A pilot project has shown the potential to speed up and improve agencies’ analysis of public comments on rules they propose, the chief data officers council has said.
A posting on cdo.gov notes that agencies publish tens of thousands of pages of proposed rules annually, which in turn result in millions of comments. In reviewing those comments, it says, agencies face issues including determining if comments were submitted as part of a mass mail campaign, which aspects of the proposed regulation a comment addresses, and how to route comments to subject matter experts for their review and response.
The council said that working with partner agencies, it developed analytic tools using natural language processing technology that can identify the topics and themes in a comment and identify and group those that contain similar themes or ideas, including those that are duplicates or near duplicates.
“These tools offer significant value at the agency level by helping reviewers respond to comments more quickly and easily. They can also offer new and better insights to comment analysts – for example, stakeholders indicated that identifying the meaning or ideas within groups of comments would benefit their review. Cost savings can be realized as agencies gain efficiencies and reduce up-front costs of comment analysis tool development,” it said.
“From a government-wide perspective, sharing these tools can improve development efforts at individual agencies. Services such as Regulations.gov/FDMS have created many cross-agency efficiencies in the rulemaking space. This pilot suggests the potential to create additional efficiencies and standardize comment analysis tools across the federal government by leveraging the latest in NLP advancements in technology,” it said.