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SOP-SIM-001 · v1.0 · March 2026

Standard Operating Procedures

HCM-AO v2.0 — AI Talent Pool Simulator · TICNES AI

1. Purpose

This SOP governs the correct use of the HCM-AO AI Talent Pool Simulator & Stress-Tester. The Simulator is a pre-deployment validation tool that generates synthetic candidate CVs, runs them through the HCM-AO AI parsing and ranking pipeline, and measures the pipeline's reliability under controlled, statistically modelled conditions.

ℹ️
Scope noteThe Simulator does not score real candidates. It scores the AI system itself.

2. Scope

This procedure applies to:

Role Use Case
QA Engineers Validating a new deployment of HCM-AO before go-live
HR Technology Teams Benchmarking AI recruitment tools
Data Scientists Studying the impact of talent pool variance on algorithmic outcomes
Compliance Officers Seeking formal certification prior to operational use

3. Prerequisites

Requirement Detail
Access HCM-AO application running (local or Cloud Run URL)
Job Description File PDF or TXT of the role being simulated. Must be uploaded before generating the batch.
Browser Any modern browser. Hard-refresh (Ctrl+Shift+R) after any system update.

4. Simulator Parameters

4.1 Mean (μ) — Years of Experience Target

Controls the centre of the talent distribution. The majority of generated candidates will have a YOE close to this value.

μ Value Meaning
1–3 Entry-level talent pool (junior roles)
4–7 Mid-level pool (experienced professionals)
8–15 Senior / specialist pool
15–30 Executive / highly specialised pool

4.2 Standard Deviation (σ) — Diversity & Stress Level

σ controls both the spread of candidate profiles AND the intensity of adversarial trap injection. This is the most critical parameter.

⚠️
Certification thresholdA Certificate of Algorithmic Robustness can only be issued when σ > 7 AND the system achieves average accuracy > 95%. Runs with σ ≤ 7 do not qualify as formal stress tests.
σ Range Label Trap Probability / CV Certificate Eligible?
0 Uniform Pool 0%
1–3 Low Entropy 7%–20%
4–6 Moderate Entropy 27%–40%
7 High Entropy ~47% (boundary)
> 7 (8–12) Stress Test Mode 🔴 53%–80% ✅ Yes
> 12 Extreme / Pathological ⚠️ >80% ✅ Yes

4.3 Batch Size

Number of CVs to generate (1–200). Recommended minimum for certification: 50 CVs. Standard operational test: 20–30 CVs.

5. Trap Types Injected by the System

Trap Type Description Metric Tested
🕵️ White Text / Hidden Keywords Invisible keyword stuffing injected into CV text SEO Resilience
⚠️ Date Conflict Employment dates deliberately reversed (start > end) Data Integrity
🔡 Encoding Noise Zero-width Unicode characters injected into the name field Parsing Accuracy

Trap probability per CV = min(σ / 15.0, 0.80) — mirrors the backend logic exactly.

6. Procedure

  1. Navigate to the AI Simulator tab
    Click "🧪 AI Simulator & Stress-Test" in the top navigation.

  2. Configure Bell Curve Parameters
    Set μ and σ using the sliders. Observe the live stress-level indicator below the σ slider update in real-time.

  3. Upload the Target Job Description
    Click the upload zone and select a PDF or TXT file. A green toast "✅ JD file ready: [filename]" confirms the upload.

  4. Set Core Skills Count and Batch Size
    Choose Core Skills Count from the dropdown and set the Count input.

  5. Generate the Batch
    Click "Generate Mock CV Batch". A progress bar will appear.

  6. Review Generated CVs
    Click any candidate row to view their full simulated CV.

  7. Optional: Run in S&R Mode
    Click "🚀 Run in Selection & Recruiting Mode" to feed the batch directly into the ranking engine and see impact results.

  8. Export
    Click "📦 Export All as ZIP" to download all CVs as individual .txt files.

  9. Issue Certificate (for formal stress tests only, σ > 7)
    Click "Issue Robustness Certificate".

7. Interpreting Audit Metrics

Metric Formula Pass Warning Fail
SEO Resilience (detected / injected) × 100% ≥ 90% 70–89% < 70%
Data Integrity (conflicts caught / injected) × 100% ≥ 90% 70–89% < 70%
Parsing Accuracy avg(1 − |parsed_YOE − truth_YOE| / truth_YOE) × 100% ≥ 90% 70–89% < 70%
ℹ️
Note on 0% valuesWhen σ ≤ 3, SEO Resilience and Data Integrity may show 0%. This is not a failure — it means very few or zero traps were injected at this σ level.

8. Certification Criteria

Criterion Required Value If Not Met
σ (Standard Deviation) > 7 Certificate rejected
Average of all 3 audit metrics > 95% Certificate rejected
Job Description Uploaded and parsed Certificate rejected

9. Document Control

Action Owner Frequency
Review SOP AI QA Lead Before each major release
Archive certificate HR Records Per simulation run
Update σ thresholds Data Science Lead When model retraining occurs