Gini Loh System Tools

AI Automation Index

Will AI Replace Camera and Photographic Equipment Repairers?

Task-level automation exposure for Camera and Photographic Equipment Repairers: 15 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

27% weighted task index

15 of 15 tasks scored

Median Salary

$52,720 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

1,650 people hold this job — size, not growth

Projected 2025–35

-15.5% employment change

100 openings a year · BLS line item

Pay by state

BLS OEWS publishes 13 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$33,940 – $85,070

Highest medians

Ohio $85,070
Virginia $65,170
New Jersey $60,290
California $59,770
Arizona $59,080

Lowest medians

Texas $33,940
North Carolina $41,140
Florida $41,290
Tennessee $44,940
Kansas $46,920

State figures come from the 49-9061 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 27%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 54%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 3%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 4%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 9%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 28/100 Moderate

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

15 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 19%

3 tasks

Medium exposure (≥ 35%) 3%

1 tasks

Low exposure (below 35%) 78%

11 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Emerging & rewritten tasks

Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.

  • Revision 07/2015 · Incumbent

    Adjust or repair cameras, photographic mechanisms, or equipment such as range and view finders, shutters, light meters, or lens systems, using hand tools.

    Replaced: Adjust cameras, photographic mechanisms, or equipment such as range and view finders, shutters, light meters, or lens systems, using hand tools.

  • New 05/2025 · AI/SME

    Repair and calibrate drone cameras and equipment for aerial photography and videography.

Constituent Tasks

#8437 · Core · 15% automatable Revision

Adjust cameras, photographic mechanisms, or equipment such as range and view finders, shutters, light meters, or lens systems, using hand tools.

physical manipulation — Hands-on equipment adjustment for performance

Adjust equipment to ensure optimal performance.
#8436 · Core · 8% automatable

Disassemble equipment to gain access to defect, using hand tools.

physical manipulation — Disassembly requires hands-on tool use

Disassemble equipment for maintenance or repair.
#8440 · Core · 28% automatable

Test equipment performance, focus of lens system, diaphragm alignment, lens mounts, or film transport, using precision gauges.

physical manipulation — Hands-on mechanical testing in physical environment

Test mechanical equipment to ensure proper functioning.
#8438 · Core · 11% automatable

Clean and lubricate cameras and polish camera lenses, using cleaning materials and work aids.

physical manipulation — Physical lubrication task requiring hands and access

Clean equipment, parts, or tools to repair or maintain them in good working order. Lubricate equipment to allow proper functioning.
#8442 · Core · 75% automatable

Requisition parts or materials.

decision support — Ordering via systems automatable; human approves spend

Order materials, supplies, or equipment.
#8435 · Core · 15% automatable

Calibrate and verify accuracy of light meters, shutter diaphragm operation, or lens carriers, using timing instruments.

physical manipulation — Physical calibration to specifications

Calibrate equipment to specifications.
#8441 · Core · 18% automatable

Examine cameras, equipment, processed film, or laboratory reports to diagnose malfunction, using work aids and specifications.

visual inspection — Locating wear and damage requires physical inspection

Inspect mechanical equipment to locate damage, defects, or wear.
#8443 · Core · 71% automatable

Read and interpret engineering drawings, diagrams, instructions, or specifications to determine needed repairs, fabrication method, and operation sequence.

information retrieval — Technical reading for maintenance well handled

Read technical information needed to perform maintenance or repairs. Interpret blueprints, specifications, or diagrams to inform installation, development or operation activities.
#8439 · Core · 25% automatable

Measure parts to verify specified dimensions or settings, such as camera shutter speed or light meter reading accuracy, using measuring instruments.

physical manipulation — Physical distance measurement in field

Measure distances or dimensions.
#8444 · Core · 10% automatable

Fabricate or modify defective electronic, electrical, or mechanical components, using bench lathe, milling machine, shaper, grinder, or precision hand tools, according to specifications.

physical manipulation — Part fabrication requires physical machining and handling

Fabricate parts or components.
#20808 · Supplemental · 8% automatable

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.

physical manipulation — Electrical installation is hands-on licensed trade work

Install electrical components, equipment, or systems.
#8445 · Supplemental · 4% automatable

Assemble aircraft cameras, still or motion picture cameras, photographic equipment, or frames, using diagrams, blueprints, bench machines, hand tools, or power tools.

physical manipulation — Mechanical assembly needs hands and tools

Assemble mechanical components or machine parts.
#8447 · Supplemental · 83% automatable

Record test data and document fabrication techniques on reports.

text generation — Write test result reports from data

Document test results.
#8448 · Supplemental · 10% automatable

Lay out reference points and dimensions on parts or metal stock to be machined, using precision measuring instruments.

physical manipulation — Laying out work physically per specifications

Lay out work according to specifications.
#8449 · Supplemental · 55% automatable

Recommend design changes or upgrades of microfilming, film-developing, or photographic equipment.

decision support — Advice good; hands-on equipment context needs human

Advise others on issues related to repairs, installation, or equipment design.
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Community Sentiment

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Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
  3. 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
  4. 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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