bias

A collection of inspiring resources related to engineering management and tech leadership

XAI - An eXplainability toolbox for machine learning

Bias and Fairness Audit Toolkit

Awesome list about all kinds of interesting topics: Laws, Principles, Mental Models, Cognitive Biases

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.

Collaborative text editor (like Google Docs or CoderPad) with integrated semi-anonymizing voice chat intended to help reduce bias in technical communication.

Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM

A curated list of awesome Fairness in AI resources

Bias detection in the news. Back and front end for areyoufakenews.com

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

Automatic synthesis of RCTs

Bluetooth Impersonation AttackS (BIAS) [CVE 2020-10135]

Can we use explanations to improve hate speech models? Our paper accepted at AAAI 2021 tries to explore that question.

I will update this repository to learn Machine learning with python with statistics content and materials

Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰

RUBi : Reducing Unimodal Biases for Visual Question Answering

A reading list and fortnightly discussion group designed to provoke discussion about ethical applications of, and processes for, data science.

A collection of news articles, books, and papers on Responsible AI cases. The purpose is to study these cases and learn from them to avoid repeating the failures of the past.

List of references about Machine Learning bias and ethics

Symmetric evaluation set based on the FEVER (fact verification) dataset

Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).

This is a collection of papers and other resources related to fairness.

Compass-aligned Distributional Embeddings. Align embeddings from different corpora

How are words loaded with meaning? Repository to accompany research paper in preparation by Alina Arseniev-Koehler and Jacob G. Foster, titled "Machine learning as a model for cultural learning: teaching an algorithm what it means to be fat."

This python script guesses the race and gender (probabilistically) of the first and last authors for papers in your citation list (in the form of a .bib file) and compares your list to expected distributions based on a model that accounts for paper characteristics (e.g., author location, author seniority, journal, et cetera.) unrelated to race and gender.

Source code and dataset for the paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"