RESUMEN
Our collaboration seeks to demonstrate shared interrogation by exploring the ethics of machine learning benchmarks from a socio-technical management perspective with insight from public health and ethnic studies. Benchmarks, such as ImageNet, are annotated open data sets for training algorithms. The COVID-19 pandemic reinforced the practical need for ethical information infrastructures to analyze digital and social media, especially related to medicine and race. Social media analysis that obscures Black teen mental health and ignores anti-Asian hate fails as information infrastructure. Despite inadequately handling non-dominant voices, machine learning benchmarks are the basis for analysis in operational systems. Turning to the management literature, we interrogate cross-cutting problems of benchmarks through the lens of coupling, or mutual interdependence between people, technologies, and environments. Uncoupling inequality from machine learning benchmarks may require conceptualizing the social dependencies that build structural barriers to inclusion. © 2022 IEEE Computer Society. All rights reserved.
RESUMEN
This book examines Zoombombing, the racist harassment and hate speech on Zoom. While most accounts refer to Zoombombing as simply a new style or practice of online trolling and harassment in the wake of increased videoconferencing since the outbreak of COVID-19, this volume examines it as a specifically racialized and gendered phenomenon that targets Black people and communities with racialized and gendered harassment. Racist Zoombombing brings together histories of online racism and algorithmic warfare with in-depth interviews by Black users on their experiences. The book explains how Zoombombing is a form of racial violence, interrogates our ideas about online space and community, and challenges our notions of on and off line distinction between racial harassment of Black people and communities. A vital resource for media, culture, and communication students and scholars that are interested in race, gender, digital media, and digital culture. © 2021 Lisa Nakamura, Hanah Stiverson and Kyle Lindsey.