Aequitas is an open-source bias audit toolkit for machine learning developers, analysts, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and deploying predictive risk-assessment tools.
Explore bias analysis of the COMPAS data using the Aequitas library.
Find documentation here.
Aequitas requires Python 3.
Install this Python library from source:
python3 setup.py install
...or named as an installation requirement, e.g. via pip:
pip3 install git+https://github.com/dssg/aequitas.git
You may then import the aequitas module from Python:
import aequitas
...or execute the auditor from the command line:
aequitas-report
Provision your development environment via develop:
./develop
Common development tasks, such as deploying the webapp, may then be handled via manage:
manage --help
Find more at the documentation.
To contact the team, please email us at [aequitas at uchicago dot edu]
© 2018 Center for Data Science and Public Policy - University of Chicago