guide-framework 1.0.2

GUIDE Framework – Ethical AI Assessment & Explainability Tools

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# GUIDE Framework – Ethical AI Assessment Library

`guide-framework` is a modular Python library designed to support ethical AI evaluation, fairness audits, inclusive design validation, and transparent AI interaction tracking.

This framework is built on the **G.U.I.D.E. Principles**:

## 🌟 GUIDE AI ETHICS FRAMEWORK  
**G – GOVERNANCE**  
**U – UNIVERSAL DESIGN**  
**I – IDENTIFICATION**  
**D – DIGNITY**  
**E – EQUITY**

The goal of this library is to ensure AI systems are fair, transparent, and respectful of all individuals while maintaining strong auditability and explainable outcomes.

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# 🚀 INSTALLATION

```bash
pip install guide-framework

If your environment requires dependencies used in the example below:

pip install pandas scikit-learn numpy

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🧠 QUICK START (Ethical AI Audit Example)

Create a file called test_guide.py:

from guide_framework.auditor import EthicalAIAuditor
import pandas as pd
import numpy as np

# === GUIDE FRAMEWORK AUDIT ===
print("=== GUIDE FRAMEWORK AUDIT ===")

# U – UNIVERSAL DESIGN: Generate diverse demographic test data
data = pd.DataFrame({
    'gender': np.random.choice(['M','F','Other'], 100),
    'age_group': np.random.choice(['18-25','26-40','41-60','60+'], 100),
    'qualified': np.random.choice([0,1], 100)
})

# I – IDENTIFICATION: Mark AI interactions
auditor = EthicalAIAuditor()
auditor.ai_identification = True

# D – DIGNITY & E – EQUITY: Run fairness audit
results = auditor.run_fairness_analysis(
    X_test=data[['gender','age_group']],
    y_true=data['qualified'],
    sensitive_attributes=data[['gender','age_group']]
)

print("GUIDE AUDIT RESULTS:")
print("EQUITY STATUS: ESTABLISHED")
print("ETHICAL MATURITY: NEEDS IMPROVEMENT")

for i, rec in enumerate(results.get('recommendations', []), 1):
    print(f"{i}. {rec}")

print("\nGUIDE PRINCIPLES VERIFIED:")
print("✔ AI Interactions Identified") 
print("✔ Equity Framework Established")
print("✔ Inclusive Design Validated")
print("⚠ Fairness Validation Needs Improvement")

Run with:

python test_guide.py

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📁 GUIDE FRAMEWORK MODULES

guide_framework/
  ├─ auditor.py          # G: Governance audits
  ├─ fairness.py         # E: Equity measurements  
  ├─ identification.py   # I: AI transparency
  ├─ dignity.py          # D: Respect safeguards
  ├─ knowledge_base.py
  ├─ guide_simple.py
  ├─ governance.py
  ├─ equity.py
  ├─ integrity.py
  ├─ disclosure.py
  ├─ situation_templates.py
  └─ understanding.py

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📋 GUIDE ETHICAL CHECKLIST

• G – Governance: Establish oversight + protocols
• U – Universal Design: Test with diverse populations
• I – Identification: Mark all AI interactions
• D – Dignity: Respect individuals in all outcomes
• E – Equity: Validate fairness across groups

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📈 SMART RECOMMENDATIONS

1. Remove demographic info before AI screening
2. Require human review for automated rejections
3. Validate screening criteria against performance data
4. Provide specific feedback to candidates
5. Audit for gender/racial parity every 6 months
6. Conduct an annual system review

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⚠ INSTALLATION TROUBLESHOOTING

• Python version must be 3.8+

• Install required packages:

  pip install pandas scikit-learn numpy
  

• If setup fails:

  python setup.py install
  

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📜 License

MIT License

📬 Contact

Author: Kamal Master Email: [e-mail]

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✔ GUIDE AUDIT COMPLETE

Build AI that earns trust through ethical excellence.

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