Customized search engine built on top of Searx, designed to re-rank search results by detecting and mitigating biases.

Code for paper "Consequence-aware Sequential Counterfactual Generation" (https://link.springer.com/chapter/10.1007/978-3-030-86520-7_42), @ ECML PKDD 2021 (). Repository maintained by Philip Naumann.

Unofficial implementation of paper "Flexibly Fair Representation Learning by Disentanglement"

"AdaFair: Cumulative Fairness Adaptive Boosting" algorithm (CIKM 2019) and its extension to other parity-based fairness notions (@Kais2022); Repository maintained by Vasileios Iosifidis.

Neural Additive Models - Visualization Tool in PyTorch/Plotly-Dash

Scripts to process the reference framework into an object

Repository of the paper "Toward a Responsible Fairness Analysis: From Binary to Multiclass and Multigroup Assessment in Graph Neural Network-Based User Modeling Tasks"

Code for paper "XPROAX - Local explanations for text classification with progressive neighborhood approximation", DSAA 2021 (https://ieeexplore.ieee.org/abstract/document/9564153). Repository maintained by Yi Cai.

Quilt: Robust Data Segment Selection against Concept Drifts (AAAI 2024)

Experiments for the paper "Finding patterns in ambiguity", accepted at ReGenAI workshop @ CVPR 2024

FRACTURED-SORRY-Bench: This repository contains the code and data for the FRACTURED-SORRY-Bench framework, as described in our paper.

An open source web platform for assessing Responsible and Trustworthy AI maturity level

About Unofficial implementation of paper "Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization"

This project is a set of tools to create a model card.

Introduction to responsible machine learning with Python

Agentic AI for Scalable Coaching

Code for paper "Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement​", Neurips 2023

[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6101 of Semester 1, AY2021-2022, starting from 08/2021. The instructors of this course are Prof. Bo An, Prof. Yu Han, and Dr. Melvin Chen.

Open-source Project for Responsible Al Checklists in Machine Learning and Al Development

Checklist for an analysis of various aspects of responsibility of models and data resources