Will AI replace Laundry and Dry-Cleaning Workers?
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 32 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 51-6011.00 · Production
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 32 rated tasks. In O*NET’s words.
- Determine spotting procedures and proper solvents, based on fabric and stain types.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 29 of its 32 rated tasks; the first 6 are shown. In O*NET’s words.
- Clean machine filters, and lubricate equipment.
- Examine and sort into lots articles to be cleaned, according to color, fabric, dirt content, and cleaning technique required.
- Load articles into washers or dry-cleaning machines, or direct other workers to perform loading.
- Operate extractors and driers, or direct their operation.
- Remove items from washers or dry-cleaning machines, or direct other workers to do so.
- Sort and count articles removed from dryers, and fold, wrap, or hang them.
What the job is
Operate or tend washing or dry-cleaning machines to wash or dry-clean industrial or household articles, such as cloth garments, suede, leather, furs, blankets, draperies, linens, rugs, and carpets. Includes spotters and dyers of these articles.
Also called: Laundry Aide, Laundry Worker, Laundry Attendant, Laundry Housekeeper, Mater, Hatter, Puffer, Wringer.
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