EXPOSED
The core of this job is physical and relational: otoscopic inspection, taking earmold impressions, physically fitting and modifying shells, and coaching an 80-year-old through six weeks of adaptation — none of that is text-on-screen work AI touches. The real threat isn't a language model, it's self-fitting OTC hearing aids and app-based audiometry that let manufacturers bypass the fitting appointment entirely, plus AI-driven first-fit algorithms that shrink the programming skill premium. Most states license hearing aid dispensers, which keeps a human in the loop for medical-referral screening and fitting sign-off.
Dipped in 2020, then grew past where it started.
Median pay $53,420 → $65,160 -2.4% 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
+18.4% 10,700 → 12,600 on the projections basis
Growing, and only partly exposed
The BLS expects +18.4% more of these jobs by 2034, and at 64/100 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.
~1,000 openings a year on average, including replacing people who leave.
Hearing ScreenerAudioprosthologistHearing Aid FitterHearing SpecialistAudiology AssistantAudiology TechnicianHearing Aid AttendantHearing Aid DispenserHearing Aid ConsultantHearing Aid SpecialistHearing Care SpecialistNewborn Hearing ScreenerHearing Care PractitionerHearing Care ProfessionalHearing Screen TechnicianHearing Instrument DispenserHearing Technician (Hearing Tech)Hearing Instrument Specialist (HIS)Hearing Aid Technician (Hearing Aid Tech)Hearing Health Technician (Hearing Health Tech)Hearing Screening Technician (Hearing Screening Tech)Licensed Hearing Instrument Specialist (Licensed HIS)Board Certified Hearing Instrument Specialist (Board Certified HIS)National Board Certified Hearing Instrument Specialist (National Board Certified HIS)
Holding it up: embodiment . Weakest point: judgment & accountability .
Mixed — a routine tier and a judgment tier Pure-tone air conduction screening, speech discrimination testing, and real-ear verification are already largely software-driven, and first-fit algorithms now generate the initial program from an audiogram automatically — but silicone impression-taking, shell modification with a grinder, and troubleshooting a feedback complaint on a live ear keep this at 13 rather than down in the automatable band.
Hands-on in uncontrolled environments You are working inside another person's ear canal with an otoscope, a curette, and impression material against an eardrum you must not perforate, then hand-buffing shells and reslotting vents — 15 not 18 because it happens in a clinic chair, not a warehouse or a roof, and the patient sits still.
Licensed human required and personally liable Roughly 45 states license hearing aid dispensers with a written and practical exam, and you personally sign the fitting agreement and the FDA-required medical-referral waiver when you see drainage, sudden unilateral loss, or visible deformity — 12 rather than higher because an audiologist's or ENT's scope supersedes yours on anything diagnostic, and OTC dereg has already thinned what the licence protects.
Meaningful discretion Real calls exist — whether tinnitus plus asymmetry means stop and refer, whether to override a first-fit toward less gain for a first-time wearer, whether a non-adapting patient needs a different receiver or more counselling — but they sit inside the FDA red-flag list and ANSI verification targets, which is why this is 9 and not in the ambiguous-high-stakes 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 (13/20 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 (12/20) 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 (9/20) 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 36 of this occupation's 64 points (56%).
Embodiment (15/20) 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.
No occupation passed every test: close enough to hearing aid specialists on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
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 79/100 — SAFE.
Task-mix shift is genuinely available here: as OTC and AI first-fit absorb mild-to-moderate, straightforward cases, the remaining caseload concentrates in hard-to-fit work — severe/profound losses, asymmetric and single-sided deafness, draining or surgically altered ears, custom deep-canal and CIC shells, pediatric earmold remakes, tinnitus masking, and OTC rescue cases where self-fitting failed. That residual is more physical and more judgment-dense per hour, though it is a smaller total headcount.
State licensing boards (e.g., dispenser boards in TX, FL, OH) extending scope rules to require a licensed dispenser or audiologist to perform and sign real-ear verification/probe-microphone measurement for any device sold as prescription-grade, and to document the FDA red-flag medical referral screen in person rather than via app questionnaire. Also watchable: state boards ruling that remote/app-based fitting of a prescription device constitutes dispensing requiring in-state licensure, as some boards did for teleaudiology during COVID waivers that later expired.
Payer-side mandate rather than licensure: if Medicare hearing aid coverage is enacted (recurring bills in Congress) with a condition-of-payment requiring a licensed dispenser's fitting and verification claim, the signature becomes economically load-bearing rather than merely legal.
Formalizing the referral decision as an owned call: boards or FDA guidance making the dispenser accountable for documented differential triage (sudden unilateral loss, conductive patterns, otorrhea, retrocochlear red flags) with defined liability for failure to refer, rather than passing an app-generated waiver. Malpractice or board-discipline cases arising from missed acoustic neuroma after app-based screening would accelerate this.
Manufacturer channel economics rather than consumer sentiment: if major OEMs keep gating the highest-margin prescription tiers, real-ear verification, and warranty/remake service through credentialed dispensing channels — and if OTC return rates stay high enough that retailers market in-person fitting as the premium remedy — buyers pay for the human as part of the outcome guarantee.
The limit. The binding constraint is unit volume, not any of these dimensions. Even with a stronger liability shield, an FDA OTC category that already lets manufacturers sell direct plus AI first-fit means fewer fitting appointments per thousand hearing losses; a smaller, better-protected profession is still a smaller one. Embodiment is already near its realistic ceiling and cannot rise. Trust premium is the weakest lever: price sensitivity among older buyers is severe and much of the perceived value historically came from the bundled device markup, which OTC compresses regardless of who fits it.
| New York-Newark-Jersey City, NY-NJ | 590 | $75,720 +16% |
| Los Angeles-Long Beach-Anaheim, CA | 480 | $80,050 +23% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 390 | $61,390 -6% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 330 | $61,980 -5% |
| Pittsburgh, PA | 310 | $44,990 -31% |
| Atlanta-Sandy Springs-Roswell, GA | 210 | $56,010 -14% |
| Houston-Pasadena-The Woodlands, TX | 210 | $57,220 -12% |
| Chicago-Naperville-Elgin, IL-IN | 200 | $69,320 +6% |
| Nashville-Davidson--Murfreesboro--Franklin, TN | 80 | $91,010 +40% |
| San Jose-Sunnyvale-Santa Clara, CA | 40 | $86,090 +32% |
| San Francisco-Oakland-Fremont, CA | 100 | $83,930 +29% |
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 64. 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.