# Model Makers, Wood

> Construct full-size and scale wooden precision models of products. Includes wood jig builders and loft workers.

- **SOC code:** 51-7031.00
- **Canonical URL:** https://singulariki.com/roles/role-51-7031-00
- **Also known as:** Craftsman, Model Maker, Sample Builder, Sample Maker, Builder, Jig Maker, Model Builder, Product Development Carpenter
- **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):
- Read blueprints, drawings, or written specifications, and consult with designers to determine sizes and shapes of patterns and required machine setups.
- Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, screws, and other fasteners.
- Verify dimensions and contours of models during hand-forming processes, using templates and measuring devices.
- Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.
- Construct wooden models, patterns, templates, full scale mock-ups, and molds for parts of products and production tools.
- Plan, lay out, and draw outlines of units, sectional patterns, or full-scale mock-ups of products.
- Select wooden stock, determine layouts, and mark layouts of parts on stock, using precision equipment such as scribers, squares, and protractors.
- Mark identifying information on patterns, parts, and templates to indicate assembly methods and details.
- Set up, operate, and adjust a variety of woodworking machines such as bandsaws and planers to cut and shape sections, parts, and patterns, according to specifications.
- Maintain pattern records for reference.
- Build jigs that can be used as guides for assembling oversized or special types of box shooks.
- Issue patterns to designated machine operators.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Production and Processing _(knowledge)_
- Near Vision _(ability)_
- Design _(knowledge)_
- Arm-Hand Steadiness _(ability)_
- Finger Dexterity _(ability)_
- Building and Construction _(knowledge)_
- Manual Dexterity _(ability)_
- Control Precision _(ability)_
- Engineering and Technology _(knowledge)_
- Mathematics _(knowledge)_
- Oral Comprehension _(ability)_
- Problem Sensitivity _(ability)_

**Skills in demand:**
- Finger Dexterity _(Common Skill)_
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Inductive Reasoning _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Dassault Systemes CATIA
- Siemens NX

## AI exposure & outlook

- **AI task-overlap index:** 31st percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 28th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 27th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 45th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 91st percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -4.5% growth (Declining); 0.1k annual openings; 0.9k → 0.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $51,850; 360 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Autonomy median:** 2.0 (higher = AI acts more independently).

**Tasks most handed to AI here:**
- Verify dimensions and contours of models during hand-forming processes, using templates and measuring devices. _(0.4% of measured AI use)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me verify dimensions and contours of models during hand-forming processes, using templates and measuring devices.

## 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/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **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-51-7031-00_