# Grinding and Polishing Workers, Hand

> Grind, sand, or polish, using hand tools or hand-held power tools, a variety of metal, wood, stone, clay, plastic, or glass objects. Includes chippers, buffers, and finishers.

- **SOC code:** 51-9022.00
- **Canonical URL:** https://singulariki.com/roles/role-51-9022-00
- **Also known as:** Chipper, Finisher, Grinder, Polisher, Buffer, Casting Finisher, Jewelry Polisher, Knife Grinder
- **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):
- Verify quality of finished workpieces by inspecting them, comparing them to templates, measuring their dimensions, or testing them in working machinery.
- Grind, sand, clean, or polish objects or parts to correct defects or to prepare surfaces for further finishing, using hand tools and power tools.
- Measure and mark equipment, objects, or parts to ensure grinding and polishing standards are met.
- Trim, scrape, or deburr objects or parts, using chisels, scrapers, and other hand tools and equipment.
- Mark defects, such as knotholes, cracks, and splits, for repair.
- Study blueprints or layouts to determine how to lay out workpieces or saw out templates.
- Move controls to adjust, start, or stop equipment during grinding and polishing processes.
- Remove completed workpieces from equipment or work tables, using hand tools, and place workpieces in containers.
- Load and adjust workpieces onto equipment or work tables, using hand tools.
- Repair and maintain equipment, objects, or parts, using hand tools.
- Select files or other abrasives, according to materials, sizes and shapes of workpieces, amount of stock to be removed, finishes specified, and steps in finishing processes.
- Record product and processing data on specified forms.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Arm-Hand Steadiness _(ability)_
- Finger Dexterity _(ability)_
- Control Precision _(ability)_
- Near Vision _(ability)_
- Production and Processing _(knowledge)_
- Mechanical _(knowledge)_
- Manual Dexterity _(ability)_
- Quality Control Analysis _(transferable_skill)_
- Operations Monitoring _(transferable_skill)_
- Multilimb Coordination _(ability)_
- English Language _(knowledge)_
- Operation and Control _(transferable_skill)_

**Skills in demand:**
- Finger Dexterity _(Common Skill)_
- English Language _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Equipment Maintenance _(Specialized Skill)_
- Visualization _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Mathematics _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Word _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 10th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 13th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 6th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 24th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 94th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -21.2% growth (Declining); 0.8k annual openings; 11.8k → 9.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $41,690; 11,850 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

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-51-9022-00_