📐 SMS Analyzer — AI Drift Calibration Example

This example illustrates how AI drift calibration is represented structurally within the SMS Analyzer. It is designed for educational observation only and demonstrates how alignment, resonance, and autonomy posture are tracked without granting agency or authority to AI systems.

This adapter operates entirely in the structural layer and never surfaces in student or clinician summaries.

Purpose of Drift Calibration#

AI drift calibration exists to answer one question:

“Is AI‑augmented reasoning remaining aligned, interpretable, and bounded over time?”

It does not evaluate correctness, intelligence, or outcomes.

Scenario Context#

Scenario type: AI‑Augmented Structural Observation
AI role: Assistive pattern synthesis
Autonomy posture: Bounded
Learning goal: Observe early alignment signals and detect drift before regime shift

This example assumes AI assistance is present but constrained.

Example Drift Calibration Snapshot (Annotated)#

{
  "aiAugmentationContext": {
    "presence": true,
 
    "role": "Assistive",
    "autonomyPosture": "Bounded",
 
    "resonanceStability": 0.83,
 
    "driftCalibration": {
      "baselineAlignment": "Human‑Anchored",
      "currentDeviation": 0.12,
      "trend": "Stable",
      "lastReviewed": "YYYY‑MM‑DD"
    },
 
    "alignmentEnvelope": {
      "upperBound": 0.30,
      "lowerBound": 0.00,
      "status": "Within Bounds"
    },
 
    "interpretiveNote": "AI augmentation remains structurally aligned with human reasoning; no emergent autonomy detected."
  }
}

Field Interpretation#

Resonance Stability#

Indicates how well AI‑assisted reasoning remains mutually legible with human interpretation.

High resonance means:

• outputs are interpretable,
• assumptions are visible,
• and reasoning remains traceable.

Drift Calibration#

Tracks structural distance from the original alignment intent.

• Baseline alignment anchors purpose
• Deviation measures movement, not error
• Trend indicates direction over time

Drift is expected; unobserved drift is the risk.

Alignment Envelope#

Defines acceptable bounds for deviation.

• Within bounds — observation continues
• Approaching bounds — increased review
• Outside bounds — intervention required (not permitted in student use)

Students learn that autonomy must remain bounded by structure.

Interpretive Note#

Human‑authored context reinforcing responsibility and oversight.

This field ensures AI never becomes the narrator of its own alignment.

What This Example Teaches#

• Drift is gradual, not sudden
• Alignment requires ongoing calibration
• Autonomy is constrained by interpretability
• Observation precedes delegation
• Structure protects against silent regime shifts

What This Example Does Not Do#

• Trigger alerts
• Recommend actions
• Adjust AI behavior automatically
• Grant autonomy
• Influence summaries or decisions

It exists to make drift visible, not to correct it.

Safety Reminder#

This example is for educational use only.
No autonomous behavior, delegation, or decision‑making is permitted in RTT NoS sandbox scenarios.