**Code Repository for “A Designed look at Artificial Intelligence from the Lens of
Fairness”**



This repository contains the Python code used to reproduce the simulation study presented in the manuscript.

All analyses were implemented in Google Colab, and the notebook is structured to run end-to-end in that environment without modification.



**Contents**

fairness\_simulation.ipynb

Primary notebook containing the complete workflow, including data generation, model fitting, and figure \& table generation.



**Execution Instructions**

Google Colab (Recommended Execution Environment)

Open fairness\_simulation.ipynb in Google Colab.

Select Runtime → Run all.

Output files will be saved automatically.



**Software Requirements**

The code requires Python 3.10–3.12.

The following packages are imported and must be available:

numpy

pandas

scikit-learn

matplotlib

seaborn

textwrap (standard library)

os (standard library)

google-colab (only required when running in Colab)



**Reproducibility**

Randomness is controlled by fixed seeds

No external data files are needed.

A clean Colab session is sufficient to regenerate all manuscript results.



**Correspondence**

For inquiries regarding the code or simulation design:

Md Borhan Uddin

Department of Mathematics and Statistics

Washington State University

Email: mdborhan.uddin@wsu.edu

