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Les pages d’organisations montrent qui exploite les systèmes, quelles preuves publiques existent et quelles questions restent ouvertes.
Ouvrez un système pour voir qui est concerné, quelle source soutient l’affirmation et si une personne peut revoir ou corriger une erreur.
Automatic analysis of recorded calls made to Benefits Advisors in the DOL Interactive Voice Repsonse (IVR) center.
Web Scraping to Identify Potentially Fraudulent Multiple Employer Welfare Arrangements (MEWAs)
The Census of Fatal Occupational Injuries (CFOI) collects and publishes a complete count of work-related fatal injuries and descriptive data on their circumstances.
Statistical coding assistance; human review; no impact on rights or benefits.
Imputes missing expenditure values in the Consumer Expenditure Interview Survey when respondents answer "don't know" or refuse to provide an expense amount.
Identify and describe electronic documents received by EBSA investigators for formal investigations - save time by automating the first phase of the document review process
Inspection: An AI headset offers a hands-free, voice-controlled solution that enhances the efficiency, safety, and accuracy of MSHA inspectors using the Inspection Application System (IAS).
Identification of an anomaly,Not pursuing in 2025; discontinued pre-deployment
Automatic Data Processing Workflow with Form Recognizer (9130/9178 Reconciliation Project)
Process automation only, Not pursuing in 2025; discontinued pre-deployment
Using Amazon Web Services Personal Identifying Information scrubber for ITA text fields and Named Entity Recognition to remove additional names from the text fields.
Process automation,Not pursuing in 2025; discontinued pre-deployment
Recommends price tolerance boundaries for industries based on historical and seasonal trends.
Automates review of grant documents to detect anomalies, delays, and compliance issues.
The Worker PLUS model was developed as an evolutionary iteration of the Paid Family and Medical Leave Simulator Model developed by Albelda and Clayton-Matthews (the ACM model)
BLS establishment-based surveys, such as the Survey of Occupational Injuries and Illnesses (SOII), the National Compensation Survey (NCS), and the Occupational Requirements Survey (ORS), use the Longitudinal Database...
Read-only, informational chatbot: draws from authoritative sources and case-status data, makes no determinations
Does not involve sensitive data or direct impact on individuals' rights or access to services, Not pursuing in 2025
Meeting NARA metadata standards for (permanent) federal documents by using AI to identify data within the document, and also using NLP to classify and summarize documents.
Code suggestions only; mandatory human review; no automated decisions, Not pursuing in 2025
It does not involve sensitive data It does not directly affect individuals' rights or access It is used for administrative summarization, not decision-making
The input is state-submitted response files that include occupation title and sometimes job description of the surveyed units.
The Survey of Occupational Injuries and Illnesses (SOII) collects hundreds of thousands of narratives describing cases of work-related injury and illness annually.
The bot will take the transcript and summarize the meeting notes
Recommends expense classification categories for Consumer Expenditure Interview Survey expense responses.
The Occupational Requirements Survey (ORS) collects and publishes information about specific work-related requirements.
The Natural Language Processing tool is intended to be a conversational query and synthesis tool that summarizes and synthesizes evaluation and technical assistance reports, as well as responses to requests for public...
AI used to train Inspectors to visually inspect unsafe areas from a safe location.
Assigns expense classification categories to reported expenses from Consumer Expenditure Diary Survey respondents.
Many comments submitted through the BLS.gov customer satisfaction survey are not actionable (i.e., do not provide an issue or explanation of what could improve the user experience).
The AI is intended to allow the claims examiner more time to focus on more critical adjudication tasks.
Private and secure in-house solution to evaluate business use cases that can solve problems using Generative AI models and semantic search.
BLS receives bulk data from some corporations related to the cost of goods they sell and services they provide.
This use case cuts down on the number of emails that ODEP's WRP team needs to respond to in their program inbox, wrp@dol.gov.
The BLS productivity office publishes measures of hours worked by major sector and industry.
The primary data source for the Quarterly Census of Employment and Wages (QCEW) is administrative data from state unemployment insurance programs.
It's an AI-powered search assistant that retrieves and summarizes content from internal DOL sources to assist with information discovery.