The State of Algorithmic Fairness in Mobile Human-Computer Interaction
July 22, 2023 Β· Declared Dead Β· π International Conference on Human-Computer Interaction with Mobile Devices and Services
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Authors
Sofia Yfantidou, Marios Constantinides, Dimitris Spathis, Athena Vakali, Daniele Quercia, Fahim Kawsar
arXiv ID
2307.12075
Category
cs.HC: Human-Computer Interaction
Citations
4
Venue
International Conference on Human-Computer Interaction with Mobile Devices and Services
Last Checked
4 months ago
Abstract
This paper explores the intersection of Artificial Intelligence and Machine Learning (AI/ML) fairness and mobile human-computer interaction (MobileHCI). Through a comprehensive analysis of MobileHCI proceedings published between 2017 and 2022, we first aim to understand the current state of algorithmic fairness in the community. By manually analyzing 90 papers, we found that only a small portion (5%) thereof adheres to modern fairness reporting, such as analyses conditioned on demographic breakdowns. At the same time, the overwhelming majority draws its findings from highly-educated, employed, and Western populations. We situate these findings within recent efforts to capture the current state of algorithmic fairness in mobile and wearable computing, and envision that our results will serve as an open invitation to the design and development of fairer ubiquitous technologies.
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