DOE · DOE-499 · record R3360
Argo
Department of Energy · ANL - Argonne National Laboratory (SC43 OIM)
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
- Impact of system failure or erroneous results is negligible.
- Start date
- 2023-11-01 (day precision)Source: 2023-11-01T00:00:00
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Other
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Broad usage across science and lab-ops for use cases that could benefit with genAI techniques.
Expected benefits
Enables anyone within the Argonne community to leverage text-based generative AI with their Argonne-specific information and data, including sensitive research or operational data up to and including CUI.
System outputs
Large language model responses (prediction-based) following user prompting.
Technology
- AI classification
- Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
- System name(s)
- Argonne National Laboratory Information Technology Infrastructure
- 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
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Yes
- Demographic features
- Not reported
- Training and evaluation data
- N/A – we are using existing pre-trained large language models, no training required.
- Federal Data Catalog
- No
Governance
6 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 reviewNo answer reported
Ongoing monitoringReported in progressSource: b) Development of monitoring protocols is in-progress
Operator trainingReported in placeSource: a) Yes, sufficient and periodic training has been established
Fail-safeReported in placeSource: a) Yes
Appeal processNot applicableSource: b) Not applicable
User and public consultationReported in placeSource: a) Direct usability testing
Potential impacts and how they were identified
Not reported