← Risk register SOC 25-4022 · reviewed 2026-08-11

Librarians and Media Collections Specialists

133,790 US workers · median $68,270/yr · Education

EXPOSED

The information-retrieval core of the job — answering reference questions, building search strategies, cataloging and metadata assignment, compiling bibliographies, writing readers' advisory lists — is exactly what language models do cheaply, and vendor-supplied MARC records already stripped much of the cataloging tier. What persists is the physical, community-facing library: running children's storytime and teen programs, teaching information literacy to students who don't know what they don't know, managing budgets and collection challenges, and being the trusted adult in a public building. Most librarians hold an MLS and school librarians need state teaching certification, but that's a hiring gate, not a liability shield, so headcount tracks municipal and campus budgets more than technology.

10-year outlook: Reference and cataloging roles keep consolidating into fewer positions while programming, instruction, and community-services librarians hold steady — the occupation shrinks modestly and shifts decisively toward in-person work.

US employment, 2019–2025-1.4%
135,690133,790 workers

Roughly flat across the period, with year-to-year wobble.

Median pay $59,500 → $68,270 -8.2% in real terms (nominal +14.7%, 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

+1.7% 142,100 → 144,500 on the projections basis

Exposed, but growing

AI can already do a lot of these tasks, and the BLS still expects +1.7% 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.

~13,500 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.

CatalogerLibrarianCataloguerClassifierBibliographerLaw LibrarianFilm LibrarianNews LibrarianMedia LibrarianMusic LibrarianDocument ManagerMedia SpecialistMedia TechnicianPrison LibrarianRecord LibrarianSchool LibrarianCatalog LibrarianDigital LibrarianLibrary AssociateMedical LibrarianSerials LibrarianSystems LibrarianVisual SpecialistChemical Librarian

Score — 42/100 resistance

Holding it up: trust premium (12/20). Weakest point: liability shield (5/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 8 + 8 + 5 + 12 + 9 = 42. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 8/20

Mixed — a routine tier and a judgment tier An 8 reflects the split inside a single workday: OPAC search, copy cataloging against OCLC records, ILL request routing, and database-of-record reference answers are already largely machine work, while storytime, a bibliographic instruction session for a freshman comp class, and a reconsideration hearing over a challenged title still need a person in the room — that mix is why it sits at 8 rather than the 4 a pure cataloging post would get.

Embodiment 8/20

Some physical or field component An 8 covers the shelving-adjacent reality — weeding the stacks by hand, processing and repairing physical items, hauling AV carts and setting up program space, staffing a service desk in a building open to whoever walks in — without reaching the 13+ band, because none of it happens outdoors, on scaffolding, or in an environment you cannot control.

Liability shield 5/20

Certification preferred, not legally required The MLS and, for school librarians, state teaching certification gate who gets hired, but nothing you sign carries personal legal exposure: a bad subject heading, an over-ordered database, or a collection decision is answered to a director, board, or principal, not a licensing body that can strip your credential — hence 5, the certification-preferred floor rather than a licensed-professional score.

Trust premium 12/20

Some relationship component 12 recognizes that regular patrons return for you specifically — the reference interview where someone finally admits what they are actually researching, the teacher who plans a unit with you, the parent whose kid learned to sit through a book at your storytime — but most transactions are with strangers who would take the same answer from a self-checkout or a chatbot, keeping this below the relationship-is-the-product band.

Judgment & accountability 9/20

Meaningful discretion 9 is set by genuine discretion with a backstop: you decide what to buy, what to weed, how to handle a patron privacy request or a minor asking about something sensitive, and how to defend a title under challenge — but selection policies, ALA guidance, and board approval frame those calls, and the consequences of getting them wrong land on the institution rather than on you personally.

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

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: trust, physical-presence, judgment

How to future-proof this job

Training paths for your skill gaps: Khan Academy — physics, chemistry and biology from the ground up free · Learning How to Learn — the most-taken course on Coursera, and free free to audit · Coursera — teaching and instructional design, audit free free to audit · MIT OpenCourseWare — systems analysis and engineering free · Coursera — project coordination and cross-team delivery free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Family and Consumer Sciences Teachers, Postsecondary EXPOSED · 53/100 · you already have ~64% of the skill profile

Skills to close: Science, Learning Strategies, Instructing, Systems Analysis

Secondary School Teachers, Except Special and Career/Technical Education SAFE · 69/100 · you already have ~62% of the skill profile

Skills to close: Learning Strategies, Instructing, Science, Coordination

Elementary School Teachers, Except Special Education SAFE · 72/100 · you already have ~58% of the skill profile

Skills to close: Learning Strategies, Instructing, Coordination, Science

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 63/100, still EXPOSED.

8 specific changes that would raise this score
  • already happening liability shield +4

    State statutes that make a named certified librarian the legally designated decision-maker in materials-challenge and 'harmful to minors' review — Arkansas Act 372 (2023) and Iowa SF 496 attach personal exposure to a specific employee, and several states pair this with a mandated formal reconsideration process only a certified librarian may run. Perverse but real: it makes the role legally non-delegable to a district administrator or a vendor tool.

  • already happening judgment accountability +3

    Formal role in institutional AI/misinformation policy: campus and district adoption of information-literacy requirements that name the librarian as the reviewer of AI-generated citations and source provenance (already appearing in ACRL Framework implementations and in nursing/law school accreditation research-competency standards).

  • already happening task resistance +3

    Task-mix shift: routine reference, bibliography compilation and copy cataloging fully absorbed, leaving instruction, archival appraisal, licensing/consortial negotiation, and adversarial-context research (litigation, FOIA, provenance disputes) — genuinely a two-tier occupation, but the judgment tier employs far fewer people than the current headcount.

  • already happening trust premium +2

    Continued parental and community willingness to fund in-person youth programming — storytime, teen spaces, supervised after-school presence — as a childcare-adjacent good rather than an information service. Visible in library levy passage rates and in program attendance holding while reference transactions collapse.

  • plausible liability shield +3

    Enforcement of state mandates requiring a certified school librarian per building or per enrollment threshold (existing in a handful of states; recurring bills in Pennsylvania, Washington, Michigan). Where the mandate carries accreditation or funding consequences, headcount stops tracking discretionary budget.

  • plausible liability shield +2

    Library-records confidentiality statutes (48 states) extended by AG opinion or amendment to cover queries submitted to third-party AI reference tools, requiring a named librarian to certify the vendor pipeline. Turns patron-privacy compliance into a signed human duty.

  • plausible judgment accountability +2

    Records-retention and public-records obligations shifting to library and archives staff as agencies digitize — a named archivist/librarian signing appraisal and disposition decisions with legal consequence, as under state records-management acts and NARA-modeled schedules.

  • plausible trust premium +2

    Paid demand specifically for human-verified sourcing where fabricated citations carry cost — court-rule sanctions for AI-hallucinated authority (Rule 11 orders in Mata v. Avianca and successors) driving law-firm and expert-witness research spend toward credentialed information professionals.

The limit. Every upward lever here is institutional, and none of them protects the median position: liability and judgment gains concentrate in school librarians under challenge-law regimes and in archival/special-collections roles, while the large public-library reference tier has no route back. The binding constraint is municipal and campus budget, not capability — a mandate that raises liability_shield without funding it produces fewer, more exposed librarians rather than more of them.

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 359 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

New York-Newark-Jersey City, NY-NJ 10,690 $81,670 +20%
Chicago-Naperville-Elgin, IL-IN 3,740 $66,250 -3%
Boston-Cambridge-Newton, MA-NH 3,660 $79,450 +16%
Washington-Arlington-Alexandria, DC-VA-MD-WV 3,630 $95,480 +40%
Los Angeles-Long Beach-Anaheim, CA 3,270 $97,510 +43%
Dallas-Fort Worth-Arlington, TX 2,550 $74,340 +9%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 2,430 $77,330 +13%
San Francisco-Oakland-Fremont, CA 1,940 $101,490 +49%

Best paid

Naples-Marco Island, FL 90 $106,550 +56%
Kennewick-Richland, WA 90 $105,240 +54%
San Jose-Sunnyvale-Santa Clara, CA 700 $103,240 +51%

Percentages are against this occupation's national median of $68,270. 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

The score above is about what the work exposes. This is reporting about real deployments in this occupation — the difference between "could be automated" and "somebody automated it."

1 of 1 reported case, with sources

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.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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Kept current

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