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Large People ModelHuman Operating Architecture
Manual assessmentAI Amplificationpercent

Human-in-the-loop clarity

The share of AI-touched decisions with an explicit autonomy level and defined oversight.

Formula

Oversight clarity coverage

(AI-touched decisions with autonomy level and oversight defined / total AI-touched decisions) * 100

Unit

percent

Direction

Higher is better

Cadence

Monthly for AI programs.

Numerator

AI-touched decisions with explicit autonomy and oversight

Denominator

Total AI-touched decisions

Worked Example

AI decision oversight review.

AI-touched decisions

31

Decisions with explicit oversight

14

Calculation

14 / 31 * 100

Result

45.2%

Interpretation

Humans may not know when to review, approve, or intervene.

Recommended action

Define oversight and autonomy levels before increasing AI scope.

Why it matters

This metric helps leaders see whether the ai amplification layer is healthy enough to support execution and AI readiness.

What it reveals

Whether humans know when AI supports, recommends, acts, or requires approval.

Manual assessment method

Classify AI-touched decisions by autonomy level and identify oversight requirements.

Lapemo calculation path

Supported by autonomy level, gate thresholds, supervisors, and AI-touched decision types.

Interpretation Bands

Healthy

85-100%

Strong enough for normal operating review.

Watch

70-84%

Usable, but gaps should be assigned owners.

Risk

50-69%

Weak enough to slow execution or create risk.

Critical

<50%

Do not scale the related workflow without intervention.

Required inputs

  • AI-touched decision list
  • Autonomy level
  • Oversight owner
  • Approval rule

Data sources

  • AI governance checklist
  • Decision Rights Matrix
  • Agent accountability checklist

Common pitfalls

  • Saying human-in-the-loop without naming the loop
  • Ignoring autonomy levels

Recommended actions

  • Define autonomy tiers
  • Assign oversight owners
  • Add approval gates

Measure Before You Scale

Measure the operating model before AI amplifies it.

Use the Metrics Library to understand what to diagnose, what to monitor, and where Lapemo can turn framework metrics into operating intelligence.