AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications

Author:

Chen Pu1ORCID,Wu Linna2,Wang Lei1

Affiliation:

1. College of Communication Engineering, PLA Army Engineering University, Nanjing 210007, China

2. Aerospace System Engineering Shanghai, Shanghai 201109, China

Abstract

This article provides a comprehensive overview of the fairness issues in artificial intelligence (AI) systems, delving into its background, definition, and development process. The article explores the fairness problem in AI through practical applications and current advances and focuses on bias analysis and fairness training as key research directions. The paper explains in detail the concept, implementation, characteristics, and use cases of each method. The paper explores strategies to reduce bias and improve fairness in AI systems, reviews challenges and solutions to real-world AI fairness applications, and proposes future research directions. In addition, this study provides an in-depth comparative analysis of the various approaches, utilizing cutting-edge research information to elucidate their different characteristics, strengths, and weaknesses. The results of the comparison provide guidance for future research. The paper concludes with an overview of existing challenges in practical applications and suggests priorities and solutions for future research. The conclusions provide insights for promoting fairness in AI systems. The information reviewed in this paper is drawn from reputable sources, including leading academic journals, prominent conference proceedings, and well-established online repositories dedicated to AI fairness. However, it is important to recognize that research nuances, sample sizes, and contextual factors may create limitations that affect the generalizability of the findings.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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