Presentation 1
From _neijuan_ to _bujuan_: Chinese IT Practitioners' Changing Philosophy towards Working
Boyang Liang
University of Leeds, United Kingdom
The Chinese IT industry is characterized by high uncertainty and mobility. Due to the ongoing economic downturn, many IT companies are laying off employees as part of efforts to maintain sustainable operations. Additionally, IT individuals are opting to switch jobs to leverage their value or pursue higher salaries. To gain a competitive edge in the industry, a majority of individuals turned to “_neijuan_.” Unlike its interpretation in the agricultural field as involution, _neijuan_ is defined in the working context as internal energy-consuming competition. Existing research on Neijuan primarily discusses it as a social phenomenon, but I believe it is also a culture and spiritual state. Given the high uncertainty within the industry itself, the outcome of _neijuan_ is not necessarily success in competition, but it can also lead to a sense of anxiety for others. Nevertheless, some IT employees still practice _neijuan_ in their work, the duration and sources of occurrence vary, but some choose to give up _neijuan_(_bujuan_). Through conducting 30 semi-structured interviews in Beijing, China, where the IT industry is highly concentrated, this research aims to explore what _neijuan_ means to IT practitioners as insiders, how they manage pressure and embrace uncertainty, and to contribute to the prevalent discourse in academic contexts out of numerous media reports. This study adopts a qualitative research approach, assisted by NVivo for coding analysis, and all fieldwork has been completed. This is a part of my PhD thesis and will be a groundbreaking ethnographic study to understand both the industry and individuals.
Presentation 2
From Farmland to Warehouse: The Impacts of E-commerce Logistic Infrastructure on Rural Chinese Space
Lizhen Zhao
umass-amherst, United States of America
In the past decades, e-commerce platforms have brought significant transformation to not only economic activities, labor conditions, governance, social structures, and cultural production in rural China, but also how rural spaces are configured and experienced. Logistic distribution centers, despite foundation to e-commerce platform economy and providing a unique entry point to examine the materiality and spatiality of e-commerce platforms, drew little scholarly attention. The present study focuses on how logistic distribution centers shape rural land use and rural people’s experiences with space in northwest China. Inspired theoretically by platform infrastructure studies, I am conducting a long-term ethnographic fieldwork (with participatory observation and interviews) in Gansu province, northwest China. I argue that, firstly, in the process of transforming land use for logistic distribution center construction, although most participating parties (local government, developers, farmers, cadres) benefit economically, the interests are unevenly distributed with farmers having little power to negotiate the terms. Secondly, the new spatial experiences emerged for the landless farmers employed at the distribution center are highly gendered: for women working in warehouse, the cultural expectation for care work force them into heavily exploitative, gendered, and surveilled space; while for mostly male delivery workers, though experiencing the urban space with more collective cooperation and autonomy, they are still in a rather precarious position constantly at risk from uncontrollable factors in said space.
Presentation 3
ML WORKER AGENCY & AUTONOMY IN AI DEVELOPMENT IN IRELAND
Jason Kalathas
University College Dublin, Ireland
This paper aims to shed new light on the emerging field of AI work by examining the agency and autonomy of ML workers in AI development. AI talent and AI work are some of the most high-demanded professions today ((Steinhoff, 2021). However, relevant research on tech workers has mainly overlooked expert workers such as data scientists and ML engineers. Digital labour studies have thus far mainly researched lower ranks of digital workers by looking into gig work (Scholz, 2017), crowd work (Graham et al., 2017), and platform work. Addressing this research overlook, Dorschel (2022) calls for an expansion of research interest toward tech workers to understand how they contribute to the development of AI technologies.
This research looks into ML development in three different work settings in Ireland (private sector, public sector, and public/private). We conduct twenty semi-structured interviews with different professionals working on ML development in the corporate industry, two University College Dublin spin-off companies, and academic research centres. By centering ML workers into the debate, we explore how these AI workers perceive their agency and input in the AI development process as well as to what extent they enjoy autonomy as expert tech workers (Lazzarrato, 1997; Steinhoff, 2021). Finally, following Abbott's system of professions ((1988), this paper examines whether there is an emerging ecosystem of AI professions.
Presentation 4
HOW FACT-CHECKERS ARE BECOMING MACHINE LEARNERS: A CASE OF META’s THIRD PARTY PROGRAMME
Yarden Skop(1), Anna Schjøtt Hansen(2)
1: University of Siegen, Germany; 2: University of Amsterdam, Netherlands, The
A recent development in the field of fact-checking is what some scholars call the “debunking turn” in which fact-checking organisations move from fact-checking expressions of politicians and public figures to checking claims made on social media. A main driver of this change is the proliferation of a paid program initiated by Meta, where fact-checkers check and label claims on the platform in exchange for monetary remuneration. This paper draws on interviews with and fieldwork amongst fact-checkers who are or have been part of the Meta partnership. Based on the empirical insights we argue that the human-machine assemblage in fact-checking is (1) enabling a move beyond the ‘debunking turn’ by turning journalists into ‘machine learners’ and (2) cements a ‘politics of demarcation’ in which public contestation over public facts is diminished and moved into networked infrastructures.
With this argument, the paper highlights an additional aspect of the platformisation of journalism, as the labelling and claim-checking work of journalists now also enables large tech platforms to expand technical infrastructures that commodify journalistic work by turning it into training data aimed at improving their ML systems and algorithms. This enables platforms to move further beyond their current market role, as they also participate in the further industrialisation and standardisation of fact-checking. As large tech companies become industry leaders in the provision of ML systems, for example, for fact-checking, the need to understand what politics they produce equally increases, as they become integral in the production of democratic ideals of citizens and public debate.
