EXPOSED
Lecture writing, slide decks, syllabus construction, quiz banks, reading summaries and first-pass essay feedback are all things current models do at usable quality, and much of an intro human/physical geography course is exactly that. What persists is live classroom facilitation, GIS and remote-sensing lab supervision, field methods instruction, thesis advising and the institutional judgment of grading and curriculum design. The bigger near-term threat to this 3,300-person occupation is departmental consolidation and enrollment decline in small geography programs, which AI-assisted course delivery accelerates rather than causes.
This fall is concentrated in 2020 and has not recovered since.
Median pay $80,520 → $97,590 -3.0% in real terms
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
+3.3%
Percentage only. The projection counts a different population from the 3,330 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Growing, and only partly exposed
The BLS expects +3.3% more of these jobs by 2034, and at 48/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
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.
~300 openings a year on average, including replacing people who leave.
LecturerProfessorInstructorCollege ProfessorAssistant ProfessorAssociate ProfessorCartography TeacherGeography ProfessorGeomatics ProfessorGeography InstructorCartography ProfessorGeospatial InstructorCollege Faculty MemberGeography Faculty MemberHuman Geography ProfessorUniversity Faculty MemberHuman Geography InstructorPhysical Geography ProfessorHuman Geography Faculty MemberCultural Geography Faculty MemberGeographic Information Systems Professor (GIS Professor)Geographic Information Systems Faculty Member (GIS Faculty Member)
Holding it up: trust premium . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Roughly half the workload — GIS lab troubleshooting when a projection fails mid-exercise, running a field methods week with GPS units and soil augers, defending a thesis proposal with a committee, reading a student's confused mental map and diagnosing why — has no text-output substitute, while the intro-course scaffolding of lecture notes, quiz banks and map-reading worksheets already does, which is what pins this at 11 rather than up with lab scientists or down with content writers.
Some physical or field component Field camp, campus watershed walks, hauling total stations and Trimble units outdoors, and standing over a student's shoulder at an ArcGIS workstation are real physical duties, but they are a few weeks and a few lab hours per term against a base of lecturing, screen-based mapping and committee work — a 9, not the 15 of a field geologist who lives in the terrain.
No licence, no signature requirement No state licence, no board exam, no professional registry gates who teaches human geography — a PhD and a departmental hiring vote are the only entry controls, and GISP certification is optional and unenforced even for the GIS courses, so nothing in law requires a credentialed human to deliver the content.
Meaningful discretion Grading a contested essay on political borders, setting curriculum for an accreditation review, deciding whether a student's fieldwork is publishable, and calling safety judgments on a field trip are genuine discretion, but they sit inside departmental grading policies, catalogue requirements and IRB review rather than being unappealable high-stakes calls — hence 10, mid-band.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (11/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (4/20) is whether the law requires a licensed human to sign. Trust premium (14/20) is whether buyers specifically pay for a person. Judgment and accountability (10/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 28 of this occupation's 48 points (58%).
Embodiment (9/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
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 62/100, still EXPOSED.
If intro survey lecturing is largely absorbed by AI-assisted/asynchronous delivery, the residual job becomes GIS/remote-sensing lab supervision, field camp instruction, thesis and capstone advising, and IRB-adjacent research design — tiers current models cannot deliver. This is a task-mix shift requiring no new rule, and is visible in how surviving geography programs already reposition around GIScience labs rather than survey courses.
If accreditors or state systems adopt rules that credit-bearing courses must have documented substantive faculty interaction (the federal 'regular and substantive interaction' standard for distance education, already enforced in Title IV audits), the assessable-by-AI portion cannot be counted as instruction.
If academic-integrity policy makes the instructor of record the accountable decider on AI-use allegations, with appealable findings and personal documentation duties, grading judgment becomes a consequential contested call rather than a scoring task.
If departments shift required credits toward field methods (surveying, GPS/drone data collection, soil and stream sampling) and field camps as the program's differentiator against online competitors, the share of the workload occurring in unpredictable outdoor environments rises.
If institutions market small-cohort, in-person instruction as the paid-for distinction — and if faculty union contracts (e.g. AAUP/AFT chapters that have bargained AI clauses limiting course delivery by machine, as in the 2024 CSU and Rutgers negotiations) restrict AI-only sections — students and parents are explicitly buying human instruction.
Narrow route only: if faculty teaching GIS toward professional certification (GISP, or state surveying/mapping licensure paths where geospatial coursework is credited) must be individually credentialed and sign competency attestations, a licensure hook appears for that subset.
The limit. No lever addresses the dominant risk: program closure from enrollment decline and departmental merger into environmental science or earth systems. A geography teacher can score well on every dimension and still lose the line item when the major is discontinued. Liability shielding is structurally weak — postsecondary teaching has no signature requirement and no personal liability, and nothing in motion changes that.
| Portland-Vancouver-Hillsboro, OR-WA | 130 | $103,470 +6% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 120 | $99,560 +2% |
| Los Angeles-Long Beach-Anaheim, CA | 100 | $146,040 +50% |
| Chicago-Naperville-Elgin, IL-IN | 90 | $103,280 +6% |
| Atlanta-Sandy Springs-Roswell, GA | 60 | $85,420 -12% |
| College Station-Bryan, TX | 60 | $88,300 -10% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 60 | $107,830 +10% |
| New York-Newark-Jersey City, NY-NJ | 60 | $99,640 +2% |
| Los Angeles-Long Beach-Anaheim, CA | 100 | $146,040 +50% |
| Austin-Round Rock-San Marcos, TX | 30 | $109,900 +13% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 60 | $107,830 +10% |
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 48. 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.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.