Chapter 7
Conclusion: A risk factor framework for OSH, digitalization and forms of employment

The aim of this research project and report has been twofold: First, we have sought to advance the empirical understanding of occupational safety and health (OSH) risk factors related to different forms of non-standard employment and digitalization, such as field technologies and digital platforms. Our second aim has been to use this knowledge to develop a risk factor framework that can be useful for Nordic labour inspectorates to assess potential risk factors at individual workplaces. This chapter endeavours to achieve this second aim, drawing on insights from the case studies, the scoping review (Bråten and Thorbjørnsen, 2023), feedback from the project workshops and other key sources. 

At one of the project workshops with representatives from Nordic labour inspectorates,

7 December 2023.

one of the participants argued that keeping up with new forms of platform-mediated gig work felt like “running after a quite rapid development”. Hopefully, the insights and proposals gathered in this chapter can contribute to “taming the treadmill” and strengthening the toolbox of the Nordic labour inspectorates. Accordingly, this chapter has been written to be accessible to an audience beyond the usual research community. 

The chapter is structured as follows. First, we provide an overview of the relevant OSH dimensions (psychosocial and organizational) and some of the ways in which new technology has been reshaping OSH challenges. In section 7.3, we present and discuss our risk factor framework. This framework is designed to provide labour inspectorates with a conceptual overview of potential risk factors and thereby be useful before and during inspections in digitalized work arrangements. A total of seven risk factors are discussed: isolation, deskilling, worker turnover, piece-rate precarity and stress, reduced autonomy, control and surveillance, and increased OSH fragmentation. The final section summarizes the risk factors and discusses regulatory challenges associated with OSH, digitalization and non-standard forms of employment.

As this and previous research has shown, current rapid technological development has significant consequences for how work is conducted and how workplaces, labour processes and labour markets are structured and organized. As such, digitalization and other technological innovations can create new occupational safety and health risks (Cockburn, 2021; EU-OSHA, 2018; Oppegaard and Bråten, Chapter 2). At the same time, new technologies also recast and reiterate existing risk factors. Surveillance, for example, did not emerge as an OSH challenge with the introduction of monitoring technologies such as GPS tracking and digital devices, and time pressure at work is not in itself a result of algorithms assigning workers tasks. Moreover, the OSH risk factors created by new technologies coexist with those emerging from the labour processes. As Huseby shows in Chapter 3, cleaners working for digital platforms continue to be exposed to labour process–specific risk factors associated with cleaning while also working within the highly digitalized work arrangement of the platform. This highlights the importance, for researchers as well as labour inspectorates, of avoiding being blinded by the newness of digital technologies and letting “shiny new objects” obscure our assessment of the effects of technology at work.

A similar argument can be made regarding non-standard forms of employment, which have been characterized as OSH risks (Cummings and Kreiss, 2008; Howard, 2017; Oppegaard and Bråten, Chapter 2). Increases in the share of self-employed workers and other non-standard forms of employment have long been associated with emergence of the so-called new economy and “post-industrial society” (Lipset and Bendix, 1959). Today, the notion of the “Uberization” of the economy frames the development as one where workers no longer find permanent employment, only fragmented “gigs” (see Davis, 2016). Such generalizations have to be approached with caution. First, self-employment and non-standard forms of employment are not new phenomena; they were prevalent in the early phase of capitalism (Stanford, 2017) and in the major capitalist economies in the period before World War II (Steinmetz and Wright, 1989). Second, while the decline in self-employment rates in the post-war era was followed by a revival from the 1970s (Bögenhold and Saber, 1991; Steinmetz and Wright, 1989), non-standard forms of employment vary between different regulatory regimes and labour market models. In the Nordic countries, they have recently remained a stable and relatively marginal phenomenon (Rasmussen et al., 2019). There are, however, important differences between industries (Nergaard, 2018) and different forms of non-standard employment (Cools et al., 2023). 

These nuances must be kept in mind when evaluating and analysing the potential effects of new technologies and work arrangements. The aim of this chapter and our risk factor framework is therefore to show how OSH risks can be articulated through digitalization and across different forms of employment.

This section presents our risk factor framework and subsequently explains each risk factor in detail. Drawing on our previous literature review (Bråten and Thorbjørnsen 2023), previous research and evaluations (see Christensen et al. 2020, 2021; Foldal et al., 2023; Mattila-Wiro et al. 2020), the project workshops

Representatives of the Nordic labour inspectorates were invited to two digital workshops (1 Dec 2022 and 7 Dec 2023) to share their experiences and to give input on the preparation of a conceptual risk factor framework.

and our new empirical studies from the preceding chapters, we have identified seven key occupational safety and health risk factors associated with digitalization of work and non-standard forms of employment. These have been distilled into a risk factor framework (see Table 7.1).

A draft version was presented at a webinar with the Nordic inspectorates on 7 December 2023, and we are grateful to the participants for their constructive feedback.

An important aspect of our project has been to explore how technology-related risk factors are also affected by employment status. Non-standard forms of employment in general can constitute an independent risk factor, but this project has also shown that technology-induced risks are mediated and shaped by workers’ employment status. The framework therefore distinguishes between risk factors for workers who are classified as employees and those who are self-employed. This is the key legal distinction in Nordic labour law, and it has significant consequences for workers’, employers’, and other authorities’ rights and obligations (Alsos et al., 2022; Hotvedt et al., 2020). Importantly, self-employed workers are generally not covered by working environment legislation and have limited rights in relation to collective organization and negotiation, and labour inspectorates may have limited authority to require compliance with OSH standards and regulations. This, as will see below, tends to heighten the OSH risks for these workers.

The following framework therefore explores the interaction between digitalization and forms of employment, assessing the potential risk level for each identified risk factor for employed and self-employed workers. While it is important to highlight that new technologies in some cases can also lead to better OSH and safer and healthier working environments (see Christensen et al., 2020), this project is concerned solely with mapping OSH risks. We review each risk factor, first defining the risk and subsequently exploring the dynamics of employment status. Importantly, however, the risk factors identified remain merely risks and, as such, potential. In practice, workplaces and labour processes tend to exhibit their contextually specific dynamics – and the factors highlighted below must be investigated through close empirical inspection of the realities on the ground. The aim of this framework is therefore to explore tendencies immanent in the digitalization of work and non-standard forms of employment and map potential risk factors.

Table 7.1 OSH Risk factor framework

The first risk factor associated with remote and lone work is isolation (Ropponen et al., 2019). As digital technologies open up new possibilities for remote work, workers have new opportunities to perform more work outside fixed workplaces. An example of this could be the use of home offices, made possible by digital co-working technologies, which has caused workers to become more physically disconnected from the office environment. Field technologies, furthermore, enable workers in a number of industries to perform their job while far away from a traditional workplace and colleagues (Tranvik and Bråten, 2015). The risk of isolation is also notable in platform-mediated gig work, as the empirical chapters on cleaning and food delivery show (see also Wells et al., 2021). Platform workers usually work alone, guided throughout the labour process by the platform technology, and previous studies have found that they report high levels of loneliness (Glavin et al., 2021).

This suggests that digitalization enables new work arrangements that can potentially reduce interaction and communication between workers within an organization and increase the risk of isolation (Bråten and Thorbjørnsen, 2023; Håkansta, 2022). This is in itself a psychosocial risk factor, but isolation can also heighten the risk of workers not being informed about or integrated into OSH work and routines. Remote and mobile workplaces, made possible by new digital technologies, can also make it more difficult for labour inspectorates to ensure compliance with OSH standards and regulations. 

Isolation is a risk factor for both employed and self-employed workers in digitalized work arrangements. There is, however, reason to assume that the OSH risks associated with isolation tend to be greater for self-employed workers. Being self-employed, they are individualized and do not formally have any colleagues or a fixed or virtual workplace community (Ropponen et al., 2019). Still, empirical case studies find that platform workers in many cases nonetheless come together, build communities and mobilize collectively, despite their self-employment and dispersed labour process (see for example Tassinari and Maccarrone, 2020). This is also the case in the Nordic countries, and our case study of platform-based food delivery in Denmark and Norway found that workers engage with each other in the field (Jesnes and Rasmussen, chapter 5).

A second OSH risk factor associated with the digitalization of work is “deskilling”. The notion of deskilling refers to the reduction of skill requirements for performing a job. Deskilling has been identified as a tendency linked to the implementation of new technologies in the labour process as this might simplify work tasks and lower competency requirements, thereby making it possible for employers to cut costs by replacing higher paid workers with lower paid “unskilled” workers (Braverman, 1974). While there is little evidence of a tendency towards broad deskilling in the Nordic labour markets at an aggregate level (Rolandsson and Dølvik, 2021), this dynamic can still be found in specific workplaces, where the digitalization of work tasks and labour processes can be organized in new ways, reducing competence requirements (Schaupp, 2022b; Shibata, 2023).

Digital technologies might, for example, be used to guide workers throughout the labour process, continuously and flexibly providing directions. Thus, digitalization reduces the requirement for labour process–specific skills and language knowledge, as well as reducing the need to provide workers with formal and informal training. Gig platforms’ “algorithmic management” and field technologies in logistics illustrate their digital capacity to give workers instructions in real-time (Oppegaard, 2023; Oppegaard and Bråten, Chapter 2; Vallas et al., 2022). Such digital technologies might therefore enable recruitment of “unskilled” workers, facilitating the exploitation of already marginalized segments of the labour force (Altenried, 2022). This is clearly the case in platform-mediated gig work, where workers often are migrants, who have few other labour market opportunities and come to their “gig” from unemployment or other precarious jobs (Huseby, Chapter 3; Jesnes and Oppegaard, 2023; Jesnes and Rasmussen, Chapter 5; Seppänen, Chapter 6).

Deskilling can be considered an OSH risk factor insofar as it increases workers’ dependence on technology, reduces employers’ and companies’ incentives to invest in their workers’ competencies, and shifts the power balance between workers and employers in favour of the latter. OSH risks might also be heightened as workers are recruited from precarious positions in the labour market, who can be in increased need of protections, without being integrated into a workplace community, as discussed above in context of the risk of isolation. As we will see below, deskilling can also contribute to higher turnover rates and reduced worker autonomy. 

A risk factor closely related to deskilling is that of worker turnover. Implementation of new technologies might increase turnover rates, under certain conditions and if they, for example, increase the pace and stress of work, reduce autonomy or are used for surveillance (Christensen et al., 2020). More generally, however, technologies that are used to standardize the labour process and reduce knowledge and skill requirements can make it easier and cheaper to replace workers, facilitating flexible and scalable workforces (Altenried, 2020). Such a tendency is likely to be reinforced when technological deskilling is combined with non-standard forms of employment, which themselves are found to lead to greater worker turnover (Schulte et al., 2019).

While physically hazardous working conditions and injuries at work can increase worker turnover (Cottini et al., 2011; McCaughey et al., 2013), high turnover rates can themselves, indirectly, constitute an OSH risk factor. First, worker turnover and the flexibilization of organizations can make workplaces increasingly fragmented. On the one hand, this can make it more difficult to sustain efficient OSH routines. On the other hand, it can also make labour inspectorates’ enforcement of OSH legislation increasingly complicated. Second, high turnover rates and the ease of replacing workers can reduce employers’ and companies’ incentives to provide a work environment that promotes OSH. Furthermore, a digitalized work environment that facilitates high worker turnover and replaceability of workers might also increase employers’ and companies’ relative power over workers, limiting workers’ capacity to demand a safer and healthier work environment.

By enabling efficient coordination, digitalization makes new organizational forms possible. As we have seen, one tendency is more fragmented workplaces, associated particularly with platform-mediated gig work (Davis, 2016). In these work arrangements, workers are classified as self-employed contractors and paid per “gig” they compete. Digitalization of work, particularly the rise of platform-mediated gig work, has thus led to a resurgence of the piece rate model (Moore and Joyce, 2020; Stanford, 2017). Piece rates should not be seen as a consequence of digitalization, but rather as a managerial technique made possible by the increased fragmentation of organizations and workplaces facilitated by new technologies.

Research has shown that platform workers tend to earn relatively low and unpredictable wages (Piasna et al., 2022). Since they are paid a piece rate, they also adjust their work schedules to demand, often having to work unsocial and long hours to make a living (Jesnes and Oppegaard, 2023; Oppegaard, 2021, 2023), which can constitute a significant OSH hazard (Samant, 2020). Moreover, and as the empirical analyses in the previous chapters show, unpredictable earnings are a significant stress factor for some platform workers (Huseby, Chapter 3; Jesnes and Rasmussen, Chapter 5). Digitalization of work, when combined with fragmented organizational and payment models, might therefore lead to what can be termed piece rate precarity and stress. This is a psychosocial risk factor prevalent in platform-mediated gig work (Bérastégui 2021; Lenaerts et al., 2021). 

For self-employed workers, however, the piece rate model is generally nothing new. Self-employed workers in non-digital work arrangements also tend to be dependent on demand for the services they sell to earn an income. This is the case with taxi owners, for example, who in most markets were classified as self-employed business owners long before the rise of platforms such as Uber (see Aarhaug et al., 2020). While traditional self-employed workers in many industries are able to determine their own prices, and thus influence their wages, self-employed workers in the platform economy generally have little to no influence over the price of their services, increasing their dependence on fluctuations in demand and the unpredictability of their income. Piece rate models can also be combined with traditional employment relationships. In these cases, workers are usually legally allowed to unionize and bargain collectively, increasing their influence on their earnings and potentially limiting the precarious effects of the piece rate model. The case of the food delivery platform Foodora in Norway, some of whose workers are classified as employees and signed a collective agreement after a strike in 2019, illustrates this (see Jesnes and Oppegaard, 2023; Jesnes and Rasmussen, Chapter 5).

As we have seen above, digital technologies can be used to standardize and routinize the labour process, leading to reduced worker autonomy (Schaupp, 2022b; 2022a). Autonomy has been found to be a work characteristic that promotes job satisfaction, motivation and high-quality jobs (Parker et al., 2001), and it constitutes an important aspect of the psychosocial work environment (Christensen et al., 2020).

As we will see in the next section, reduced worker autonomy through digitalization of work is a pertinent issue in platform-mediated gig work, where gig platforms often exercise significant control over the labour process through “algorithmic management” (Lee et al., 2015; Moore and Joyce, 2020; Oppegaard, 2023; Oppegaard and Bråten, Chapter 2). Platform workers are often recruited by the promise of flexibility and autonomy (Jesnes and Oppegaard, 2023; Seppänen, Chapter 6), but in the labour process they are subject to digital control techniques that in practice limit their capacity for autonomy (Altenried, 2020). The formal flexibility gig platforms promote has therefore been described as a “fictitious freedom” (Shibata, 2020).

The potentially negative consequences of reduced worker autonomy through digitalization are likely to be exacerbated if workers are classified as self-employed contractors. This employment status is fundamentally based on service providers having flexibility and autonomy to determine the conditions under which they work – such as when and how long they work, how they perform their labour and so on. This freedom legitimizes the lack of regulation of their working environment. For self-employed workers, significant OSH risks might therefore arise when their labour processes are controlled by digital technologies that limit their flexibility and autonomy without them being granted the rights and protections following from traditional employment relationships.

On the other hand, new technologies can also be used to increase workers’ autonomy (see Christensen et al., 2020; Leso et al., 2018). For example, if new technologies are deployed to automate physically demanding and monotonous tasks, workers might gain increased autonomy and supervise and monitor semi-autonomous production systems to a greater extent. This can increase workers’ capacities for decision-making and required skills. As such, this process can be termed “upskilling”. This scenario illustrates that the effects of new technologies remain open-ended and highlights the importance of investigating how particular technologies are used in practice in specific cases.

As work becomes more digitalised, and data is generated and processed in real time, there are new possibilities to monitor, control and coordinate workers’ labour processes. In the case of platform-mediated gig work, this form of control is often labelled “algorithmic management” (Lee et al., 2015; Wood, 2021). The fact that new technology has implications for control and coordination is not new, but what is important with new digital technology is the way in which it generates an increasing variety of information (data) in real time, which could potentially be misused for negative control and surveillance at work (Oppegaard and Bråten, Chapter 2).

Gig platforms control workers through a triadic constellation of algorithmic task assignment, economic incentives and rating systems (Lee et al., 2015), usually combined with organizational techniques such as piece rate payment and self-employment (Moore and Joyce, 2020; Oppegaard, 2023). In these work arrangements, workers’ earnings and working time are shaped by the technological determination of the number of available tasks and prices. Workers also risk being “deactivated” if they receive poor ratings. “Algorithmic management”, sometimes described as a form of “digital Taylorism” (Altenried, 2020), furthermore operates through mechanisms that often are experienced as opaque from the perspective of workers, who often have limited opportunities to discuss or dispute the platforms’ decisions (Oppegaard and Jesnes, forthcoming; Seppänen, Chapter 6). The empirical analyses in the preceding chapters show that this form of control can create a significant stress for workers and should be regarded as an OSH risk factor (see also Bérastégui, 2021; Randolph, 2019; Samant, 2020).

Beyond the specific case of platform-mediated gig work, however, digitalization of work and the use of field technologies enables more extensive and intensive forms of surveillance (Tranvik and Bråten, 2015). As an increasing number of the aspects of workers’ labour process are recorded digitally and in real-time – including output, movements, keystrokes and biometrics – new features of workers and their work can be monitored. The increased surveillance capacity enabled by new technologies can therefore constitute a key OSH risk factor in digitalized work arrangements. 

The OSH dimensions of control and surveillance, however, also vary depending on workers’ employment status. In contrast to self-employed workers, employed workers are more likely to be protected by legislation curbing potentially hazardous effects of control and surveillance. They might also have access to representatives that can negotiate whether, what, and how new technologies are implemented (Andersen and Bråten, forthcoming).

A common thread among the points discussed above relates to how digitalization reshapes the relationship between companies and workers, both formally and in the labour process, and how this in turn is linked to OSH. A final important OSH risk factor identified relates to the regulation and enforcement of OSH standards and routines: the potential of increased OSH fragmentation.

First, the new types of work arrangements, flexible organizations and new forms of control that digital technologies enable can make it more difficult to ensure that workers and their work environments are encompassed by OSH standards and routines. This is an issue that pertains to both companies and labour inspectorates. Workers might, for example, work outside fixed workplaces, work alone and outside the purview of human managers and colleagues, have short tenure in an organization or be subjected to opaque forms of digital management. Such factors can make it complicated for companies to organize OSH routines and for workers to know their rights. 

Second, non-standard forms of employment – whether combined with a digitalization of work or not – are an OSH risk factor because workers might not be covered by working environment legislation. This can fragment OSH responsibilities. In some cases, these might be shifted onto the workers themselves, which can be particularly problematic if workers are subject to fluctuations in demand and potentially dependent on long working hours to make a living. For the labour inspectorates, non-standard forms of employment might mean, moreover, that they do not have the authority to enforce OSH standards and routines (see Jesnes and Rasmussen, Chapter 5).

The above framework has highlighted seven key occupational safety and health risk factors associated with digitalization of work across different forms of employment: isolation, deskilling, worker turnover, piece rate precarity and stress, reduced autonomy, control and surveillance, and increased OSH fragmentation. The framework, the discussion of the risk factors and our empirical analysis in the previous chapters of this report suggest that non-standard forms of employment, in particular self-employment, heighten the OSH risks arising from the digitalization of work.

Importantly, the framework only identifies OSH risk factors and thus potential hazardous work environment exposures. Actual outcomes depend on a myriad of different factors and must be assessed in practice and within specific contexts. This chapter has nonetheless shown that the digitalization of work poses significant challenges to workers’ OSH through the use of new tools and technologies in the labour process, new forms of digital control, new and flexible work arrangements and the facilitation of non-standard forms of employment. These challenges are illustrated particularly clearly in the case of platform-mediated gig work.

The future of work will depend on many other factors besides technology alone – but new technologies can be a catalyst of change in the world of work. This requires that we pay close attention to both their potential and actual effects. The current surge in the development and implementation of so-called artificial intelligence technologies is but one example of a process that has to be monitored attentively from an OSH perspective. As this report has highlighted, technologies do not necessarily create only new OSH challenges: They also, and in many cases more importantly, reshape and reiterate well-known work environment risks. This indicates that authorities tasked with regulating and enforcing OSH standards and routines are not starting from scratch when approaching the risk factors introduced by digitalization, for example. Furthermore, industry– and labour process–specific risk factors are likely to remain key risk factors for workers in digitalized work arrangements, as our case studies of platform-mediated gig work in cleaning and food delivery show (Huseby, Chapter 3; Rasmussen, Chapter 4; Jesnes and Rasmussen, Chapter 5). In addition, it is also crucial to mention that new technologies can contribute to a safer and healthier work environment for workers. This has not been the focus of this project, however, and more research on how digital technologies can improve OSH is needed. However, ensuring safe and healthy work environments still requires that the transformations of work brought about by new technologies be continuously monitored.

Nonetheless, there are regulatory challenges association with OSH, digitalization, and non-standard forms of employment. First, as employers and companies continue to develop and implement new technologies, regulations must ensure that these in themselves and the ways in which they are used do not pose OSH hazards to workers. Digital control and surveillance are issues that might be particularly pertinent in this regard, and it is imperative to make sure that existing OSH regulations are upheld and enforced in the context of new technologies. A second challenge revolves around non-standard forms of employment. OSH for workers in non-standard forms of employment is particularly precarious as working environment legislation is tied to employment status in many cases, potentially excluding atypical workers from necessary protection. While these challenges are not new, as we have emphasized, the possible misclassification of workers as self-employed contractors rather than employees has become a key issue in labour law over the last few years, exacerbated by the rise of platform-mediated gig work (Hotvedt et al., 2020). A third regulatory challenge pertains to ensuring that OSH standards and routines are upheld and enforced in fragmented work arrangements. Facing these predicaments, it might be necessary to develop regulatory responses at the national and supranational levels, as well as through collective agreements at the industry and workplace levels. The latter strategy, however, requires that unions be able and permitted to take an active role in decisions regarding technologies at work (Andersen and Bråten, forthcoming; Hagen and Oppegaard, 2020).

Finally, it is important to facilitate labour inspectorates’ capacity to enforce OSH standards and regulations in an unpredictable and rapidly changing world of work. Previous reports have shown that there is untapped potential for cross-country collaboration between the Nordic inspectorates (Foldal et al., 2023; Mattila-Wiro et al., 2020; Ødegård and Eldring, 2016). Hopefully, the risk factor framework developed in this chapter – and the analysis from the project more broadly – can contribute to “taming the treadmill” and assisting Nordic labour inspectorates in keeping up with the effects of the high-paced digital transformation.

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