Algorithmic inequality by design: Human resistance and its limits in chatbot-based customer service. - Zhao, Guoning (Big Data & Society)
This study focuses on the social inequalities embedded within chatbot-based customer service (CBCS) algorithms and those arising during their implementation, further examining users' resistance strategies and their effectiveness. Using a netnographic approach and framed by critical algorithm studies and algorithmic resistance theory, this study analyzes discussions regarding CBCS use (N = 1081) from three major Chinese social media platforms, Weibo, Zhihu, and Xiaohongshu. The study identifies three mechanisms through which CBCS algorithms reproduce, intensify, and generate social inequality, namely barriers, stratification, and labor- and cost-shifting. These mechanisms operate across structurally distinct relationships, including among different user segments, between platforms and users, between platforms and human customer service staff, and between platforms and merchants, producing different forms of inequality in each relational context. Users' resistance, whether within or beyond algorithmic frameworks, tends to be fragmented, structurally constrained, and limited in effectiveness, rarely translating into meaningful structural change. This study contributes to critical algorithm studies and algorithmic resistance research by identifying service mediation as a distinct mode of algorithmic power, developing a relational perspective on algorithmic inequality, and shifting the focus of resistance research from forms of resistance to their effectiveness in challenging structurally embedded inequalities.