DOE · DOE-571 · record R3427
GitHub Co-Pilot
Department of Energy · RL - Hanford - Richland Operations Office - Hanford (EM)
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
- This AI system does not provide a principle basis for decisions or actions with legal, material binding, or have any significat effects of those items listed in OMB-25-21 in the definition of High Impact.
- Start date
- 2025-08-25 (day precision)Source: 2025-08-25T00:00:00
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Information Technology
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
quicker, more complete, and safer code development
Expected benefits
quicker, more complete, and safer code development
System outputs
text answers to input questions, code suggestions
Technology
- AI classification
- Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
- System name(s)
- Hanford Accreditation Boundary (HAB)
- Custom-developed code
- No
- Public source code
- Not reported
Sourcing
- How it was built
- Purchased from vendorSource: a) Purchased from a vendor
- Vendor (as reported)
- GitHub
- Vendors (standardized)
- GitHub
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
- Pretrained AI's with access to GitHub code repositiories
- Federal Data Catalog
- Not reported
Governance
7 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Pre-deployment testingReported in placeSource: a) Yes
AI impact assessmentNo answer reported
Independent reviewReported in placeSource: a) Yes – by another appropriate agency office or reviewer not directly involved in the AI’s development
Ongoing monitoringReported in progressSource: b) Development of monitoring protocols is in-progress
Operator trainingReported in progressSource: b) Establishment of sufficient and periodic training is in-progress
Fail-safeNot applicableSource: b) Not applicable
Appeal processNot applicableSource: b) Not applicable
User and public consultationReported in placeSource: a) Direct usability testing
Potential impacts and how they were identified
Potential impacts were assessed by the Hanford AI SME