 72.0% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.
What holds the line here is embodiment. Across this occupation's 15 tasks it averages 2.33 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Requisition parts or materials, at 80.0%. The least is Assemble aircraft cameras, still or motion picture cameras, photographic equipment, or frames, at 0.0%. A gap of 80.0% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within installation, maintenance and repair occupations, this one is more exposed than most. The median across the 50 roles in the group is 12.8%, and only 12 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.
What would move this score. Of 15 tasks, 4 are currently banded exposed, 0 assisted and 11 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 1.23 | 0-4 |
| Embodiment | 2.33 | 0-3 |
| Presence | 0.30 | 0-3 |
| Accountability | 0.70 | 0-3 |
| Context | 1.17 | 0-3 |
| Verification cost | 1.23 | 0-3 |
Task by task
15 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Requisition parts or materials. | 80.0% | 20.0% | 0.0% | 4.14 | exposed |
| Record test data and document fabrication techniques on reports. | 73.3% | 26.7% | 0.0% | 3.34 | exposed |
| Recommend design changes or upgrades of microfilming, film-developing, or photographic equipment. | 40.0% | 35.0% | 25.0% | 2.33 | exposed |
| Read and interpret engineering drawings, diagrams, instructions, or specifications to determine needed repairs, fabrication method, and operation sequence. | 39.6% | 22.9% | 37.5% | 3.99 | exposed |
| Lay out reference points and dimensions on parts or metal stock to be machined, using precision measuring instruments. | 16.7% | 8.3% | 75.0% | 2.82 | untouched |
| Adjust cameras, photographic mechanisms, or equipment such as range and view finders, shutters, light meters, or lens systems, using hand tools. | 15.0% | 10.0% | 75.0% | 4.45 | untouched |
| Test equipment performance, focus of lens system, diaphragm alignment, lens mounts, or film transport, using precision gauges. | 15.0% | 10.0% | 75.0% | 4.37 | untouched |
| Calibrate and verify accuracy of light meters, shutter diaphragm operation, or lens carriers, using timing instruments. | 11.7% | 13.3% | 75.0% | 4.10 | untouched |
| Examine cameras, equipment, processed film, or laboratory reports to diagnose malfunction, using work aids and specifications. | 10.0% | 15.0% | 75.0% | 4.05 | untouched |
| Disassemble equipment to gain access to defect, using hand tools. | 0.0% | 0.0% | 100.0% | 4.40 | untouched |
| Clean and lubricate cameras and polish camera lenses, using cleaning materials and work aids. | 0.0% | 0.0% | 100.0% | 4.34 | untouched |
| Measure parts to verify specified dimensions or settings, such as camera shutter speed or light meter reading accuracy, using measuring instruments. | 0.0% | 0.0% | 100.0% | 3.97 | untouched |
| Fabricate or modify defective electronic, electrical, or mechanical components, using bench lathe, milling machine, shaper, grinder, or precision hand tools, according to specifications. | 0.0% | 0.0% | 100.0% | 3.55 | untouched |
| Install electrical assemblies and wiring in aircraft camera housings and memory cards or film in cameras, following blueprints and using hand tools and soldering equipment. | 0.0% | 0.0% | 100.0% | 4.31 | untouched |
| Assemble aircraft cameras, still or motion picture cameras, photographic equipment, or frames, using diagrams, blueprints, bench machines, hand tools, or power tools. | 0.0% | 0.0% | 100.0% | 3.66 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.