Court, Municipal, and License Clerks

Legal

AI exposure

  • Data source: BLSPublished: 2026-08

    Very high· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.102

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.43

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 30% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Show 1 hidden task

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Record and edit the minutes of meetings and distribute to appropriate officials or staff members.

O*NET Task ID 23269

1.0
Question applicants to obtain required information, such as name, address, or age, and record data on prescribed forms.

O*NET Task ID 23270

1.0
Issue public notification of all official activities or meetings.

O*NET Task ID 23271

1.0
Prepare meeting agendas or packets of related information.

O*NET Task ID 23274

1.0
Prepare and issue orders of the court, such as probation orders, release documentation, sentencing information, or summonses.

O*NET Task ID 23275

1.0
Prepare ordinances, resolutions, or proclamations so that they can be executed, recorded, archived, or distributed.

O*NET Task ID 23276

1.0
Code information on license applications for entry into computers.

O*NET Task ID 23277

1.0
Record case dispositions, court orders, or arrangements made for payment of court fees.

O*NET Task ID 23278

1.0
Prepare documents recording the outcomes of court proceedings.

O*NET Task ID 23281

1.0
Perform general office duties, such as taking or transcribing dictation, typing or proofreading correspondence, distributing or filing official forms, or scheduling appointments.

O*NET Task ID 23283

1.0

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information