O*NET-SOC-Code
17-2051.02

Design or oversee projects involving provision of potable water, disposal of wastewater and sewage, or prevention of flood-related damage. Prepare environmental documentation for water resources, regulatory program compliance, data management and analysis, and field work. Perform hydraulic modeling and pipeline design.

Berufsbezeichnungen und Aufgabenbeschreibungen werden wie veröffentlicht auf Englisch angezeigt. Beschriftungen, einschließlich der Aufgabenarten, sind übersetzt.

KI-Exposition

  • Datenquelle: BLSVeröffentlicht: 2026-08

    Hoch· relativ

    NiedrigVier relative BänderSehr hoch

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)

    831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band

    Quelldatensatz (XLSX-Download)

  • Datenquelle: AnthropicVeröffentlicht: 2026-03

    0.008

    0.000Spannweite der hier geführten Werte0.745

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Index der beobachteten Exposition, 0–1 wie veröffentlicht

    Auf O*NET-Aufgaben abgebildet

    Veröffentlicht je SOC-2018-Beruf; jeder O*NET-Beruf mit demselben SOC-2018-Code erhält diesen Wert

    Quelldatensatz (CSV-Download)

  • Datenquelle: ILOVeröffentlicht: 2025

    0.30

    0.09Spannweite der hier geführten Werte0.70

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht

    Veröffentlicht je ISCO-08-Berufsgattung. Mit diesem Beruf ganz oder teilweise verknüpft durch Anwendung der Umsteigeschlüssel des U.S. Bureau of Labor Statistics (ISCO-08 zu SOC 2010, SOC 2010 zu SOC 2018) in veröffentlichter Form

    Quelldatensatz (PDF-Download)

Welche Art von Wert diese Quelle veröffentlicht

Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.

KI-Exposition (OpenAI-Rubrik)

28 bewertete Aufgaben · 26 Aufgaben mit β ≥ 0,5 (92.9%)

β = direkte Exposition (E1) + 0,5 × Exposition bei verfügbaren Werkzeugen (E2), gemäß der Definition des Quell-Repositorys.

  • Quelleinheit: Aufgaben aus O*NET 27.2 → Berufscode aus O*NET 31.0
  • Alle bewerteten Aufgaben stehen in der Aufgabenliste von O*NET 31.0.
Quelle
OpenAI "GPTs are GPTs" exposure rubric
Ausgabe
gh-main-0471612
Lizenz
MIT License, Copyright (c) 2024 OpenAI

Aufgaben

Aufgabenbeschreibungen aus der O*NET® 31.0 Database, Kernaufgaben zuerst.

AufgabeArtβ (OpenAI)
Write technical reports or publications related to water resources development or water use efficiency.Kern1
Review and critique proposals, plans, or designs related to water or wastewater treatment systems.Kern0,5
Provide technical support on water resource or treatment issues to government agencies.Kern0,5
Provide technical direction or supervision to junior engineers, engineering or computer-aided design (CAD) technicians, or other technical personnel.Kern1
Identify design alternatives for the development of new water resources.Kern0,5
Develop plans for new water resources or water efficiency programs.Kern0,5
Design or select equipment for use in wastewater processing to ensure compliance with government standards.Kern0,5
Conduct water quality studies to identify and characterize water pollutant sources.Kern0,5
Perform hydrological analyses, using three-dimensional simulation software, to model the movement of water or forecast the dispersion of chemical pollutants in the water supply.Kern0,5
Perform hydraulic analyses of water supply systems or water distribution networks to model flow characteristics, test for pressure losses, or to identify opportunities to mitigate risks and improve operational efficiency.Kern0,5
Oversee the construction of decentralized or on-site wastewater treatment systems, including reclaimed water facilities.Kern0
Gather and analyze water use data to forecast water demand.Kern0,5
Conduct feasibility studies for the construction of facilities, such as water supply systems, runoff collection networks, water and wastewater treatment plants, or wastewater collection systems.Kern0,5
Conduct environmental impact studies related to water and wastewater collection, treatment, or distribution.Kern0,5
Conduct cost-benefit analyses for the construction of water supply systems, runoff collection networks, water and wastewater treatment plants, or wastewater collection systems.Kern0,5
Analyze the efficiency of water delivery structures, such as dams, tainter gates, canals, pipes, penstocks, or cofferdams.Kern0,5
Analyze storm water or floodplain drainage systems to control erosion, stabilize river banks, repair channel streams, or design bridges.Kern0,5
Analyze and recommend sludge treatment or disposal methods.Kern0,5
Analyze and recommend chemical, biological, or other wastewater treatment methods to prepare water for industrial or domestic use.Kern0,5
Design water storage tanks or other water storage facilities.Kern0,5
Design water runoff collection networks, water supply channels, or water supply system networks.Kern0,5
Design water or wastewater lift stations, including water wells.Kern0,5
Design water distribution systems for potable or non-potable water.Kern0,5
Design sludge treatment plants.Kern0,5
Design pumping systems, pumping stations, pipelines, force mains, or sewers for the collection of wastewater.Kern0,5
Design domestic or industrial water or wastewater treatment plants, including advanced facilities with sequencing batch reactors (SBR), membranes, lift stations, headworks, surge overflow basins, ultraviolet disinfection systems, aerobic digesters, sludge lagoons, or control buildings.Kern0
Evaluate the operation and maintenance of water or wastewater systems to identify ways to improve their efficiency.Kern0,5
Perform mathematical modeling of underground or surface water resources, such as floodplains, ocean coastlines, streams, rivers, or wetlands.Ergänzend0,5

Berufsinformationen

Quellen und Namensnennung

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 17-2051.02 Water/Wastewater Engineers

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

Vollständige Namensnennung und Lizenzen