NASA · NASA-545 · record R0281
Implement machine learning in NMIS to assist with mishap coding
National Aeronautics and Space Administration · OSMA: Office of the Chief Safety & Mission Assurance
Overview
- Development stage
- PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- 2026-03-30 (day precision)Source: 03/30/2026 00:00:00
- Withheld from public reporting
- Yes (disclosure risk)Source: b) Yes – agency has determined that there’s a risk to disclosure, such as a harm to an interest protected by a FOIA exemption
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Leverage Machine Learning to train computers to review mishap and close call data in NMIS to suggest event coding characteristics to help mishap program managers classify events more efficiently.
Expected benefits
Reduce manual work, increase time and efficiency, and free up skilled subject matter experts for more complex tasks.
System outputs
Suggested mishap findings and mishap event classifications.
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)
- Code V DATA CENTER
- 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
- Mishap event data, finding data, corrective action data, mishap classification data
- 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