FairComp: Workshop on Fairness and Robustness in Machine Learning for Ubiquitous Computing

TL;DR

This workshop explores fairness and ethical considerations in UbiComp research, addressing social, technical, and legal challenges to promote responsible development of ubiquitous technologies.

Contribution

It initiates a multidisciplinary discussion on fairness in UbiComp, highlighting the need for bias mitigation, ethical standards, and policy considerations in future research.

Findings

Identified social implications of fairness in UbiComp

Proposed data practices for bias mitigation in UbiComp

Analyzed legal frameworks impacting UbiComp research

Abstract

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.