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On adaptive fairness in software systems

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posted on 2021-10-28, 10:55 authored by Ali Farahani, Liliana Pasquale, Amel Bennaceur, Thomas Welsh, Bashar Nuseibeh
Software systems are increasingly making decisions on behalf of humans, raising concerns about the fairness of such decisions. Such concerns are usually attributed to flaws in algorithmic design or biased data, but we argue that they are often the result of a lack of explicit specification of fairness requirements. However, such requirements are challenging to elicit, a problem exacerbated by increasingly dynamic environments in which software systems operate, as well as stakeholders’ changing needs. Therefore, capturing all fairness requirements during the production of software is challenging, and is insufficient for addressing software changes post deployment. In this paper, we propose adaptive fairness as a means for maintaining the satisfaction of changing fairness requirements. We demonstrate how to combine requirements-driven and resource-driven adaptation in order to address variabilities in both fairness requirements and their associated resources. Using models for fairness requirements, resources, and their relations, we show how the approach can be used to provide systems owners and end-users with capabilities that reflect adaptive fairness behaviours at runtime. We demonstrate our approach using an example drawn from shopping experiences of citizens. We conclude with a discussion of open research challenges in the engineering of adaptive fairness in human-facing software systems.

Funding

Differential expression in the tissues of the three-spined stickleback (Gasterosteus aculeatus L) under conditions of different salinity of water, the influence of epigenetic factors, the connection with the processes of evolutionary adaptation.

Russian Foundation for Basic Research

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Publication

International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS);pp. 97-103

Publisher

IEEE Computer Society

Note

peer-reviewed

Other Funding information

SFI

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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

English

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