DOL · DOL-19 · record R1289

OEWS Occupation Autocoder

Department of Labor · BLS

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Used for survey processing for statistical purposes
Start date: 2018-01-01 (day precision)Source: 01/01/2018 00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Other: Applied Mathematical SciencesSource: Other - Applied Mathematical Sciences
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The input is state-submitted response files that include occupation title and sometimes job description of the surveyed units. The autocoder reads the job title and assigns up to two 6-digit Standard Occupational Classification (SOC) codes along with their probabilities as recommendations for human coders. Codes above a certain threshold are appended to the submitted response file and sent back to states to assist them with their SOC code assignment.

Expected benefits

Improving data accuracy and saving time for SOC coders

System outputs

6-digit Standard Occupational Classification (SOC) codes

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): BLS Internal system
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Agency Generated
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported