FairCompass: Operationalising Fairness in Machine Learning

27 December 2023

Papers citing "FairCompass: Operationalising Fairness in Machine Learning"

6 / 6 papers shown

Title
Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systems Yongsu Ahn Quinn K. Wolter Jonilyn Dick Janet Dick Yu-Ru Lin HAI 26 0 0 10 Sep 2024
Exploring Bias and Prediction Metrics to Characterise the Fairness of Machine Learning for Equity-Centered Public Health Decision-Making: A Narrative Review Shaina Raza Arash Shaban-Nejad Elham Dolatabadi Hiroshi Mamiya 26 2 0 23 Aug 2024
Verifiable evaluations of machine learning models using zkSNARKs Tobin South Alexander Camuto Shrey Jain Shayla Nguyen Robert Mahari Christian Paquin Jason Morton Alex Pentland MLAU ALM 31 11 0 05 Feb 2024
Towards the Right Kind of Fairness in AI Boris Ruf Marcin Detyniecki 44 26 0 16 Feb 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,187 0 23 Aug 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 739 0 13 Dec 2018