# Gem and Diamond Workers

> Fabricate, finish, or evaluate the quality of gems and diamonds used in jewelry or industrial tools.

- **SOC code:** 51-9071.06
- **Canonical URL:** https://singulariki.com/roles/role-51-9071-06
- **Also known as:** Diamond Cutter, Diamond Setter, Gemologist, Lapidarist, Diamond Grader, Diamond Picker, Diamond Polisher, Diamond Sawer
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Examine gems during processing to ensure accuracy of angles and positions of cuts or bores, using magnifying glasses, loupes, or shadowgraphs.
- Assign polish, symmetry, and clarity grades to stones, according to established grading systems.
- Examine diamonds or gems to ascertain the shape, cut, and width of cut stones, or to select the cuts that will result in the biggest, best quality stones.
- Estimate wholesale and retail value of gems, following pricing guides, market fluctuations, and other relevant economic factors.
- Immerse stones in prescribed chemical solutions to determine specific gravities and key properties of gemstones or substitutes.
- Hold stones, gems, dies, or styluses against rotating plates, wheels, saws, or slitters to cut, shape, slit, grind, or polish them.
- Sort rough diamonds into categories based on shape, size, color, and quality.
- Examine gem surfaces and internal structures, using polariscopes, refractometers, microscopes, and other optical instruments, to differentiate between stones, to identify rare specimens, or to detect flaws, defects, or peculiarities affecting gem values.
- Identify and document stones' clarity characteristics, using plot diagrams.
- Secure gems or diamonds in holders, chucks, dops, lapidary sticks, or blocks for cutting, polishing, grinding, drilling, or shaping.
- Advise customers and others on the best use of gems to create attractive jewelry items.
- Measure sizes of stones' bore holes and cuts to ensure adherence to specifications, using precision measuring instruments.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Near Vision _(ability)_
- Finger Dexterity _(ability)_
- Customer and Personal Service _(knowledge)_
- Arm-Hand Steadiness _(ability)_
- Quality Control Analysis _(transferable_skill)_
- Visual Color Discrimination _(ability)_
- Problem Sensitivity _(ability)_
- Production and Processing _(knowledge)_
- Active Listening _(essential_skill)_
- Speaking _(essential_skill)_
- Deductive Reasoning _(ability)_
- Category Flexibility _(ability)_

**Skills in demand:**
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- English Language _(Common Skill)_
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Social Perceptiveness _(Common Skill)_

**Tools & technology:**
- Business accounting software
- Gem identification databases
- GemCad
- Inventory tracking software
- Jewelry design software
- Spectrophotometer analysis software
- Web browser software

## AI exposure & outlook

- **AI task-overlap index:** 39th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 45th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 42nd percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 35th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 89th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -5.5% growth (Declining); 4k annual openings; 35.1k → 33.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $49,140; 23,420 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-51-9071-06_