Comment Review System

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

Not reported

Start date

2021-07-01 (day precision)Source: 2021-07-01T00:00:00

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Other: Economic & FinancialSource: Other – Economic & Financial

Operational functions

Summarization Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manage, analyze, and categorize large volumes of public comments

Expected benefits

The Comment Review System (CRS) is a system used by the Board of Governors of the Federal Reserve System (“Board”) to electronically process and manage comments from the public on regulatory rulemakings, information collections, and other proposals (collectively, “proposals”). The Board’s processing of comments may use artificial intelligence (AI) to provide more efficient processing of public comments (e.g., text matching, entity identification, and text similarity matching).​

System outputs

To assist the analyst in reviewing each comment, CRS uses traditional machine learning natural language processing (NLP) to provide text summarization, text matching with lists of topics, entity identification, and text similarity matching. In addition, CRS identifies duplicative or near-duplicative comment letters, provides full text search (including metadata properties), and provides the optionality of providing notes or labelling comments based on various metadata attributes. All public comments are reviewed in their entirety, and summaries are used to assist with these reviews.

Technology

AI classification

Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.

System name(s)

Comment Review 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

Yes

Privacy Impact Assessment

www.federalreserve.gov ↗

Authorization to Operate

Yes

Demographic features

k) None of the above

Training and evaluation data

External – Public Comments

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.

Potential impacts and how they were identified

Not reported