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

Fit interpretable models. Explain blackbox machine learning.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

XAI - An eXplainability toolbox for machine learning

Bias Auditing & Fair ML Toolkit

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

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

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]

A curated list of awesome Fairness in AI resources

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

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

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

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

Automatic synthesis of RCTs

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

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

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

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

Identify bias and measure fairness of your data

repository of police abuse cases against people of color