accuracy-explainability-tradeoff

algorithmic-transparency-playbook

cifrank

The repo for causal intersectionality for fair ranking.

courses

This is repo of all Data Responsibly related courses.

dataresponsibly

The repository for all the datasets and projects related with data responsibly.

dataresponsibly.github.io

Data, Responsibly

dataresponsiblyui

A Django project for the Web UIs of the Data, Resposibly.

datasets

This is the repository for all the public datasets that have been used in DataResponsibly projects.

datasynthesizer

datavalidator

fairdags

This is the repository of code for fairDAGs.

fairness-in-ranking

This repository is for metrics of fairness in rankings. TBD.

fairprep

FairPrep is a design and evaluation framework for fairness-enhancing interventions that treats data as a first-class citizen.

fairrank

fides

Responsible Data Management Platform

hiring-stability-audit

External stability audit to test the validity of personality predictions made by AI hiring systems

mew-supplementals

Supplemental materials for the paper of Most-Expected-Winner.

mirrordatagenerator

MirrorDataGenerator is a python tool that generates synthetic data based on user-specified causal relations among features in the data. It focuses on how features relate with demographic attributes (e.g. gender, race, disability status, etc), which are considered as sensitive information for certain domains (e.g. employment, housing, etc).

mlcf

A controlled environment to play around with various data errors and stages in the ML lifecycle and measure their impact on model fairness and stability.

rai_site.github.io

rankingfacts

This is the repository of source codes for RankingFacts demo.

rds

A repository that redirects to the current version of the RDS course website.

rds21

Website for the Responsible Data Science courses DS-UA 202 and DS-GA 1017

rds22

rds23

Course website for the Spring 2023 offering of Responsible Data Science (DS-UA 202 and DS-GA 1017) at New York University.

rds24

sharp

Implementation of the algorithm proposed in the paper "ShaRP: Explaining Rankings with Shapley Values", by Pliatsika et al.

smartnoise-sdk

Tools and service for differentially private processing of tabular and relational data

spring19

Another link for Spring course 2019

synrd

Synthetic Research Datasets Feasibility Study