HHS · no agency ID · record R0912

DAIT AIDS-Related Research Solution

Department of Health and Human Services · HHS/NIH

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: 2018-01 (month precision)Source: Jan-18
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: Document processing and extraction Derived by keyword rules; see methodology

Problem the AI is intended to solve

DAIT POs need to identify grant applications that involve AIDS-related research (ARR) so they can evaluate them for additional funding.

Expected benefits

DAIT ARR suggests prioritization of grant applications that are likely to include AIDS-Related Research to assist POs in prioritizing which grants to select, which improved the review time and quality of review for ARR applications.

System outputs

This application extracts text from grant applications as input, and then uses classification models to predict the priority and category of each grant application as the output. The output is shared along with other grant application metadata in a custom module.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): DAIT AIDS-Related Research Solution
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): Deloitte
Vendors (standardized): Deloitte

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: A dataset was curated to train the model and is evaluated manually by user input.
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