Will AI replace Physical Scientists, All Other? 42/100

EXPOSED

This is a catch-all bucket (materials and surface scientists, oceanographic and atmospheric specialists, forensic and government lab scientists), and the modal worker splits time between instrument-based lab or field measurement and desk work: literature review, data reduction, statistical modeling, and report and grant writing. The desk half is the most automatable part of the job — AI already drafts methods sections, writes analysis scripts, and screens literature faster than a postdoc. What holds is hands-on experimental design, running and calibrating physical instruments, field sampling, and being the person who signs off on whether a result is real.

10-year outlook: Headcount holds roughly flat but the job reshapes: fewer hours on analysis and writing, more on instrumentation, field deployment, and standing behind conclusions.

42/100 risk resistance · ±3 on re-score

US employment, 2019–2025+27.1%

17,55022,300 workers

Headcount grew steadily across the period.

Median pay $109,910 → $122,570 -10.8% in real terms (nominal +11.5%, less ~25% US inflation over the period)

The job count is not the verdict

This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.

So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.

BLS projection, 2024–2034

+0.6%

Percentage only. The projection counts a different population from the 22,300 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.

Exposed, but growing

AI can already do a lot of these tasks, and the BLS still expects +0.6% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.

Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.

~2,000 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

InventorScientistDrone PilotRemote PilotDrone OperatorImage ScientistRadar ScientistSensor AssemblerSensor SpecialistWood TechnologistPhysical ScientistResearch ScientistSpectral ScientistCommercial Drone PilotRemote Sensing AnalystUnmanned Systems PilotRemote Sensing EngineerGeospatial Image AnalystRemote Sensing ScientistCommercial Drone OperatorRemote Sensing SpecialistUnmanned Systems OperatorRemote Sensing TechnologistWeather Algorithm Scientist

This is a catch-all code, not a single job

The BLS uses Physical Scientists, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:

The score is an average over dissimilar work. Your own role could sit well above or below it, and the five dimensions describe the bucket rather than any one job inside it.
We've withheld the transfer routes here. They are computed from skill-profile overlap, and a bucket's profile is an average of unrelated jobs — which produces confident-looking matches that are meaningless. Better to show none than to point someone at the wrong career.

If a more specific occupation on the register describes what you actually do, that page is the one to trust.

Score — 42/100 resistance

Holding it up: judgment & accountability (12/20). Weakest point: liability shield (3/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 11 + 9 + 3 + 7 + 12 = 42. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 11/20

Mixed — a routine tier and a judgment tier Sample prep, XPS or SEM runs, instrument calibration and drift checks, and deciding which follow-up experiment actually discriminates between two hypotheses stay with you — but the literature triage, the Python that reduces your spectra, the statistics, and the first draft of the methods and results sections are now hours of assisted work rather than days, and those pieces are close to half of a typical week, which is what lands this at 11 instead of the 15+ a bench-only role would earn.

Embodiment 9/20

Some physical or field component Cruise-based water sampling, radiosonde launches, contaminated-site fieldwork and glovebox or vacuum-chamber work put real hands-on hours in the job, but the modal person in this bucket does that in a temperature-controlled lab or on scheduled campaigns, not daily in uncontrolled conditions — a 9 reflects field-and-bench work that is intermittent and mostly staged, unlike a well-site geologist who is outdoors by default.

Liability shield 3/20

No licence, no signature requirement There is no licence to practise as a materials or atmospheric scientist: a PhD and a lab safety certification get you to the bench, and when a result is wrong the institution, the PI, or the accrediting body (ISO 17025, ASCLD for forensic labs) absorbs it — the 3 rather than 0 is only because forensic examiners can be cross-examined personally on their own findings.

Trust premium 7/20

Some relationship component Peer review is blind and papers are read for the data, not the author, so most output travels without you attached; the 7 comes from the parts that don't — program managers who fund you again because your last deliverable was clean, and the internal client who brings a failure analysis to you specifically because you told them the truth about the last one.

Judgment & accountability 12/20

Meaningful discretion Calling a peak real versus instrument artifact, deciding a contaminated run gets discarded rather than reported, and setting detection limits and uncertainty bounds are genuinely yours and often unfalsifiable in the short term — but much of the work runs on written protocols, SOPs and validated methods, and the consequential calls usually go up to a PI, program office, or lab director before anyone acts, which caps this at 12.

Confidence: low · reviewed 2026-08-11 · how scoring works

How to future-proof this job

Own the instrument: become the person who designs, calibrates, and troubleshoots the specific measurement apparatus your lab depends on — that capability doesn't transfer to a model.
Move toward regulatory or forensic work where a named scientist must testify to or certify results (expert witness, accreditation-body method validation), converting judgment into a signature requirement.
Take on principal-investigator-level accountability: scope the research question, defend the design to sponsors, and own negative results rather than executing someone else's protocol.
Specialize in field campaigns — oceanographic cruises, atmospheric deployments, site characterization — where data collection is physical and unrepeatable.

Where to go deeper on what this job runs on: Khan Academy — reading and vocabulary, all levels, free free · Coursera — critical thinking and logic, audit free free to audit · Coursera — active listening and communication skills free to audit · Purdue OWL — the standard reference for professional writing free · Toastmasters — public speaking practice at local clubs worldwide low · Khan Academy — physics, chemistry and biology from the ground up free

All 35 skills ranked by how many jobs they open →

What would move this back up — beyond any one person

The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 53/100, still EXPOSED.

3 specific changes that would raise this score

already happening task resistance +3

As AI absorbs literature screening, script-writing and report drafting, the residual day becomes experimental design, instrument calibration/troubleshooting, and adjudicating anomalous results — a genuine two-tier split in this bucket. Watch for lab staffing plans where the analyst tier is cut and remaining scientists are reassigned to method development and validation.
plausible liability shield +5

Forensic and environmental sub-populations are the route: if ISO/IEC 17025 accreditation bodies (A2LA, ANAB) or ASCLD/ASB standards add an explicit requirement that a named qualified analyst personally review and sign any AI- or algorithm-derived result before report release — mirroring the technical-reviewer signature already required for casework — the signature becomes non-delegable. Also watch state environmental labs' NELAP certification rules and expert-witness admissibility fights over black-box analysis under Daubert.
plausible judgment accountability +3

If agency reproducibility/validation policies (e.g. EPA method validation, NOAA data-quality directives, or a federal research-integrity rule) require a named individual to attest that an AI-assisted analysis was independently verified, the role formally owns the 'is this result real' call rather than informally holding it.

The limit. Trust premium has no realistic route: buyers here are agencies, courts and internal R&D clients who pay for accredited output, not for a human per se. The catch-all nature of the SOC also means gains concentrate in the forensic/regulatory-lab slice; industrial materials scientists likely see none of it.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 68 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Washington-Arlington-Alexandria, DC-VA-MD-WV	2,740	$170,980 +39%
Atlanta-Sandy Springs-Roswell, GA	930	$137,680 +12%
New York-Newark-Jersey City, NY-NJ	860	$139,560 +14%
Los Angeles-Long Beach-Anaheim, CA	820	$136,160 +11%
Albany-Schenectady-Troy, NY	780	$99,460 -19%
Dallas-Fort Worth-Arlington, TX	700	$133,590 +9%
Baltimore-Columbia-Towson, MD	570	$108,160 -12%
Indianapolis-Carmel-Greenwood, IN	560	$67,000 -45%

Best paid

Providence-Warwick, RI-MA	70	$180,470 +47%
Minneapolis-St. Paul-Bloomington, MN-WI	410	$176,440 +44%
Washington-Arlington-Alexandria, DC-VA-MD-WV	2,740	$170,980 +39%

Percentages are against this occupation's national median of $122,570. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.

That is worth saying out loud next to a score of 42. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

Watch this verdict

Kept current

The dispatch runs daily. 711 reported cases on file, 357 of them things a named organisation actually did. Newest landed yesterday. See it · RSS
Scores move on evidence, not on a clock. Re-scoring the same occupation drifts a couple of points on its own, so a scheduled refresh would mostly republish our own noise. An occupation is re-examined when deployments accumulate against it — which is why a verdict changing here means something. Last register revision 2026-08-11.
Employment updates once a year, when the BLS publishes. Every occupation carries its own 2019–2025 series.

Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.

Cooked Index — Physical Scientists, All Other: EXPOSED, 42/100.
Scored 2026-08-11 · printed from https://cookedindex.com/jobs/physical-scientists-all-other/
Verdicts are re-examined as evidence accumulates, so this sheet goes out of date. Check the page above for the current score, the reasoning behind each dimension, and what would move it.

Physical Scientists, All Other