Becoming transparent and feeling helpless: Expressions of vulnerability and inequality in online critiques of algorithmic surveillance in China

During the COVID-19 pandemic, numerous countries, including China, deployed digital surveillance technologies as part of broader social governance strategies. While these technologies offered certain benefits, their widespread application also posed risks, including algorithmic bias and privacy infringement. This study examines critical discussions (or critiques) on Chinese social media concerning various problems induced by algorithmic surveillance technologies such as the Health Code and Travel Code during the pandemic. Employing computational and qualitative textual analysis, our findings highlight recurring accounts of algorithmic and technical failures that users encountered when interacting with surveillance technologies. These disruptions exposed individuals to heightened algorithmic vulnerability and intensified existing inequalities, particularly through unequal treatment and negative emotional experiences. Our research further implies that the critical discussions often framed the Chinese government’s massive deployment of algorithmic surveillance technologies as exacerbating pre-existing issues, such as the digital divide and social bias, especially for vulnerable groups like older people. Meanwhile, our analysis of online critiques highlights growing concerns and skepticism among some users toward both algorithmic technologies and state governance.

Authors

Institutions

Publication Details

Journal
Asian journal of social science
Published
2025-10-22
DOI
https://doi.org/10.1016/j.ajss.2025.100214
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Becoming transparent and feeling helpless: Expressions of vulnerability and inequality in online critiques of algorithmic surveillance in China

Haili Li, Genia Kostka
Asian journal of social science
Ethics and Social Impacts of AI
article

Becoming transparent and feeling helpless: Expressions of vulnerability and inequality in online critiques of algorithmic surveillance in China

Haili Li, Genia Kostka
article en

Abstract

During the COVID-19 pandemic, numerous countries, including China, deployed digital surveillance technologies as part of broader social governance strategies. While these technologies offered certain benefits, their widespread application also posed risks, including algorithmic bias and privacy infringement. This study examines critical discussions (or critiques) on Chinese social media concerning various problems induced by algorithmic surveillance technologies such as the Health Code and Travel Code during the pandemic. Employing computational and qualitative textual analysis, our findings highlight recurring accounts of algorithmic and technical failures that users encountered when interacting with surveillance technologies. These disruptions exposed individuals to heightened algorithmic vulnerability and intensified existing inequalities, particularly through unequal treatment and negative emotional experiences. Our research further implies that the critical discussions often framed the Chinese government’s massive deployment of algorithmic surveillance technologies as exacerbating pre-existing issues, such as the digital divide and social bias, especially for vulnerable groups like older people. Meanwhile, our analysis of online critiques highlights growing concerns and skepticism among some users toward both algorithmic technologies and state governance.

Asian journal of social scienceVol. 53(4)
University of Exeter (GB), Freie Universität Berlin (DE)
Openalex Percentile: Top 70%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.