One of the key benefits to managing and utilizing data more efficiently is that it enables the use of advanced capabilities such as artificial intelligence (AI) and machine learning (ML). The Department of Labor has recently begun exploration of how these advanced technologies can be used to benefit the agency and help deliver on our mission. In an effort to create transparency in the adoption of these tools, this page serves to highlight the various uses of AI across the department.
Active AI Use Cases
| AI Use Case Name | Summary of Use Case | Stage of Development | AI Technique |
|---|---|---|---|
| AI Use Case Name Form Recognizer for Benefits Forms | Summary of Use Case Custom machine learning model to extract data from complex forms to tag data entries to field headers. The input is a document or scanned image of the form and the output is a JSON response with key/value pairs extracted by running the form against the custom trained model. | Stage of Development In production: less than 6 months | AI Technique Classification machine learning model involving computer vision |
| AI Use Case Name Claims Document Processing | Summary of Use Case To identify if physician’s note contains causal language by training custom natural language processing models. | Stage of Development In pilot (not in production) | AI Technique Natural language processing for (a) document classification and (b) sentence-level causal passage detection |
| AI Use Case Name Website Chatbot Assistant | Summary of Use Case The chatbot helps the end user with basic information about the program, information on who to contact, or seeking petition case status. | Stage of Development Planned (not in production) | AI Technique Cloud based chat bot building tool |
| AI Use Case Name Data Ingestion of Payroll Forms | Summary of Use Case Custom machine learning model to extract data from complex forms to tag data entries to field headers. The input is a document or scanned image of the form and the output is a JSON response with key/value pairs extracted by running the form against the custom trained model. | Stage of Development Planned (not in production) | AI Technique Classification machine learning model involving computer vision |
| AI Use Case Name Hololens | Summary of Use Case AI used by Inspectors to visually inspect high and unsafe areas from a safe location. | Stage of Development In production: more than 1 year | AI Technique |
| AI Use Case Name SOII Computer-Assisted Coding | Summary of Use Case The Survey of Occupational Injuries and Illnesses (SOII) collects hundreds of thousands of narratives describing cases of work-related injury and illness annually. Coders manually assigned classifications for worker occupation, nature of injury, part of body, event or exposure, source, and secondary source for each case until 2012, when the Occupational Safety and Health Statistics (OSHS) program developed machine-learning autocoders to make some assignments. Use of these autocoders subsequently expanded and coded 85% of all SOII elements for reference year (RY) 2019. This gradual increase occurred by adapting the selection criterion based on careful monitoring of the processes. This monitoring allowed the coding to expand to all six elements coded (occupation, nature, part, event, source, secondary source). | Stage of Development In production: more than 1 year | AI Technique Machine learning/natural language processing - deep neural networks with character-level convolutional embeddings and Long-Short-Term-Memory recurrent layers (source code is available on DOL's Github at https://github.com/USDepartmentofLabor/soii_neural_autocoder) |
Contact Us
U.S. Department of Labor
200 Constitution Ave NW
Suite N-1301
Washington, DC 20210
Responsible AI Official: Krista Kinnard
Email: Kinnard.Krista.N@dol.gov