Hidden Labour: UTM Researcher Exposes Material Realities of Digital Capitalism

Julie Yujie Chen wants us to rethink the digital world, not as a cloud of data, but as a system built on human labour. An Associate Professor in UTM’s Institute of Communication, Culture, Information and Technology (ICCIT) and recipient of the 2024-25 UTM Annual Research Prize in the Social Sciences, Prof. Chen has spent her career uncovering the material realities behind digital technologies. 

Her interest began during her PhD studies in the United States, when Facebook and other platforms were transforming the digital landscape. At the time, academic debates were focusing on the promise of big data — often described as “the new oil” — but rarely on the material conditions behind it.

Born and raised in China, Chen was keenly aware of the sprawling Foxconn factories that manufacture electronics for global brands like Apple, plants widely criticized for harsh working conditions.

“I started to wonder why this part of the story wasn’t circulating in the discourses on data,” says Chen, noting that similar promises are now being made about artificial intelligence. “These devices that people use to log on to enjoy social media, they’re made in China and increasingly, other parts of Asia. So, while half of me was listening to the promises of big data, the other half was fully aware of these assembly factories.”

That question led Chen from factory floors to the gig economy, where digital platforms mediate millions of precarious jobs. Working primarily in mainland China, Chen’s research spans platform labour and AI data work, grounding technology in the lived experiences of workers, the people and practices that make the digital economy possible. Chen documents how these technologies reshape work and worker subjectivity, often in ways that deepen precarity and inequality.

“Employment is an important social institution,” she says. “But for the workers I study, casualization — work becoming increasingly short term and unstable — is not new; it’s an ongoing trend. More and more workers are facing a lack of institutional protection.”

Through interviews, participant observation, platform study, and organizational analysis, Chen studies workers who manufacture digital products and those who depend on platforms for income, such as ride-hailing drivers and delivery couriers. These workers all navigate a world of short-term gigs and eroding protections, widening social inequality and leaving workers vulnerable.

Yet her research also uncovers resistance. Algorithms, she argues, have become a contested site for worker struggles. From finding ways around platform rules to organizing online, these acts — Chen calls them “algorithmic activism” — reveal that technology is never neutral. 

One of her earliest articles, touted by reviewers as one of the first to address workers’ resistance to technologies, documents how taxi drivers on ride-hailing platforms have found ways to “game the system”. And this area of focus is picking up speed, with more and more research being conducted on how workers resist and maintain autonomy when the institutional conditions are working against them.

These struggles are deeply intersectional. In China, many platform workers are rural-to-urban migrants who face unstable jobs as well as historically systemic disadvantages. 

“It’s simultaneously the struggles at the workplace and the fact that migrant workers enjoy less rights in urban areas compared to urban residents,” says Chen. “For instance, their children have less access to public education.”

Chen’s current project on AI data work uncovers similar patterns. One group she studies is urban mothers with preschool-age children, who live in less prosperous regions and shoulder caregiving responsibilities. They choose remote data annotation work because they have few alternatives in the local labour market. 

“These women are balancing century-old problems of gender inequality,” Chen points out. “So, these are intersectional struggles that are also about their identity — workers develop a lot of ambivalence toward the technologies that enable them to work in certain ways.”

For Chen, studying digital labour is both about documenting work and reframing how we think about technology and its risks. Current conversations around AI safety often focus on technical solutions, like preventing bias in algorithms or ensuring model reliability. But Chen argues that these debates overlook the social inequalities embedded in digital systems.

She is collaborating with two colleagues at the University of Sheffield on a SSHRC-funded knowledge synthesis project examining AI safety frameworks. Their goal is to broaden the debates on technical safeguards to include labour rights and ecological impacts. 

Chen is also writing a book — funded by SSHRC — based on her fieldwork with AI data workers in China. While studies have been published on data workers in Latin America, Africa, and India, this will be the first book on Chinese data workers — a group often overlooked in global discussions about artificial intelligence and China. 

“People always talk about AI competition between the U.S. and China, and how AI has been used as surveillance technology or for military purposes by the Chinese government,” she explains. “But few systematically explore the data workers behind those AI technologies within the context of remaking the Chinese digital working class. It’s interesting to hear why a worker is drawn to the job and how she thinks of her work.” 

“I wanted to frame this from working class perspectives, and to use the development of AI technologies to show how it has shifted labour struggles and social inequalities.” 

In addition to her own research projects, Chen is helping to shape the field globally. She is co-editor of the forthcoming Sage Handbook of Digital Labour, and Chen says it is the textbook she has always wanted. Featuring scholars from all over the world, the handbook brings gender and racial inequalities into digital labour debates and includes chapters on mining, e-waste, and more, along with a robust section on methodology.

Chen is also founding editor of Platforms & Society journal, which publishes research on everything from digital platforms to how these platforms embed themselves in different geographies, societies, and cultures, as well as interdisciplinary work on generative AI and large language models. She serves on the editorial boards of the Journal of Cultural Economy and the Chinese Journal of Communication. 

With each of these, Chen’s goal is to push public discourse beyond utopian or dystopian narratives about technology. 

“There seems to be this binary thinking, especially in public-facing publications. Either technologies are all good or all bad. Either robots will be great, and we’ll all be free and happy, or robots will take over your job and you’ll be jobless,” Chen says. “My research has found that it’s a more complicated picture.”

“We always think technology works like magic, but we need to get to the site of production to understand what really happens,” she adds. “Workers’ struggles are at the frontier of social structure and inequality.”