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.

翻译：本文探讨了人工智能与机器学习（AI/ML）公平性与移动人机交互（MobileHCI）的交叉领域。通过对2017年至2022年间发表的MobileHCI会议论文集进行系统分析，我们首先致力于理解该领域内算法公平性的当前状态。通过人工分析90篇论文，我们发现其中仅有少数（5%）遵循现代公平性报告规范（如基于人口统计学分组的条件分析）。与此同时，绝大多数研究结论源自高学历、在职及西方群体。我们将这些发现置于近期捕捉移动与可穿戴计算领域算法公平性现状的研究努力中，并期望我们的结果能够为设计和开发更公平的普适技术提供开放邀请。