most citedBias in Data-driven AI Systems -- An Introductory Survey

22 citations · 43 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG20203 cited

FairNN- Conjoint Learning of Fair Representations for Fair Decisions

Tongxin Hu, Vasileios Iosifidis, Wentong Liao +4

In this paper, we propose FairNN a neural network that performs joint feature representation and classification for fairness-aware learning. Our approach optimizes a multi-objectiv…

cs.AI2020

FAE: A Fairness-Aware Ensemble Framework

Vasileios Iosifidis, Besnik Fetahu, Eirini Ntoutsi

Automated decision making based on big data and machine learning (ML) algorithms can result in discriminatory decisions against certain protected groups defined upon personal data…

cs.CY202022 cited

Bias in Data-driven AI Systems -- An Introductory Survey

Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju +20

AI-based systems are widely employed nowadays to make decisions that have far-reaching impacts on individuals and society. Their decisions might affect everyone, everywhere and any…

cs.LG2019

AdaFair: Cumulative Fairness Adaptive Boosting

Vasileios Iosifidis, Eirini Ntoutsi

The widespread use of ML-based decision making in domains with high societal impact such as recidivism, job hiring and loan credit has raised a lot of concerns regarding potential…

cs.LG201918 cited

FAHT: An Adaptive Fairness-aware Decision Tree Classifier

Wenbin Zhang, Eirini Ntoutsi

Automated data-driven decision-making systems are ubiquitous across a wide spread of online as well as offline services. These systems, depend on sophisticated learning algorithms…

cs.LG2019

Fairness-enhancing interventions in stream classification

Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi

The wide spread usage of automated data-driven decision support systems has raised a lot of concerns regarding accountability and fairness of the employed models in the absence of…