Jueces
LegalExposición a la IA
- Fuente de datos: BLSPublicado: 2026-08
Alto· relativa
BajoCuatro bandas relativasMuy altoValor por grupo ocupacional
Escala, base y fuente
Cuatro bandas relativas (Bajo / Moderado / Alto / Muy alto)
831 ocupaciones detalladas de la tabla de proyecciones de empleo de BLS. El valor se asigna por código de la National Employment Matrix (NEM), de modo que las ocupaciones que comparten un código NEM reciben la misma banda
- Fuente de datos: AnthropicPublicado: 2026-03
0.311
0.000Rango de los valores aquí recogidos0.745Escala, base y fuente
Índice de exposición observada, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
- Fuente de datos: ILOPublicado: 2025
0.31
0.09Rango de los valores aquí recogidos0.70Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición a la IA generativa, 0–1 tal como se publica
Grupo primario de la CIUO-08 — todas las ocupaciones con ese código reciben este valor
Calculado por este sitio, no publicado por la OIT: de las 1012 ocupaciones que este sitio vincula al conjunto de datos de la OIT, un 65% alcanza o supera este valor.
Qué tipo de cifra publica esta fuente
La categoría de BLS es un rango relativo, no un nivel absoluto, y tampoco es una medición de primera mano: agrupa en cuatro bandas los rangos percentiles de la ocupación en varios estudios publicados. No es una previsión de empleo ni de salarios, no es una probabilidad de adopción y no distingue entre automatización y aumento.
Task-level exposure
Solo tareas expuestasValues 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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Sentence defendants in criminal cases, on conviction by jury, according to applicable government statutes.O*NET Task ID 5644 | 0.5 |
Rule on admissibility of evidence and methods of conducting testimony.O*NET Task ID 5645 | 0.5 |
Preside over hearings and listen to allegations made by plaintiffs to determine whether the evidence supports the charges.O*NET Task ID 5646 | 0.5 |
Read documents on pleadings and motions to ascertain facts and issues.O*NET Task ID 5647 | 0.5 |
Interpret and enforce rules of procedure or establish new rules in situations where there are no procedures already established by law.O*NET Task ID 5648 | 0.5 |
Monitor proceedings to ensure that all applicable rules and procedures are followed.O*NET Task ID 5649 | 0.5 |
Advise attorneys, juries, litigants, and court personnel regarding conduct, issues, and proceedings.O*NET Task ID 5650 | 0.5 |
Research legal issues and write opinions on the issues.O*NET Task ID 5651 | 0.5 |
Conduct preliminary hearings to decide issues, such as whether there is reasonable and probable cause to hold defendants in felony cases.O*NET Task ID 5652 | 0.5 |
Write decisions on cases.O*NET Task ID 5653 | 0.5 |
Instruct juries on applicable laws, direct juries to deduce the facts from the evidence presented, and hear their verdicts.O*NET Task ID 5643 | 0.0 |
Supervise other judges, court officers, and the court's administrative staff.O*NET Task ID 5656 | 0.0 |
Participate in judicial tribunals to help resolve disputes.O*NET Task ID 5660 | 0.0 |
Perform wedding ceremonies.O*NET Task ID 5661 | 0.0 |
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
Información ocupacional
Cambios recientes relacionados con esta ocupación
mar 2026: Same paper assigns ATE 0.43 by 2027 in SF Bay Tier 1. 100% of legal occupations in scope cross moderate-risk threshold by 2027 in Tier 1; only 14.3% cross in Tier 3 (New York) by 2030.
[Fuente: arXiv 2604.00186 (Gupta & Kumar, 2026)]mar 2026: ATE framework identifies judges among highest-risk occupations (ATE 0.43-0.47) for agentic AI displacement — AI systems increasingly capable of end-to-end legal reasoning workflows.
[Fuente: Gupta & Kumar (2026) Agentic AI and Occupational Displacement]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.