  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.
