Call for abstracts: special issue of China Information

China Information special issue on “Automation, Autonomy, and Alternatives: Popular Voices from Digital China”

Guest editors

• Jun Liu, University of Copenhagen, Denmark (liujun@hum.ku.dk)
• Haiqing Yu, RMIT, Australia (haiqing.yu@rmit.edu.au)

There is an increasing body of scholarly work on digital transformations in culture, politics, and society, driven by emerging media and communication technologies such as 5G, virtual and augmented reality, and AI. China remains a focal point of reference when discussing the relationship between digital technologies and cultural transformations.

Most research has taken a broad-brush, macro approach to examining the politics and policies surrounding the development and application of automation technologies in China. This research is often based on publicly available policies, industry reports, media and social media posts, and other documents. Using computational methods, surveys, discourse, or policy analysis, scholars have explored the complexity of emerging data-driven platforms and systems like the Social Credit System and the health code systems used during the COVID-19 lockdowns. These studies have focused on how automation technologies have empowered those with power and resources, further squeezing the space for societal autonomy and alternative visions and voices.

In this context, we argue that the picture is incomplete without including “other” or alternative voices on digital transformations in people’s everyday lives. This entails firsthand empirical or field-based investigation and analysis of popular voices from “below” and “inside.”

This Special Issue (SI) aims to advance the discussion by specifically accounting for popular voices in digital China. By “popular voices,” we refer to the diverse and often unofficial (though not necessarily anti-official) discourses and perspectives expressed by ordinary citizens, activists, bloggers, and other non-governmental entities. These voices often serve as undercurrents to the official or mainstream discourses promoted by the state, big tech companies, and institutionalized academics. Such undercurrents cannot be easily categorized as “pro” or “con” in relation to the mainstream narratives; many exist in a vast grey zone between the official and unofficial. They create a dynamic and contested digital sphere in China, where alternative narratives and competing discourses circulate and influence public opinion, despite the challenges posed by technology-enhanced content censorship, control, and manipulation.

“Digital China” is not a geopolitical but a technocultural concept. It evokes Tu Weiming’s framing of cultural China, transcending geography and ideology by focusing on the role of digital innovation and ensuring communicative power in linking all who are intellectually or emotionally connected to China, its people, and its culture. Digital China thus denotes a centrifugal tendency in our research on popular voices. It is a floating signifier of multiplicity and uncertainty, particularly when examining the relations between automated decision-making (ADM) systems and Chinese societies.

This SI covers the following three key themes and corresponding research questions to unpack the topic:

1. How are emerging ADM technologies and systems imagined or perceived in unofficial voices? ADM systems, like the Social Credit System, have been portrayed in mass media as state-driven, Orwellian tools of social monitoring and political repression. However, in-situ observation and analytical assessment remain limited. Additionally, there is a gap between the extensively studied policy-based understanding of ADM and its social implementations, which often reveal diverse (and sometimes contradictory) perceptions. How do popular voices across different social groups and cultural contexts perceive ADM systems, and how do they reflect on broader topics like datafication, privacy, autonomy, and control?
2. How much autonomy do citizens enjoy when dealing with algorithmic capitalism and nationalism? The autonomy of citizens is often constrained by the opaque nature of algorithms and the lack of regulatory oversight. Many individuals are unaware of how algorithms influence their choices and behaviors, from personalized advertising to political messaging. This lack of transparency can lead to feelings of powerlessness, as people struggle to navigate systems designed to maximize profit or national interests rather than individual welfare. How much autonomy do citizens truly enjoy, and what are the implications of this for their daily lives and political engagement in contemporary China?
3. What are the possible ways of alternative imaginations and actions? Alternative imaginations and actions are crucial for understanding political and cultural initiatives and diversity in contemporary China. These alternatives help cultivate a more informed and proactive citizenry. Exploring and supporting diverse narratives and practices can lead to more resilient and adaptive approaches to technology, platforms, and governance. Therefore, what are the possible ways of alternative imaginations and actions that we observe from popular voices, and how can they influence broader societal changes?

This SI derives from the 21st Chinese Internet Research Conference (CIRC 2024), organized by the ARC Centre of Excellence for Automated Decision-Making and Society. We have solicited six to nine peer-reviewed presentations on topics that address the three keywords of the special issue, spanning from personalization algorithm awareness to personal curation on social media, from consumer nationalism to outsourced environmental data activism, and from social media avoidance to digital labor. Together, this special issue delivers up-to-date investigations into understanding Digital China from popular voices, offering new insights and fostering critical discussions in the field.

Timeline

Note: individual papers will be published online as soon as they are accepted and copyedited. The special issue will be published in 2027.

This work was supported by the Independent Research Fund Denmark – Research Network (grant number 0162-00011B).