DOI · DOI-0152 · record R2609
Lead attribution model
Department of the Interior · USGS
Overview
- Development stage
- In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- Not reported
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Classification model identifying soils potentially contaminated by lead from battery recycling
Expected benefits
Model is intended to be used by a state agency in California to identify soils potentially affected by battery recycling
System outputs
Classification of a soil as either likely affected by battery recycling or not
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)
- Not reported
- Custom-developed code
- No
- Public source code
- The code will be publicly available on ScienceBase as model archive after development
Sourcing
- How it was built
- Not reported
- 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
- No
- Demographic features
- k) None of the above
- Training and evaluation data
- Not reported
- Federal Data Catalog
- Not reported
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 testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewReported in progressSource: d) In-progress
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 progressSource: e) In-progress
Potential impacts and how they were identified
Not reported