FairComp: 2nd International Workshop on Fairness and Robustness in Machine Learning for Ubiquitous Computing
Authors: 
Lakmal Meegahapola, 
Dimitris Spathis, 
Marios Constantinides, 
Han Zhang, Sofia Yfantidou, 
Niels van Berkel, Anind K. DeyAuthors Info & Claims
Lakmal Meegahapola, Dimitris Spathis, Marios Constantinides, Han Zhang, Sofia Yfantidou, Niels van Berkel, Anind K. DeyAuthors Info & ClaimsPages 996 - 999
Abstract
How can we ensure that Ubiquitous Computing (UbiComp) research outcomes are ethical, fair, and robust? While fairness in machine learning (ML) has gained traction in recent years, it remains unexplored, or sometimes an afterthought, in the context of pervasive and ubiquitous computing. 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 model generalization and robustness, as well as data processing methods 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. Building on the success of the First FairComp Workshop at UbiComp 2023, we have established a vibrant community centered around the topic of fair, robust, and trustworthy algorithms within UbiComp, while also charting a clear path for future research endeavors in this field.
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Index Terms
- FairComp: 2nd International Workshop on Fairness and Robustness in Machine Learning for Ubiquitous Computing
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Published: 05 October 2024
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UbiComp '24
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UbiComp '24: The 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing
October 5 - 9, 2024
Melbourne VIC, Australia
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Overall Acceptance Rate 764 of 2,912 submissions, 26%
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