The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning
Published in Proc. International Workshop on Data-driven Resilience Research 2022, 2022
Recommended citation: Kraft, A. and Usbeck, R. (2022). The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning. In Proceedings of the International Workshop on Data-driven Resilience Research 2022 co-located with Data Week Leipzig 2022 (DATAWEEK 2022), CEUR-WS.org, https://ceur-ws.org/Vol-3376/paper01.pdf
Abstract: Social media platforms provide a continuous stream of real- time news regarding crisis events happening on a global scale. Several machine learning methods utilize the crowd-sourced data for the auto- mated 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 meth- ods introduce ethical risks worthy of investigation — especially given their high-stakes societal context. This work identifies and critically ex- amines ethical risk factors of social media analyses of crisis events focus- ing on machine learning methods. We aim to sensitize researchers and practitioners to the ethical pitfalls and promote fairer and more reliable designs.