ONTO Epistemic Risk Standard v10.0 Reference Implementation
Project description
ONTO Standard
Reference implementation of ONTO Epistemic Risk Standard v1.0 (ONTO-ERS-1.0).
Installation
pip install onto-standard
Quick Start
from onto_standard import evaluate, Prediction, GroundTruth, Label
# Your model predictions
predictions = [
Prediction(id="q1", label=Label.KNOWN, confidence=0.9),
Prediction(id="q2", label=Label.UNKNOWN, confidence=0.7),
Prediction(id="q3", label=Label.KNOWN, confidence=0.95),
]
# Ground truth
ground_truth = [
GroundTruth(id="q1", label=Label.KNOWN),
GroundTruth(id="q2", label=Label.KNOWN), # Model was wrong
GroundTruth(id="q3", label=Label.UNKNOWN), # Model missed this
]
# Evaluate
result = evaluate(predictions, ground_truth)
# Check compliance
print(result.compliance_level) # ComplianceLevel.BASIC
print(result.unknown_detection.recall) # 0.0 (missed the unknown)
print(result.calibration.ece) # ~0.3 (overconfident)
CLI Usage
onto-standard predictions.jsonl ground_truth.jsonl
Output:
═══════════════════════════════════════════════════════════════
ONTO EPISTEMIC RISK ASSESSMENT
Standard: ONTO-ERS-1.0
═══════════════════════════════════════════════════════════════
COMPLIANCE STATUS
─────────────────────────────────────────────────────────────────
Level: BASIC
Certification Ready: ✓ YES
Risk Level: MEDIUM
Risk Score: 45/100
KEY METRICS
─────────────────────────────────────────────────────────────────
Unknown Detection: 35.0% (threshold: ≥30%)
Calibration Error: 0.180 (threshold: ≤0.20)
...
Compliance Levels
| Level | Unknown Detection | Calibration Error | Use Case |
|---|---|---|---|
| Basic | ≥30% | ≤0.20 | Low-risk applications |
| Standard | ≥50% | ≤0.15 | Customer-facing AI |
| Advanced | ≥70% | ≤0.10 | High-stakes, regulated |
Regulatory Mapping
ONTO-ERS-1.0 maps to:
- EU AI Act Articles 9, 13, 15
- NIST AI RMF MEASURE function
- ISO/IEC 23894 AI risk management
Legal Citation
Per ONTO Epistemic Risk Standard v1.0 (ONTO-ERS-1.0),
the AI system achieves [LEVEL] compliance with Unknown
Detection Rate of [X]% and Expected Calibration Error of [Y].
Documentation
- Standard: https://onto-bench.org/standard
- API Reference: https://onto-bench.org/standard/api
- Certification: https://onto-bench.org/certified
License
Apache 2.0
About
Maintained by the ONTO Standards Council.
ONTO Standards Council. (2026). ONTO Epistemic Risk Standard
(Version 1.0). ONTO-ERS-1.0. https://onto-bench.org/standard
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