A Framework for Designing Fair Ubiquitous Computing Systems
Han Zhang, Leijie Wang, Yilun Sheng, Xuhai Xu, Jennifer Mankoff, and, Anind K. Dey

TL;DR
This paper proposes a comprehensive framework to incorporate fairness into the design of ubiquitous computing systems, addressing biases and promoting equitable treatment across diverse contexts.
Contribution
It introduces a novel, multi-faceted framework that guides the integration of fairness considerations into ubiquitous system development, from data collection to ongoing monitoring.
Findings
Framework emphasizes stakeholder perspectives and inclusive data collection.
Incorporates fairness-aware algorithms and evaluation criteria.
Supports human engagement while safeguarding privacy.
Abstract
Over the past few decades, ubiquitous sensors and systems have been an integral part of humans' everyday life. They augment human capabilities and provide personalized experiences across diverse contexts such as healthcare, education, and transportation. However, the widespread adoption of ubiquitous computing has also brought forth concerns regarding fairness and equitable treatment. As these systems can make automated decisions that impact individuals, it is essential to ensure that they do not perpetuate biases or discriminate against specific groups. While fairness in ubiquitous computing has been an acknowledged concern since the 1990s, it remains understudied within the field. To bridge this gap, we propose a framework that incorporates fairness considerations into system design, including prioritizing stakeholder perspectives, inclusive data collection, fairness-aware algorithms,…
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