4 papers
Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinking
Zichong Wang, Yang Zhou, David Lo +1
The increasing use of Machine Learning (ML) software can lead to unfair and unethical decisions, thus fairness bugs in software are becoming a growing concern. Addressing these fai…
Online and Customizable Fairness-aware Learning
Wenbin Zhang
While artificial intelligence (AI)-based decision-making systems are increasingly popular, significant concerns on the potential discrimination during the AI decision-making proces…
Attention Mechanism based Cognition-level Scene Understanding
Xuejiao Tang, Wenbin Zhang
Given a question-image input, the Visual Commonsense Reasoning (VCR) model can predict an answer with the corresponding rationale, which requires inference ability from the real wo…
Fairness Amidst Non-IID Graph Data: A Literature Review
Wenbin Zhang, Shuigeng Zhou, Toby Walsh +1
The growing importance of understanding and addressing algorithmic bias in artificial intelligence (AI) has led to a surge in research on AI fairness, which often assumes that the…