US dataswitch to UK

Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders

dumping, pouring, examining samples to verify qualities, installing, maintaining or repairing hoses, pumps and cleaning or sterilizing tanks, screens. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: setting up or adjusting machine controls to regulate conditions is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 6%
changing shape: 0%
staying human: 94%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 7 out of 100 (6–11 allowing for uncertainty): minimal exposure, across 20 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for separating, filtering, clarifying, precipitating, and still machine setters, operators, and tenders is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

What shifts is maintaining logs of instrument readings: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Set up, operate, or tend continuous flow or vat-type equipment; filter presses; shaker screens; centrifuges; condenser tubes; precipitating, fermenting, or evaporating tanks; scrubbing towers; or batch stills. These machines extract, sort, or separate liquids, gases, or solids from other materials to recover a refined product. Includes dairy processing equipment operators. The job title says “separating”, “filtering”, “clarifying”, “precipitating”, “still machine setters”, “operators” or “tenders”: officially one job, several names. The real job is the part underneath: setting up or adjusting machine controls to regulate conditions. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But separating, filtering, clarifying, precipitating, and still machine setters, operators, and tenders is not one task. It is 20 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is setting up or adjusting machine controls to regulate conditions, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 6%
changing shape: 0%
staying human: 94%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

4 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

1 task

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Maintaining logs of instrument readings
This is reading one thing and writing another: logs of instrument readings in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Maintain logs of instrument readings, test results, or shift production for entry in computer databases.” (O*NET task statement)
How this row was scored
Exposure score: 62 out of 100 (58–66 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Logging readings and shift figures into a database is exactly what software is good at.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

Changing shape

0 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.

Staying human

19 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Monitoring material flow or instruments
This work happens in the physical world: material flow, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor material flow or instruments, such as temperature or pressure gauges, indicators, or meters, to ensure optimal processing conditions.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Instruments can be watched automatically, but the job still expects someone on the floor beside the equipment.
The five ratings: output a model can produce 3/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Setting up or adjusting machine controls to regulate conditions
This work happens in the physical world: or adjusting machine controls, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up or adjust machine controls to regulate conditions such as material flow, temperature, or pressure.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Setting and adjusting machine controls for flow, temperature or pressure is done at the machine.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Turning valves or moving controls
This work happens in the physical world: valves, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Turn valves or move controls to admit, drain, separate, filter, clarify, mix, or transfer materials.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Turning valves and moving controls is hands-on work in the plant.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Inspecting machines or equipment
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect machines or equipment for hazards, operating efficiency, malfunctions, wear, or leaks.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking equipment for wear and leaks means walking up to it and looking.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Operating machines to process materials in compliance with applicable safety
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate machines to process materials in compliance with applicable safety, energy, or environmental regulations.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Running the processing machines safely means being at them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Examining samples to verify qualities
This work happens in the physical world: samples, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine samples to verify qualities such as clarity, cleanliness, consistency, dryness, or texture.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging clarity, dryness or texture of a sample is done by handling and looking at it.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Starting agitators, shakers, conveyors, pumps or centrifuge machines
This work happens in the physical world: agitators, shakers, conveyors, pumps or centrifuge machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Start agitators, shakers, conveyors, pumps, or centrifuge machines.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Starting pumps, shakers and conveyors happens at the equipment.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Communicating processing instructions to other workers
This work happens in the physical world: instructions, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Communicate processing instructions to other workers.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Written instructions are easy to produce, though they are usually passed on in person on a noisy floor.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Dumping, pouring
This work happens in the physical world: specified amounts, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Dump, pour, or load specified amounts of refined or unrefined materials into equipment or containers for further processing or storage.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Loading and pouring material into equipment is physical handling.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.

Show the other 10 tasks

Collecting samples of materials or products for laboratory analysis
staying human
This work happens in the physical world: samples of materials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Collect samples of materials or products for laboratory analysis.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Taking a physical sample requires being at the tank with a container.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Testing samples to determine viscosity
staying human
This work happens in the physical world: samples, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Test samples to determine viscosity, acidity, specific gravity, or degree of concentration, using test equipment such as viscometers, pH meters, or hydrometers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Lab tests on samples require someone to load them into the instruments.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Measuring or weighing materials
staying human
This work happens in the physical world: materials, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Measure or weigh materials to be refined, mixed, transferred, stored, or otherwise processed.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Weighing and measuring material means handling it.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Cleaning or sterilizing tanks, screens, inflow pipes, production areas or equipment, using hoses, brushes, scrapers or chemical solutions
staying human
This work happens in the physical world: tanks, screens, inflow pipes, production areas or equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean or sterilize tanks, screens, inflow pipes, production areas, or equipment, using hoses, brushes, scrapers, or chemical solutions.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning and sterilizing tanks and pipes is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Connecting pipes between vats and processing equipment
staying human
This work happens in the physical world: pipes, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Connect pipes between vats and processing equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Connecting pipes between vats is physical assembly.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Removing clogs, defects or impurities from machines, tanks, conveyors, screens or other processing equipment
staying human
This work happens in the physical world: clogs, defects or impurities, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Remove clogs, defects, or impurities from machines, tanks, conveyors, screens, or other processing equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Clearing clogs and impurities out of equipment is done by hand.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Installing, maintaining or repairing hoses, pumps, filters or screens to maintain processing equipment, using hand tools
staying human
This work happens in the physical world: hoses, pumps, filters or screens, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Install, maintain, or repair hoses, pumps, filters, or screens to maintain processing equipment, using hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Fitting and repairing pumps, hoses and screens needs hand tools.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Turning valves to pump sterilizing solutions or rinse water through pipes or equipment or to spray vats with atomizers
staying human
This work happens in the physical world: valves, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Turn valves to pump sterilizing solutions or rinse water through pipes or equipment or to spray vats with atomizers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Flushing lines and spraying vats is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Removing full containers from discharge outlets and replacing them with empty containers
staying human
This work happens in the physical world: full containers, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Remove full containers from discharge outlets and replace them with empty containers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Swapping full containers for empty ones is manual handling.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Assembling fittings, valves, bowls, plates, disks, impeller shafts or other parts to prepare equipment for operation
staying human
This work happens in the physical world: fittings, valves, bowls, plates, disks, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Assemble fittings, valves, bowls, plates, disks, impeller shafts, or other parts to prepare equipment for operation.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Assembling valves, plates and shafts is hands-on.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.

What this job pays, and how many people do it

Median pay: $51,610a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 60,100in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: logs of instrument readings in, a record out. The rows above are exactly that shape: maintaining logs of instrument readings. What it cannot do is be there in the room, and that is still where or adjusting machine controls get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Start with what does not change: setting up or adjusting machine controls to regulate conditions is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 6% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 94% in rows it is nowhere near. That is the position, measured across 20 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Maintaining logs of instrument readings is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to logs of instrument readings, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether or adjusting machine controls are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near monitoring material flow or instruments. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to separating, filtering, clarifying, precipitating, and still machine setters, operators, and tenders (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was chemical equipment operators and tenders: only about 13% of its durable work is work you already do. And on the numbers you do not need one. This job scores 7/100 here, with only 6% of the task list in the top band, and “monitor material flow or instruments” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Chemical Equipment Operators and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already set up or adjust machine controls to regulate conditions, and their equivalent is to adjust controls to regulate temperature, pressure, feed, or flow of liquids or gases…. Across both published task lists that is about 13% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 13% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Food Cooking Machine Operators and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already set up or adjust machine controls to regulate conditions, and their equivalent is to observe gauges, dials, and product characteristics, and adjust controls to maintain appropriate temperature…. Across both published task lists that is about 11% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $41,590 against your $51,610, 19.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Mixing and Blending Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already collect samples of materials or products for laboratory analysis, and their equivalent is to collect samples of materials or products for laboratory testing. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 6% of its task weight, across 20 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like setting up or adjusting machine controls to regulate conditions arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Chemical and related process operatives is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

In UK official statistics this job is counted as Chemical and related process operatives. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for separating / filtering / clarifying / precipitating / still machine setters / operators / tenders, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 6% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for separating / filtering / clarifying / precipitating / still machine setters / operators / tenders. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

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Questions people ask about this job

Will AI replace Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders?: Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders (United States, SOC 51-9012), 6% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 7 out of 100 (range 6–11, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Maintain logs of instrument readings, test results, or shift production for entry in computer databases” (62/100, high); “Communicate processing instructions to other workers” (32/100, low); “Monitor material flow or instruments, such as temperature or pressure gauges, indicators, or meters, to ensure optimal processing conditions” (19/100, minimal). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders” stay human?: About 94% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Assemble fittings, valves, bowls, plates, disks, impeller shafts, or other parts to prepare equipment for operation” (0/100, minimal); “Start agitators, shakers, conveyors, pumps, or centrifuge machines” (0/100, minimal); “Examine samples to verify qualities such as clarity, cleanliness, consistency, dryness, or texture” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders” do about AI?: Start from the ledger rather than the headline: 6% of this job's weighted core work is exposed, and roughly 94% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 20 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
4 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.