Feedback Analysis Solution (FAS)
Description
Speeds up the manual and time-consuming process of analyzing public comments on frequently posted regulations.gov and FDMS dockets by employing advanced natural language processing and machine learning technologies.
Detailed example
FAS categorize stakeholder feedback (collected in multiple venues), thereby enabling CMS analysts to use the system to quickly identify comments that may impact program/policy decisions. The system utilizes Artificial Intelligence (AI) to minimize bias through topic, theme, stakeholders, and sentiment models that standardize the analysis process, and provide insights that were previously difficult to obtain manually.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Speeds up the manual and time-consuming process of analyzing public comments on frequently posted regulations.gov and FDMS dockets by employing advanced natural language processing and machine learning technologies. FAS help categorize stakeholder comments or feedback (collected in multiple venues), thereby enabling analysts to use the system to quickly identify comments that may impact program/policy decisions.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Use API to comments from Regulations.gov, FDMS, Federal Register.