论文标题
通过机器学习在社交媒体上分析危机事件的道德风险
The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning
论文作者
论文摘要
社交媒体平台在全球范围内提供了有关危机事件的连续实时新闻。几种机器学习方法利用人群数据来自动检测危机以及其前体和后果的表征。与危机有关的事件的早期发现和定位可以帮助挽救生命和经济。然而，应用的自动化方法引入了值得调查的道德风险 - 特别是考虑到他们的高风险社会背景。这项工作确定并批判性地研究了针对机器学习方法的危机事件的社交媒体分析的道德风险因素。我们旨在使研究人员和从业人员对道德陷阱进行敏感，并促进更公平，更可靠的设计。
Social media platforms provide a continuous stream of real-time news regarding crisis events on a global scale. Several machine learning methods utilize the crowd-sourced data for the automated detection of crises and the characterization of their precursors and aftermaths. Early detection and localization of crisis-related events can help save lives and economies. Yet, the applied automation methods introduce ethical risks worthy of investigation - especially given their high-stakes societal context. This work identifies and critically examines ethical risk factors of social media analyses of crisis events focusing on machine learning methods. We aim to sensitize researchers and practitioners to the ethical pitfalls and promote fairer and more reliable designs.
