EXPOSED
The text-production half of this job — lecture notes, reading guides, discussion prompts, syllabi, essay feedback, and much scholarly summarizing — is exactly what language models do well, and students are already using them to write the papers you grade. What survives is live Socratic argument in a room, reading a student's confusion in real time, and being a trusted adult who talks with 19-year-olds about death, faith, and what a good life is. The bigger near-term threat is not AI but humanities enrollment decline and adjunctification, which has already made the modal worker in this title contingent and low-paid.
This fall is concentrated in 2020 and has not recovered since.
Median pay $75,240 → $80,260 -14.7% 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
+0.7%
Percentage only. The projection counts a different population from the 20,460 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 +0.7% 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.
~2,000 openings a year on average, including replacing people who leave.
EducatorProfessorInstructorJewish EducatorDivinity TeacherEthics ProfessorTheology TeacherAdjunct ProfessorCollege ProfessorAdjunct InstructorDivinity ProfessorReligion ProfessorReligious EducatorTheology ProfessorAssistant ProfessorAssociate ProfessorMetaphysics TeacherPhilosophy LecturerReligion InstructorHumanities ProfessorPhilosophy ProfessorPhilosophy InstructorPhilosophy SpecialistAdjunct Faculty Member
Holding it up: trust premium . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Roughly half the week — building a Kant seminar's reading schedule, writing prompts on the trolley problem, summarizing secondary literature, marking 60 papers against a rubric — is text-in/text-out that a model does at speed, while the part that holds is the unscripted eighty minutes where you hear a student misread Nietzsche and reroute the whole discussion, plus dissertation supervision and departmental judgment about what counts as a philosophy major; that mix of clearly-exposed and clearly-durable is what puts it at 11 rather than in the resistant band.
Some physical or field component The physical demand is standing in a classroom, writing on a board, holding office hours, and moving between campus buildings — nothing that requires manipulating equipment or working in conditions a remote instructor couldn't reproduce, which is why this sits well below the field-and-tool occupations rather than near them.
No licence, no signature requirement No state licence, no board exam, no certification body stands between you and the lectern — a PhD (often not even a completed one, for adjuncts) is a hiring credential, not a legal monopoly on teaching Aquinas, and nobody sues the instructor for a bad reading of Aristotle; the 3 reflects that even accreditation requirements bind the institution, not you personally.
Meaningful discretion You decide unilaterally whether a paper is plagiarized or AI-written, how hard to press a student defending a repugnant position in front of peers, what to do when a discussion of suicide turns personal, and where a grade lands on the line between B+ and A- with scholarship consequences — real discretion with real cost, but bounded by rubrics, appeals processes, department curricula, and Title IX referral paths, which keeps it at 11 rather than in the owns-the-call 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 (3/20) is whether the law requires a licensed human to sign. Trust premium (15/20) is whether buyers specifically pay for a person. Judgment and accountability (11/20) 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 29 of this occupation's 48 points (60%).
Embodiment (8/20) 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.
Law Teachers, Postsecondary EXPOSED
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 58/100, still EXPOSED.
Task-mix shift as the routine tier evaporates: if institutions respond to AI-written papers by moving assessment to live oral defense, in-class handwritten exams, and iterative dialogue — a shift visible in the 2023-25 wave of departmental assessment-policy rewrites — the remaining job is real-time argument evaluation and diagnosing confusion, which current models cannot do in a room. Raises task_resistance without any new law, but only where seminar-sized classes survive; large-lecture GenEd sections gain nothing.
Institutional codification of in-person, no-device seminar formats as a paid premium: e.g., accreditation-recognized 'oral examination' requirements (already standard at Oxford/Cambridge and in some US honors colleges), or a university adopting Middlebury/Chicago-style small-seminar caps with viva voce assessment as its explicit differentiator against AI-mediated instruction. Also seminary and denominational credentialing (ATS accreditation standards for M.Div. formation, ordination boards) that require face-to-face spiritual formation hours with a human instructor.
Formal role in academic-integrity adjudication: if faculty handbooks or state law make the individual instructor the accountable decision-maker on AI-misuse allegations (a determination with appeal rights and real consequence for the student), and if AI-detection evidence is explicitly non-dispositive requiring instructor judgment — a direction some honor-code offices have already taken after Turnitin detector false-positive controversies.
Only a narrow route, and it applies to the clergy-adjacent slice: state clergy-privilege and mandatory-reporter statutes, plus denominational safe-church certification, attach personal duties to named credentialed humans doing pastoral formation. A seminary instructor holding ordination and supervising counseling practica sits inside that. This does not extend to secular philosophy faculty, where no plausible licensure route exists.
The limit. Every lever here is small relative to the real risk, which is not capability but demand: humanities enrollment decline, program closures (West Virginia University 2023, and successor cases), and adjunctification. A rising trust premium for human seminar teaching does not help if the seminar is cut and the title's modal worker is a per-course adjunct with no claim on it. There is no plausible licensure regime for secular philosophy instruction, so liability_shield is effectively capped in the low single digits.
| New York-Newark-Jersey City, NY-NJ | 1,400 | $101,210 +26% |
| Chicago-Naperville-Elgin, IL-IN | 830 | $78,930 -2% |
| Boston-Cambridge-Newton, MA-NH | 690 | $100,770 +26% |
| Los Angeles-Long Beach-Anaheim, CA | 670 | $103,320 +29% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 550 | $77,870 -3% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 510 | $79,310 -1% |
| Dallas-Fort Worth-Arlington, TX | 410 | $76,730 -4% |
| San Jose-Sunnyvale-Santa Clara, CA | 370 | $100,140 +25% |
| Riverside-San Bernardino-Ontario, CA | 120 | $123,650 +54% |
| Oxnard-Thousand Oaks-Ventura, CA | 90 | $122,700 +53% |
| San Francisco-Oakland-Fremont, CA | 130 | $119,530 +49% |
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.