184 citations · 399 across the 12 of their papers we have counts for
4 papers · 1 filter
Fair Enough: Searching for Sufficient Measures of Fairness
Suvodeep Majumder, Joymallya Chakraborty, Gina R. Bai +2
Testing machine learning software for ethical bias has become a pressing current concern. In response, recent research has proposed a plethora of new fairness metrics, for example,…
FairMask: Better Fairness via Model-based Rebalancing of Protected Attributes
Kewen Peng, Joymallya Chakraborty, Tim Menzies
Context: Machine learning software can generate models that inappropriately discriminate against specific protected social groups (e.g., groups based on gender, ethnicity, etc). Mo…
FairBalance: How to Achieve Equalized Odds With Data Pre-processing
Zhe Yu, Joymallya Chakraborty, Tim Menzies
This research seeks to benefit the software engineering society by providing a simple yet effective pre-processing approach to achieve equalized odds fairness in machine learning s…
Bias in Machine Learning Software: Why? How? What to do?
Joymallya Chakraborty, Suvodeep Majumder, Tim Menzies
Increasingly, software is making autonomous decisions in case of criminal sentencing, approving credit cards, hiring employees, and so on. Some of these decisions show bias and adv…