FairComp: Workshop on Fairness and Robustness in Machine Learning for
  Ubiquitous Computing
Sofia Yfantidou Dimitris Spathis Marios Constantinides Tong Xia Niels van Berkel
How can we ensure that Ubiquitous Computing (UbiComp) research outcomes are
both ethical and fair? While fairness in machine learning (ML) has gained
traction in recent years, fairness in UbiComp remains unexplored. This workshop
aims to discuss fairness in UbiComp research and its social, technical, and
legal implications. From a social perspective, we will examine the relationship
between fairness and UbiComp research and identify pathways to ensure that
ubiquitous technologies do not cause harm or infringe on individual rights.
From a technical perspective, we will initiate a discussion on data practices
to develop bias mitigation approaches tailored to UbiComp research. From a
legal perspective, we will examine how new policies shape our community's work
and future research. We aim to foster a vibrant community centered around the
topic of responsible UbiComp, while also charting a clear path for future
research endeavours in this field.