ISCO 3434 · O*NET 35-1011.00 · codes unverified
Chef
Robots have been cooking in labs for a decade. A commercial kitchen at seven on a Friday is a different problem entirely.
The shape of the work holds. The admin around it thins out considerably.
Scale, labels and thresholds are provisional. This is open question Q-02.
8 of 20 in the launch set
How the score is made
Four declared inputs, never collapsed into one number. Assistance is kept apart from outright automation, because a tool that makes you faster and a tool that replaces you are not the same event. Physical work counts as shelter only to the extent robotics cannot reach it.
The full method is written out, including what it cannot tell you.
Note on this occupation Placeholder values. The robotics number here is higher than for the trades because commercial kitchens are far more structured environments than a domestic crawlspace.
- Assisted
- 30
- Done outright
- 14
- Physical
- 84
- Robotics reach
- 28
Higher is generally good news. It means more of the work gets faster without the work going away.
This is the number most people mean when they say exposure. It is kept separate from assistance on purpose.
Protective only for as long as robotics cannot reach it. Read this one next to the robotics number, never alone.
Low reach turns physical work into shelter. High reach turns it into the main exposure.
placeholder Working Paper 140, Generative AI and Jobs 2025 index O*NET 31.0 Global Automation Atlas 2026 release data 0.1-placeholder
What changes
Tasks moving to machines, in whole or in part.
- Ordering, stock control and costing a menu.
- Rostering and compliance records.
- Recipe development first drafts and allergen checking.
What stays human
Tasks that need a person, and why.
- Tasting, and knowing what is missing.
- Running a line under pressure with people who are also under pressure.
- Judging produce that is never the same twice.
What's new
Work that did not exist in this job ten years ago.
- Menus built around supply volatility rather than tradition.
- Automated prep in high-volume kitchens, and supervising it.
- Provenance and dietary claims that have to hold up.
These three lists are editorial commentary, written against task-level data but not generated from it (OCC-05). Treat them as the author's reading, not as output.
Compare with another job
Pick one. You get a card with both scores, both sets of components, and a link worth sending to someone.
- Hairdresser 84
- Plumber 82
- Primary school teacher 79
- Electrician 79
- Aged care worker 75
- General practitioner 73
- Registered nurse 72
- Fashion designer 65
- Civil engineer 59
- Product designer 55
- Software developer 44
- Graphic designer 43
- Heavy truck driver 34
- Data analyst 32
- Paralegal 31
- Accountant 28
- Copywriter 24
- Bank teller 13
- Customer service representative 12
Sources used on this page
- Working Paper 140, Generative AI and Jobs
International Labour Organization · 2025 index · Confirm
- O*NET
US Department of Labor · 31.0 · CC BY 4.0
- Global Automation Atlas
Global Automation Atlas · 2026 release · Confirm