posted on 2021-10-28, 10:55authored byAli 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.