Fairness Requirement in AI Engineering – A Review on Current Research and Future Directions

Nga Pham (), Hung Pham-Ngoc () and Anh Nguyen-Duc ()
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Nga Pham: Dainam University
Hung Pham-Ngoc: VNU University of Engineering and Technology
Anh Nguyen-Duc: University of South Eastern Norway

A chapter in Sustainability in Software Engineering and Business Information Management, 2023, pp 3-13 from Springer

Abstract: Abstract Currently, Artificial Intelligence (AI) has been applied to the same development techniques as software. There have been opinions that the evaluation of the quality of AI software should be based on the element of AI software fairness. An unfair AI software is considered shoddy software. There is a lot of recent researches intending to make AI software fair, accountable and transparent. Therefore, it is extremely important to consider the issue of fairness while analyzing this kind of software. A big question is also raised. What is fair AI software? How to measure the fairness of a given AI software and how to test that fairness? This paper will summarize the concepts of fairness in AI software that have been introduced as well as the method of measuring and testing fairness in AI software according to those concepts. Based on an ad-hoc literature review, we summarize some recent findings in the area of requirement engineering for AI fairness and point out some research gaps.

Keywords: Fairness; Bias; AI; Definitions of Fairness; AI Software Fairness; Literature review (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-32436-9_1

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