Will AI replace Paperhangers?
Estimated risk score: 6 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 25).
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 47-2142.00 · 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: 0 of its 20 rated tasks. In O*NET’s words.
None of its rated tasks.
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.
- Apply adhesives to the backs of paper strips, using brushes, or dunk strips of prepasted wallcovering in water, wiping off any excess adhesive.
- Apply sizing to seal surfaces and maximize adhesion of coverings to surfaces.
- Apply thinned glue to waterproof porous surfaces, using brushes, rollers, or pasting machines.
- Check finished wallcoverings for proper alignment, pattern matching, and neatness of seams.
- Cover interior walls and ceilings of rooms with decorative wallpaper or fabric, using hand tools.
- Fill holes, cracks, and other surface imperfections preparatory to covering surfaces.
What the job is
Cover interior walls or ceilings of rooms with decorative wallpaper or fabric, or attach advertising posters on surfaces such as walls and billboards. May remove old materials or prepare surfaces to be papered.
Also called: Bill Poster, Paper Hanger, Wallpaper Hanger, Poster, Wallpaperer, Vinyl Hanger, Billboard Poster, Bill Board Poster.
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