Resources related to Watson OpenScale

Examining the susceptibility of Fairness Measures to various scenarious of data imbalance

Codebase for "Fair-GAIN" for fair ML predictions.

FACT-AI (Fairness, Accountability, Confidentiality, and Transparency in AI) Project on Debiasing word embeddings

[Official Codes] Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation (RecSys 22)

Hmumu classifiers trained to be fair w.r.t. the invariant mass.

The aim of the project is to apply different global, local and performance interpretability methods as well as model fairness evaluations to a dataset with protected attributes. The dataset regards traffic violations in Montgomery, Maryland, USA. This is a fork of a group project of my Data Science for Business Master's Degree at HEC Paris.

Trustworthy AI/ML course by Professor Birhanu Eshete, University of Michigan, Dearborn.

Human in the Loop

🔍In recent years the advancement of ML (machine learning) increased automation for tasks in different domains. One of the challanges was an issues with job recruitment systems that demonstrated bias toward female applicants [4]. This repo will investigate some of the techniques used to overcome these challenges. 👨🏽‍🔧

Affevtive Bias in Large Pre-trained Language Models

Fairness in Digital Image Forgery Detection System

FairPy: A Python Library for Machine Learning Fairness

AI fairness checker

All the material needed to implement FairVIC for bias mitigation in deep neural networks.

Building Fair AI models tutorial at PyData Berlin / REVISION 2018

Report for INFO4900 Independent Research under Prof. Dawn Schrader. Surveyed bias detection and mitigation methods in language models. Identified emerging Language Model tasks where existing mechanisms fail. Designed a novel fairness test and proposed a framework to update large language models when what society considers fair changes.