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This chapter is concerned with examining Pokémon Go in light of the digital economy and surveillance capitalism. The chapter begins by developing the theoretical framework underpinning this undertaking, which includes Bauman and Lyon (2013) ‘liquid surveillance’ and Zuboff's (2019) ‘surveillance capitalism’. Following this, we outline the various implications involved in the playing of Pokémon Go, when the production of locative data is not framed as leisure but labour. While Pokémon Go might be suited to the machinations of surveillance capitalism, as we establish, little research has examined this topic from the position of familial locative play or joint-media engagement. As a corollary to this, then, one of the aims of this chapter is to understand how issues of surveillance are perceived by the parents who play this hybrid reality game (HRG) with their children. Consequently, the chapter is driven by the following research questions. First, are families cognisant of the data they produce by playing this HRG, and how these data might be used? Second, do families think critically about the gamic mechanics of this HRG, such as the spawning locations of Pokémon and the reasoning behind these decisions? Third, are participants concerned about the potential application of their gamic data, and if so, how are these concerns reconciled? Fourth, do participants use the familial playing of Pokémon Go as an opportunity to discuss the production of data and its multifaced uses with their children?

This paper examines how contemporary workplace surveillance can simultaneously incentivize and commodify workforce behavior. Specifically, workplace surveillance is reconceptualized as rent-seeking, which offers a framework for analyzing novel employer-employee relationships stemming from alternate views of risk and reward.

The case of workplace microchipping is studied qualitatively as a backdrop for theorizing emergent labor relations in the context of surveillance capitalism and biopolitics.

Reconsidering surveillance within the context of personal risk and entrepreneurial lure offers much to 21st century discourse on labor and supervision. It is imperative that the public sector engages in appropriate regulatory protocols to manage emergent behavior in organizations.

This study departs from the popular conceptualization of human microchipping as an intersection of legal and ethical considerations of surveillance. Instead, the authors examine a different aspect of the microchipping phenomenon, taking into account employee creative reactions to employer surveillance in the context of risk and return.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2022-0009

Research suggests that centers of calculation, empowered by accounting inscriptions, are similar to maps: they provide a useful, albeit simplified, version of reality. The purposes of this paper are to examine whether and how digital platforms change the nature of centers of calculation, and to improve the understanding of the relationship between digital platforms and accounting.

An in-depth, single case-study design is used to empirically investigate how a Nordic hotel chain competed with global online travel agencies (OTAs) in the quest for the “new oil”—customer data.

The paper demonstrates how the case organization created a local alternative to global digital platforms with the aim of acquiring customer data, thereby moving from a center of calculation (CoC) to what authors label a “center of data appropriation” (CDA). While CoCs are guided by accounting inscriptions that enable “mapping”, CDAs are constructed around accounting inscriptions with other properties that enable digital “mirrors” of the economic domain. The authors find that this has two governing effects. First, multiple centers emerge that compete for access to the periphery. Second, future forms of competition can follow dynamic trajectories, where mutual dependence between CDAs may lead to coopetition.

Scholars have suggested that surveillance capitalism creates market-power imbalances. This study indicates that the transformation of local organizations into CDAs enables them to challenge global digital-platform organizations. Therefore, authors argue that local organizations may retain some market power by establishing local CDAs.

The chapter critically analyzes the concepts and the practices of surveillance in modern and postmodern societies along with their consequences. We show the changes in the systems, which are used to monitor individuals, and emphasize the transition toward soft surveillance systems, probably stimulated by digital technologies. This switch from top-down control to “lateral” monitoring systems encloses surveillance practices with suggestive names like interveillance, synopticon, and dataveillance. The dark side of digital health has a bright start. According to Topol’s (2016) vision of the future, we will soon be the “consumers,” the real protagonists, of the management of our health – thanks largely to the practically endless data about our bodies, behaviors, and lifestyles we will be able to collect and analyze. We will share our health information in real time with the doctors whom we will choose based on their score in clinical rankings (here, too, quantification rears its head). Yet, this simplified version of health makes it seem that there are always some solutions, which the algorithm can supply as long as it has enough information. Moreover, in the United States, some health-insurance companies have started to offer a discount on premiums to the members who agree to collect and share self-tracking data with them. Clearly, the discount is given only to the workers who have healthy habits. At first sight, this can seem as a win-win trade-off; however, what today is presented as an individual option can easily become a requirement tomorrow.

The paper argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”. Big data platforms are shaping the processes of production, labour, the price of products and market conditions. “Digital platforms” and “big data” have become an integral part of the processes of production, distribution and exchange relations. These twin pillars are central to the capitalist accumulation processes. The article argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”.

As a conceptual paper, this paper follows critical methodological lineages and traditions based on non-linear historical narratives around the conceptualisation, construction and transition of the “Marxist theory of capital accumulation” in the age of platform economy. This paper follows a discourse analysis (Fairclough, 2003) to locate the way in which an artificial intelligence (AI)-led platform economy helps identify and conceptualise new forms of capitalist accumulation. It engages with Jørgensen and Phillips' (2002) contextual and empirical discursive traditions to undertake a qualitative comparative analysis by exploring a broad range of complex factors with case studies and examples from leading firms within the platform economy. Finally, it adopts two steps of “Theory Synthesis and Theory Adaptation” as outlined by Jaakkola (2020) to synthesise, adopt and expand the Marxist theory of capital accumulation under platform capitalism.

This article identifies new trends and forms of data driven capitalist accumulation processes within the platform capitalism. The findings suggest that an AI led platform economy creates new forms of capitalist accumulation. The article helps to develop theoretical understanding and conceptual frameworks to understand and explain these new forms of capital accumulation.

This study builds upon the limited theorisation on the AI and new capitalist accumulation processes. This article identifies new trends and forms of data driven capitalist accumulation processes within platform capitalism. The article helps to understand digital and platform capitalisms in the lens of digital labour and expands the theory of capitalist accumulation and its new forms in the age of datafication. While critiquing the Marxist theory of capitalist accumulation, the article offers alternative approaches for the future.

The paper aims to investigate how accounting techniques, when embedded within data-driven public-sector management systems, mask and intensify the neoliberal ideological commitments of powerful state and corporate actors. The authors explore the role of accounting in the operationalisation of “instrumentarian power” (Zuboff, 2019) – a new form of power that mobilises ubiquitous digital instrumentation to ensure that algorithmic architectures can tune, herd and modify behaviour.

The authors employ a qualitative archival analysis of publicly available data related to the automation of welfare-policing systems to explore the role of accounting in advancing instrumentarian power.

In exploring the automation of Australia's welfare debt recovery system (Robodebt), this paper examines a new algorithmic accountability that has emerged at the interface of government, technology and accounting. The authors show that accounting supports both the rise of instrumentarian power and the intensification of neoliberal ideals when buried within algorithms. In focusing on Robodebt, the authors show how the algorithmic reconfiguration of accountability within the welfare system intensified the inequalities that welfare recipients experienced. Furthermore, the authors show that, despite its apparent failure, it worked to modify welfare recipients' behaviour to align with the neoliberal ideals of “self-management” and “individual responsibility”.

This paper addresses Agostino, Saliterer and Steccolini's (2021) call to investigate the relationship between accounting, digital innovations and the lived experience of vulnerable people. To anchor this, the authors show how algorithms work to mask the accounting assumptions that underpin them and assert that this, in turn, recasts accountability relationships. When accounting is embedded in algorithms, the ideological potency of calculations can be obscured, and when applied within technologies that affect vulnerable people, they can intensify already substantial inequalities.

The initial jurisprudential response to the gig economy above has included the exploration of two new legal personae: algorithmic persons and dependent contractors. The author uses the word ‘exploration’ here, because neither figure has become an established character on the legal landscape in the United States – yet. Given the sector’s claims of absolute novelty, it may seem that the best way to develop regulations is to identify new positions and actors, define them, and then apply existing regulations and expectations or develop new ones accordingly. This chapter explains why this approach is misguided. First, legal personae have only a tangential relationship with actually existing human beings. Much regulatory energy could be caught up in elaborate definitions and descriptions intended to develop robust regulation, only to find that they create the blueprint for future business models that avert these very frameworks. Second, these legal personae are developed within the existing frameworks of employment law and corporate regulation, which in the United States, are determined by a phantasmagoric understanding of ‘the market’. Unless this basic framework is questioned, one can expect that these new legal personae will fail to protect actual workers and consumers.

Big data are indispensable in scientific endeavours ranging from nuclear research to climate studies. However, there is a growing misperception that congeries of data can be easily reconstructed into competitive business insights. Such notions have been encouraged by a plethora of mainstream techno-utopian forecasts.

This paper investigated such claims and related big data developments, including its “systems-first” and oligopolistic orientations. Due to the paucity of current scholarship on an admittedly pessimistic topic, the paper studied contrarian developments in the industry by relying on secondary data. The study of experts and scholars; industrial trends; and discrepancies and critical gaps in the mainstream data narrative were sourced to prognosticate the likely trajectory of many data giants.

A key finding was that the big data industry faces an untenable market bubble worth trillions of dollars. This will have severe consequences for common digital access and social stability worldwide. Evidence presented also suggests that the data industrial complex may undergo a function creep by facilitating a transition from surveillance capitalism to surveillance society.

Primary data for a study of this nature may take years to materialize. This is a “first-pass” study that seeks to illuminate latent dangers facing the big data/AI sector. There is a paucity of scholarly study that even remotely touches on this topic. Therefore, supporting arguments was sourced from contemporary reports and expert study (secondary data).

As control of data may have geostrategic implications, balkanization of the wired ecosystem may be underway with Russia and China leading the way. Future superpowers may be defined by the way they handle data. The concentration of data in fewer hands may also affect citizen innovation.

A break-down of the data industrial complex may lead to social mayhem as the monetization of presently free software, blogs and social media platforms may be unfeasible.

This topic has hardly been explored due to the novelty of big data, its applications and the daily hype over its potentials. This paper boldly describes dark countercurrents in the industry.