HHS · no agency ID · record R0679

Semi-Automated Nonresponse Detection for Surveys (SANDS)

Department of Health and Human Services · HHS/CDC

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: 2022-09 (month precision)Source: Sep-22
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Health and Medical
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual review of open-ended survey responses is labor-intensive and cost-prohibitive at scale. SANDS automates the detection of nonresponses in survey data, reducing the burden on researchers and improving data quality.

Expected benefits

SANDS significantly reduces manual curation time for open-ended survey responses by providing automated scoring and flagging of nonresponses. This enables faster compilation of high-quality datasets for qualitative research and streamlines the review process for researchers.

System outputs

The system outputs scores for open-ended survey responses, identifying likely nonresponses and flagging responses that require further review. This helps improve survey data quality and informs questionnaire design.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): Not reported
Custom-developed code: Yes
Public source code: huggingface.co ↗

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: Not reported
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: 3,000 labeled open-ended responses to web probes on questions relating to the COVID-19 pandemic, gathered from the Research and Development Survey (RANDS) conducted by the Division of Research and Methodology at the National Center for Health Statistics.
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.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported