Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams

Zhang, Wenbin and Zhang, Mingli and Zhang, Ji and Liu, Zhen and Chen, Zhiyuan and Wang, Jianwu and Raff, Edward and Messina, Enza (2020) Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams. In: 32nd International Conference on Tools with Artificial Intelligence (ICTAI'20), 9-11 Nov 2020, Baltimore, United States.


Abstract

Artificial intelligence (AI)-based decision-making systems are employed nowadays in an ever growing number of online as well as offline services-some of great importance. Depending on sophisticated learning algorithms and available data, these systems are increasingly becoming automated and data-driven. However, these systems can impact individuals and communities with ethical or legal consequences. Numerous approaches have therefore been proposed to develop decision-making systems that are discrimination-conscious by-design. However, these methods assume the underlying data distribution is stationary without drift, which is counterfactual in many realworld applications. In addition, their focus has been largely on minimizing discrimination while maximizing prediction performance without necessary flexibility in customizing the tradeoff according to different applications. To this end, we propose a learning algorithm for fair classification that also adapts to evolving data streams and further allows for a flexible control on the degree of accuracy and fairness. The positive results on a set of discriminated and non-stationary data streams demonstrate the effectiveness and flexibility of this approach.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Date Deposited: 22 Feb 2021 01:54
Last Modified: 26 Feb 2021 04:22
Uncontrolled Keywords: AI fairness, online classification, flexible fairness
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460501 Data engineering and data science
Identification Number or DOI: https://doi.org/10.1109/ICTAI50040.2020.00069
URI: http://eprints.usq.edu.au/id/eprint/41392

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