Free and Fair Commonsense Algorithms for Society is a platform for fair, open-source, and math-based algorithms for individual, commercial, and institutional use, built using cutting edge machine learning techniques and designed to improve the well-being of the individuals impacted by the algorithms.
This repository hosts a custom scikit-learn transformers python package for use with free-and-fair-common-sense-algorithms/algorithms.
Run:
python setup.py sdist bdist_wheel
To develop and promote fair, equitable, auditable, machine learning solutions that improve the quality of life for all people equally.
Free and Fair Commonsense Algorithms for Society (FAFCSAFS) was founded in 2020, during the era of big data and continuous technical advancement in machine learning. However, countless algorithmic solutions developed today are second-rate, costly, proprietary, and fail in providing improvements over non-algorithmic solutions, and in many cases, actually making the situation worse than before. This is why FAFCSAFS was established: to harness the power of the technological advancements of the era while not causing a detriment to society. FAFCSAFS provides individuals and organizations access to high-quality algorithmic solutions for various situations, focusing on situations where human biases can severely jeopardize any outcome and where fairness is paramount.
Free and Fair Commonsense Algorithms for Society (FAFCSAFS) is a community project. We invite your participation through the development of new algorithms to be featured on the website for anyone to use, or pull requests improving the development process and architecture, or website, or by submitting issues.
If you are interested in contributing, please read the contribution guide.
- Brian Clifton (project lead)