Governance and accountability
Governance evidence
What agencies reported about the OMB M-25-21 minimum practices for high-impact AI. This is a disclosure analysis, not an audit, a compliance finding or an official assessment. An unanswered question is missing evidence, not evidence that a safeguard is absent.
Practice-by-practice evidence
Denominator: 17 records · all use cases in the current filterReported in placeNot applicableNo answer reported
Pre-deployment testing
Pre-deployment testing
Reported in place: 2 (11.8%)Pre-deployment testing
No answer reported: 15 (88.2%)
17Reported in place: 2 (11.8%)Pre-deployment testing
No answer reported: 15 (88.2%)
AI impact assessment17
Independent review17
Ongoing monitoring17
Operator training17
Appeal process
Appeal process
Reported in place: 1 (5.9%)Appeal process
Not applicable: 1 (5.9%)Appeal process
No answer reported: 15 (88.2%)
17Reported in place: 1 (5.9%)Appeal process
Not applicable: 1 (5.9%)Appeal process
No answer reported: 15 (88.2%)
User and public consultation
User and public consultation
Reported in place: 2 (11.8%)User and public consultation
No answer reported: 15 (88.2%)
17Reported in place: 2 (11.8%)User and public consultation
No answer reported: 15 (88.2%)
| Practice | In scope | In place | In progress | Not in place | N/A | Precluded or waived | Other | No answer | Answered | In place of applicable |
|---|---|---|---|---|---|---|---|---|---|---|
| Pre-deployment testing | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
| AI impact assessment | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
| Independent review | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
| Ongoing monitoring | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
| Operator training | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
| Fail-safe | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
| Appeal process | 17 | 1 | 0 | 0 | 1 | 0 | 0 | 15 | 12% | 6% of 16 |
| User and public consultation | 17 | 2 | 0 | 0 | 0 | 0 | 0 | 15 | 12% | 12% of 17 |
Answered = records with any answer ÷ records in scope. In place of applicable = reported in place ÷ (in scope minus not applicable, precluded and waived). Unanswered records stay in that denominator, so the rate is a lower bound on reported evidence, not an estimate of real practice.
| Testing | Impact assess. | Indep. review | Monitoring | Training | Fail-safe | Appeal | Consultation | n | |
|---|---|---|---|---|---|---|---|---|---|
| NASA | – | – | – | – | – | – | – | – | 6 |
| DOT | – | – | – | – | – | – | – | – | 4 |
| DHS | 50% | 50% | 50% | 50% | 50% | 50% | 33% | 50% | 4 |
| USDA | – | – | – | – | – | – | – | – | 1 |
| DOI | – | – | – | – | – | – | – | – | 1 |
| DOE | – | – | – | – | – | – | – | – | 1 |
Hatched cells: the agency answered nothing for that practice, so there is no evidence either way. Compare agencies with care: each agency is one reporting unit, and portfolios differ in size and type.
Records requiring further investigation
15 records with at least one practice unanswered or in progressOpen in explorer| Use case | Stage | Test | AIA | Review | Monitor | Train | Fail-safe | Appeal | Consult |
|---|---|---|---|---|---|---|---|---|---|
| Aircraft Landing Location Predictor (KESTREL) DHS · DHS-65 | Deployed | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Certified Professional Controller (CPC) On-Board Success Evaluator DOT · DOT-1000008 | Deployed | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Predictive flood modeling USDA · USDA-082 | Deployed | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| OTA Automated Passenger Screening Gate System DHS · DHS-2397 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Managing curb allocation in cities DOE · DOE-357 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Improving recreation opportunities and access to public lands through machine learning and transportation planning DOI · DOI-0104 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Automated Delay detection using voice processing DOT · DOT-1000009 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Technical Operations Predictive Maintenance DOT · DOT-1000010 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Predictive Analytics Using Autonomous Track Geometry Measurement System (ATGMS) Data DOT · DOT-1000035 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Explainable and robust deep semi-supervised model for multi-class anomaly detection in flight data NASA · NASA-11 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Machine Learning Airport Surface Model: Airport Configuration Prediction NASA · NASA-18 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Machine Learning Airport Surface Model: Arrival Runway Prediction NASA · NASA-19 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Machine Learning Airport Surface Model: Departure Runway Prediction NASA · NASA-20 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Machine Learning Airport Surface Model: Taxi-out Prediction NASA · NASA-23 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
| Unsupervised anomaly detection in flight data with deep variational autoencoders NASA · NASA-33 | Pre-deployment | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported | No answer reported |
Unanswered analytical questions
Generated from the data; for follow-up with agencies- 1 high-impact use cases mark an appeal process as not applicable. On what basis was each individual outcome judged not contestable?
These are questions the inventory raises but cannot answer. They are not findings of non-compliance.