Will AI replace Mixing and Blending Machine Setters, Operators, and Tenders?
Estimated risk score: 19 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 38).
For the occupation as a whole, from ratings of its 19 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 51-9023.00 · 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: 2 of its 19 rated tasks. In O*NET’s words.
- Record operational or production data on specified forms.
- Read work orders to determine production specifications or information.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 17 of its 19 rated tasks; the first 6 are shown. In O*NET’s words.
- Add or mix chemicals or ingredients for processing, using hand tools or other devices.
- Clean and maintain equipment, using hand tools.
- Collect samples of materials or products for laboratory testing.
- Compound or process ingredients or dyes, according to formulas.
- Dump or pour specified amounts of materials into machinery or equipment.
- Examine materials, ingredients, or products visually or with hands to ensure conformance to established standards.
What the job is
Set up, operate, or tend machines to mix or blend materials, such as chemicals, tobacco, liquids, color pigments, or explosive ingredients.
Also called: Pugger, Slaker, Blunger, Reducer, Crutcher, Dip Dyer, Boss Dyer, Chem Prep.
Related jobs, estimated
- Crushing, Grinding, and Polishing Machine Setters, Operators, and Tendersestimate ±1917Very low
- Gem and Diamond Workersestimate ±1921Very low
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tendersestimate ±1916Very low
- Jewelers and Precious Stone and Metal Workersestimate ±1922Very low
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