long-term-impact-of-fairness-constraints

This repository can be used for analysing the long-term impact of static fairness constraints.

• The functions and classes for our model are in "fico_util.py", "util.py", and "eq_odds.py".
• We present the applications of our model with Jupyter notebook.
• The figure in the FICO experiment is plotted by Matlab. The code is in the folder "FICO_fig".

Installation

Step 1: Install Python 3.

Step 2: Intall pip.

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
python get-pip.py

Step 3: Install Jupyter notebook.
pip install notebook

Step 4: Install the following packages. fairlearn, tempeh, numpy, pandas, scipy, sklearn, matplotlib, cvxpy, pynverse, random, copy, progressbar, collections
pip install XXX (replace XXX with the name of packages)

Step 5: Restart the Jupyter Notebook and run the code.

notebooks

The synthetic data, FICO, and COMPAS experiments are shown in the folder notebook.

COMPAS_Fig

Figures and results of COMPAS experiment.

FICO_fig

Figures and results of FICO experiment.