Will AI replace Fence Erectors?
Estimated risk score: 8 out of 100
Very low replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (0 to 27).
For the occupation as a whole, from ratings of its 20 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 47-4031.00 · Construction and Extraction
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 1 of its 20 rated tasks. In O*NET’s words.
- Discuss fencing needs with customers, and estimate and quote prices.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 19 of its 20 rated tasks; the first 6 are shown. In O*NET’s words.
- Align posts, by lines or sighting, and verify vertical alignment of posts, using plumb bobs or spirit levels.
- Assemble gates, and fasten gates into position, using hand tools.
- Attach fence rail supports to posts, using hammers and pliers.
- Attach rails or tension wire along bottoms of posts to form fencing frames.
- Complete top fence rails of metal fences by connecting tube sections, using metal sleeves.
- Construct and repair barriers, retaining walls, trellises, and other types of fences, walls, and gates.
What the job is
Erect and repair fences and fence gates, using hand and power tools.
Also called: Fence Builder, Fence Laborer, Fence Installer, Gate Tech, Fence Tech, Fence Mechanic, Fence Repairman, Fence Contractor.
Closest jobs we score by hand
In the same field (Construction and Extraction). Different jobs, each scored by a person.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate