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In Norwegian work life the hype around AI is omnipresent and challenges how, who, what and when to trust in knowledge-workers’ daily work. This study investigates emerging technologies’ impact on (dis/mis)trust, and how epistemic practices become reconfigured in AI-mediated work.

Paper long abstract

Advances in emerging technologies, like digital systems and artificial intelligence, are increasingly becoming interwoven into Norwegian knowledge-intensive work, reshaping not only the epistemic practices, but meaning-making, norms and values. In Norway, characterised as a high-trust country and one of the most digitalised countries in the world, the hype around AI and beliefs in ‘techno–solutionism’ reigns supreme. However, increasingly, worries about the ‘loss of the Nordic gold’, e.g. trust, figure in the public discourse around AI implementation. This study investigates trust in technology (or the lack thereof), and how emerging technologies might reshape different trust relations at work. It builds on ethnography from two Norwegian firms, one in the public services and one in the media industry, currently implementing AI at a large scale.

We understand trust as embedded in actions yet to come: Trust exists only by virtue of mutual and reciprocal expectations of something not yet realised (Sørhaug 1996). In anthropology, recent research suggests that trust takes new and different shapes as our lives are fully entangled in a digital sociality (Maguire & Albris, 2024, Pink & Quilty, 2025) and that distrust, a form of withholding trust, a “trustless trust,” is put forth by developers who promise to erase the need for trust in institutions (Bruun et al., 2020). Hence, when confronted with emerging technologies, trust might become one-directional, rather than reciprocal. Correspondingly, understanding mis/distrust as emerging social forms in work life is crucial, especially as human-technology interactions become more complex with AI as a collaborator.

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Ethnography of a Swiss robotics company showing how engineers use LLM tools to decide when robots and code are “good enough.” I trace how these adequacy regimes reshape autonomy, productivity, care, and hierarchies of expertise.

Paper long abstract

This paper draws on ethnographic fieldwork at a Swiss robotics company, conducted as part of my current project on “adequacy regimes” in generative-AI supported work. Building on my earlier research on “good enoughness” in software engineering (Bialski 2024), I ask how robotics engineers decide when a robot, a line of code, or a workaround is “good enough” to move on.

In this setting, hybrid work is the norm: engineers alternate between hands-on lab work with physical robots and remote coordination through digital platforms (issue trackers, code review tools, chat channels) and AI systems (LLM copilots, simulation tools). Across these sites, they continually negotiate what counts as “good work.” Autonomy no longer means simply exercising individual judgment, but knowing when to defer to automated test suites, safety protocols, or AI-generated suggestions. Productivity is framed in terms of shipping “good enough” fixes under time pressure, while still upholding care for users, colleagues, and the robots that must operate safely in human environments.

By following debugging sessions, code reviews, and safety discussions, I show how platform metrics, AI outputs, and informal peer evaluations together reshape hierarchies of expertise, competence, and deservingness. The paper thus contributes to the panel’s aim by demonstrating how infrastructures of automation and connectivity reconfigure not only how robotics work is organized, but how workers imagine their productive and moral selves in relation to “good enough” machines and emerging adequacy regimes.

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Drawing on ethnographic fieldwork at the Beijing Film Academy in China, this paper examines how platforms and AI reshape ideas of “good work” before labour enters the market, showing how algorithms mediate creative labour and reconfigure productivity, fairness, responsibility, and value.

Paper long abstract

As platforms, AI, and data-driven systems increasingly organise labour, the meaning of “good work” is being rewritten. Digital anthropology has often centred on platform employment, the gig economy, or data labour, paying less attention to how algorithms shape workers’ values and ethics before labour enters the market. Drawing on thirteen months of ethnographic fieldwork at the Beijing Film Academy (BFA), this paper examines how platformisation and algorithmic systems rework standards of “good work” in the pre-industrial formation of creative labour.

Focusing on collaborative projects between internet video companies and BFA under the state’s “Internet+” policy, the paper traces AI-based film script evaluation systems as remote, non-face-to-face mechanisms of judgment that intervene in creative training, project selection, and access to resources. Treating algorithms as mediating infrastructures embedded in institutional settings, it shows how different actors attach moral meanings to them: platform management frame AI as a route to objectivity and efficiency in response to concerns about corruption and risk control; film producers use it to distribute accountability and manage investment uncertainty; BFA students adjust their creative strategies and career imaginaries in relation to platform preferences and algorithmic feedback.

In this highly digitalised environment, “good work” becomes less about expressive achievement alone than about creativity that is assessable, governable, and low-risk. The paper argues that algorithms function as moral technologies that reorder ideas of competence, fairness, and deservingness in Chinese creative labour.

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This paper examines how “good work” is redefined in the age of AI through inter-objective relations between digital tools, platforms, and labour. Drawing on ethnography with remote IT workers in India, it shows how "LLM epistemologies" reshape "understanding" as a practice.

Paper long abstract

This paper examines how “good work” is understood in the age of artificial intelligence by focusing on how understanding as a practice is produced through inter-objective relations. Interobjectivity is approached as the shared reality that emerges from relations between digital tools, human labour practices, and platform logics, where objects, infrastructures, and market systems actively participate in shaping meaning, value, and subjectivity (Latour 1994, 2005; Polanyi 2018; Stiegler 1998, 2019). I argue that these inter-objective relations reorganise understandings of “good work” by transforming both the division of labour and the division of values.

Drawing on ethnographic research with remote IT workers in India, this paper develops how the triad of AI, platforms, and human labour reconfigures (moral) understanding(s) of autonomy, care, and dignity. The aim of the ethnography is to demonstrate how computational models of “understanding,” developed within AI practices, circulate beyond technical domains and are taken up in everyday practices between home and work.

Engaging critically with the debates on “pragmatic genealogy” (Queloz 2021), the paper introduces an ethnographic intervention that situates “understanding” as practice within lived socio-material worlds of remote workers. I argue that “LLM epistemologies” contribute to the formation of everyday practices of “understanding” that shape the morality through which remote workers come to judge what counts as good, responsible, or meaningful work. Lastly, this paper argues how emerging technologies open new pathways for understanding “to understand” work and morality by embedding computational epistemologies into everyday life and what it could mean for [H]umans in a polarised world?

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This paper explores how self-proclaimed middle-class pious women in Turkey working for an MLM company redefine platform labor as a moral pursuit of abundance, navigating a marketized patriarchal bargain within digitized and platformatized MLMs.

Paper long abstract

In the hyperinflationary and polarized landscape of "New Türkiye," digital technologies are re-engineering the domestic fabric of society. This paper examines how pious, middle-class women redefine "good work" as they work for GE International, a Malaysian Multi-Level Marketing (MLM) firm selling Ganoderma fungi-infused products. Drawing on ethnography and 32 in-depth interviews, I trace how these workers negotiate a marketized patriarchal bargain, shifting their pursuit of security from the collapsed male-breadwinner model to the digital market. I conceptualize this space as the "algorithmic berzah", a socio-technical isthmus where digital metrics and Islamic moral economies converge. Through three vignettes, I demonstrate how workers assess productivity and care. First, I analyze "somatic theology," where distributors physically ingest Ganoderma-infused products to become "living testimonials," reframing economic precarity as a physiological blockage. Second, I look at the "re-moralization" of labor; as the company shifts toward AI-generated advertisements, women intervene by adding vernacular prayers and domestic imagery to sterile outputs to sustain kinship trust. Lastly, I examine the member portal of the MLM as a digital Book of Deeds, where platform rankings are phenomenologically reclaimed as measures of spiritual zeal. By focusing on these micro-encounters with digital infrastructure, the paper argues that distributors function as "nodal persons" who transmute the "cold" extraction of the gig economy into a "warm" pursuit of divine abundance. Ultimately, I show how "good", "work", and "good work" are redefined as projects of spiritual self-reform that promise salvation in both this world and the next.

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This paper examines how hybrid and remote workers in Amsterdam imagine a “good workplace” and “good workday.” Drawing on ethnography in co-working spaces, it shows how place mediates material, affective, and moral dimensions of work, shaping how neoliberal ideals of self-fulfilment are enacted.

Paper long abstract

With a particularly high number of hybrid and remote workers in the Netherlands, everyday choices of work environment participate in a broader reconfiguration of work as a site of self-fulfilment and affective satisfaction. Drawing on ongoing ethnographic fieldwork in Amsterdam as part of the ReWorkChange ERC-project, this paper examines how hybrid and remote knowledge workers imagine a “good workplace” and, correspondingly, a “good workday.”

Based on extensive participant observation in co-working spaces and interviews with their workers, the paper traces how remote and hybrid workers make sense of their working days and how these processes are entangled with the material and immaterial dimensions of commodified workplaces. The analysis focuses on how work environments are selected, valued, and invested with meaning, highlighting ‘place’ as a key medium through which ideas of “good work” are enacted.

Building on Kathi Weeks’ (2011) critique of the work ethic as a moral framework that ties self-fulfilment and social worth to productive labour, the paper extends this argument to the context of hybrid and remote work by asking how workplaces inform, and are informed by, changing imaginations of what makes a working day feel meaningful, successful, or satisfying. Engaging with the contemporary co-working office as a space where place itself becomes a central commodity (Jansson, Fast, and Andersson 2026), the paper shows how such environments operate as moral infrastructures that shape how ideals of self-fulfilment, produced within neoliberal conditions, are aligned with place-based consumption through work, thereby reimagining what it means to have a “good” workday.

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This paper shows how women data annotators in rural China negotiate ethics of care and productivity. Through state imaginaries and care infrastructures, migrant women redefine "good work," utilizing AI annotation labor as a pragmatic solution to balance economic survival and reproductive labor.

Paper long abstract

Recent critiques of the platform economy often frame data annotation as precarious "invisible labor" or "digital sweatshops." This paper draws on ethnographic fieldwork in rural "poverty alleviation" data centers in China to explore how women workers actively negotiate the ethics, values, and hierarchies of their labor. In particular, this paper focus on the phenomenon of reverse migration, where rural women leave urban areas to return to their hometowns, lured by the promise of participating in the digital economy as "AI Training Specialists."

The paper investigates three key intersections of digital infrastructure and work ethics. First, it analyzes how state and corporate socio-technical imaginaries construct a promise of modernity that redefines rural return as patriotic participation in national digital strategy. This shifts the workers’ self-conception from low-skilled laborers to creative, high-tech subjects, allowing them to claim a sense of fairness and deservingness denied to them in urban factory settings. Second, it examines the material infrastructures of care embedded in these firms, such as “Child Growth Spaces.” This paper argues these spaces represent a “post-socialist feminized practice” where the state, market, and family co-construct a regime that simultaneously absorbs productive and reproductive labor. Finally, this paper positions AI data annotation work is a "pragmatic solution" for these migrant women. By situating these laborers within shifting vernaculars of work, it reveals how they navigate the ambivalence of everyday life, synchronizing global digital demands with local care practices to define a new, albeit complex, vision of "good work."

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This paper explores the dynamics of Amazon.com package delivery platforms and work, emphasizing how the transnational corporation exploits racialized and nationalized hierarchies of social protection.

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This paper explores themes of precarity, social protection, and citizenship in the work of delivering packages for Amazon in Mexico City and Barcelona. It draws on eight months of fieldwork split between the two cities, and interviews with more than 30 participants. The research demonstrates that Amazon strategically deploys diverse recruitment schemes, from formal employment to platform work and informal subcontracting, to externalize costs and responsibilities while retaining control over operations. Drawing on the concept of global citizenship apartheid, the essay argues that the racialized and nationalized hierarchies structuring differential access to legal recognition are instrumentalized for corporate profits. It then explores how such corporate practices in a global apartheid are spatialized and embodied, illustrating the ways that individual and collective well-being are sacrificed for the accommodation of Amazon's practices in these different cities. The paper provides insight into technical standardization and social differentiation through an ethnography of platform-mediated work by exploring aspects of the contrasting national regulatory frameworks and social conditions of a single application, Amazon Flex. The study concludes that state monopolies on employment recognition, combined with transnational corporate practices, create conditions where the world system accommodates capital accumulation while denying full recognition and protection to the workers whose precarity underwrites it.

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Drawing on ethnographic fieldwork and oral narratives of gig workers in New Delhi, this paper shows how memories of past work shape entry into and persistence within gig labour. It challenges “new precarity” by situating platform work within India’s histories of informality and jobless growth.

Paper long abstract

This paper examines the oral narratives of food delivery workers to illuminate the relationship between precarity and the choice of work within India’s urban informal economy. Drawing on ethnographic fieldwork and in-depth interviews with gig workers engaged with food delivery platforms in New Delhi, it explores how memories of prior work experiences shape workers’ present engagements with platform labour. The paper argues that workers’ decisions to enter and persist in gig work cannot be understood solely through platform strategies or algorithmic management, but must be situated within workers’ longer labour histories of informality and insecurity.

Methodologically, the study is grounded in immersive ethnography. The author worked as a food delivery worker, enabling access to opaque dimensions of the labour process and facilitating trust with interlocutors. Through oral narratives, workers engaged in retrospective sense-making practices, comparing and hierarchising different labour regimes across time. These narratives reveal how gig work is evaluated relationally, against past experiences of unemployment, casualisation, and exploitative informal work.

Theoretically, the paper draws on labour process theory and debates on precarity from Global South. While much of the literature treats precarity as a novel condition associated with platform capitalism, this paper demonstrates significant continuities in precarious work conditions in India. By situating gig work within the longer trajectory of jobless growth and income insecurity following economic liberalisation in 1991, the paper challenges the dichotomy between “old” and “new” precarity. It contributes by foregrounding oral methods as a bridge between the sociology of work, labour history, and political economy.

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This paper examines how gamified incentives in ride-hailing platforms reshape drivers' work ethics in Cluj-Napoca. Drivers perceive algorithmic prompts as motivation, yet this produces overwork and dependency, revealing tensions in defining "good work" within digitally mediated platform labor.

Paper long abstract

As ride-hailing platforms restructure labor through gamified interfaces, notions of "good work" are being redefined in contested ways. This paper examines how Uber and Bolt drivers in Cluj-Napoca, Romania, negotiate autonomy, productivity, and care within algorithmically managed work environments. Drawing on 11 semi-structured interviews, 115 ride-along observations, and participation in a driver protest, the study traces how platforms gamified incentives synchronize driver labor with urban rhythms and platform profit imperatives.

Drivers perceive these prompts as motivational opportunities rather than coercion, illustrating how algorithmic management cultivates a "machine habitus" that naturalizes self-optimization. Yet beneath this perceived flexibility lies manufactured dependence: volatile earnings and intermittent bonuses compel drivers to work extended hours, sacrificing health, family time, and social ties. The platform's gamified dispositif transforms pay uncertainty into consent, aligning worker subjectivity with algorithmic demands while externalizing risks onto drivers. Ethnographic observation of a May 2025 driver protest reveals the tensions underlying collective resistance. The protest was undermined when part-time drivers, less financially dependent on platforms, continued working.

Situating this analysis within Cluj's post-socialist urban transformation—characterized by gentrification, peri-urban displacement, and infrastructural inequalities—the paper shows how platforms extract value not only from drivers' labor but also from publicly funded infrastructure and social-reproductive mobility (school runs, shift commutes). Understanding these dynamics requires attending to both algorithmic governance and the uneven social positions through which workers experience and contest "good work."

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This ethnography explores platform workers' shifting subjectivities and imaginaries of good work in Spain. It reveals how workers separate 'jobs' from 'work', constructing certainty through autonomy and reconfiguring the vernacular ethics through which they envision their productive selves.

Paper long abstract

This paper examines how people performing jobs for digital platforms negotiate shifting values of autonomy, money, and meaningful work. Whilst scholarship on platform labour emphasises precarity and algorithmic control, these framings often obscure how workers themselves reimagine what work should be and what constitutes a valuable working life. Drawing on ethnographic research with platform workers in Spain—including delivery riders, data brokers, and warehouse operators—I examine how daily encounters with digital infrastructures reshape workers' subjectivities and their imaginaries of good work.

Central to this inquiry is how workers separate "jobs" (gigs performed for money) from "work" (meaningful activity placed elsewhere: music, trading, professional aspirations). Platform workers articulate work paths where technology enables life projects, not simply constraining them, and where money becomes functional, a means to pursue autonomy, detached from stable employment as an end in itself. Neither identifying as "workers" nor organising their futures around career progression, participants navigate fragmented labour through what they value: the capacity to be "in and out" of work relationships, choosing their subjectivity on demand.

I argue that autonomy—over stability—emerges as the pivot through which platform workers construct certainty through endemic uncertainty. By attending to how money, jobs, and work are differently configured in workers' imaginaries, this research contributes to anthropological understandings of how digital platforms recast not only labour conditions but the vernacular ethics through which people envision their productive and moral selves.