Regulating labour platforms, the data deficit

Hawley, Adrian John Article Regulating labour platforms, the data deficit European Journal of Government and Economics (EJGE) Provided in Cooperation with: Universidade da Coruna Suggested Citation: Hawley, Adrian John (2018) : Regulating labour platforms, the data deficit, European Journal of Government and Economics (EJGE), ISSN 2254-7088, Universidade da Coruna, A Coruña, Vol. 7, Iss. 1, pp. 5-23, https://doi.org/10.17979/ejge.2018.7.1.4330 This Version is available at: https://hdl.handle.net/10419/217761 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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European Journal of Government and Economics ISSN: 2254-7088 Regulating labour platforms, the data deficit Adrian John Hawleya, * a Royal Holloway, University of London, United Kingdom * Corresponding author at: School of Management, Royal Holloway, University of London, Egham TW20 0EX, United Kingdom. email: [email protected] Article history. Received 24 January 2018; first revision required 23 April 2018; accepted 22 May 2018. Abstract. It is widely reported that there is a data deficit regarding working conditions in the gig economy. It is known, however, that workers are disadvantaged because they are not classed as employees with the result that they lack work-related entitlements and may not be protected by the social welfare safety net. Nor is this compatible with the social market economy enshrined in the European Union treaties. Two obstacles are that labour law and social policy are mainly a national competence and that platforms are reluctant to share data with regulators. In this paper I take the specific case of offline labour platforms intermediated by app and smart phone such as driving and delivering and look for new pathways between access to data and the shaping of public policy in member states with potentially legal certainty.. Keywords. Data; gig economy; social market; labour platforms; public policy; soft power 1. Introduction 'A paradox in the digital and Internet economy is that never before has so much data been collected, and never before has it been so difficult to access. The value of this data is likely to be much higher for social and public policy purposes than it is for private purposes of the platform operators' (Codagnone, Biagi and Abadie 2016:60,61) The labour platform model of the gig economy offers popular services but depends for its competitive advantage over established service providers on low wages, precariousness and lack of in- or -out of work entitlements and benefits. This raises the question of its compatibility with the concept of the social market enshrined in the European Union (EU) treaties, specifically with regard to employment practices. There are different models of the social market throughout the EU but it has been broadly defined as a 'fundamental social model that ensured people’s rights, inclusion to social protection, a good wage model that shared productivity through collective bargaining and social dialogue' (Burrow 2018) and, specifically, 'the creation of a world of work that is humane, socially balanced and sustainable' (Jürgens, Hoffmann and DOI. https://doi.org/10.17979/ejge.2018.7.1.4330 A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 6 Schildmann 2017:222). This is reflected in the concept of 'good work' in the gig economy by Taylor (2017) who measures it against a number of criteria such as, 'employment quality, working conditions, consultative participation and collective representation in addition to wages' and also 'good gigs' by Balaram, Warden and Wallace-Stephens (2017) and as 'Gute Arbeit' in Germany (German Federal Ministry of Labour and Social Affairs 2017). With the rise of the gig economy is there a need therefore for new regulation or are existing rules being breached or evaded? How do we know? This is a question of data, its availability and quality. Two important considerations are the role of the EU, since labour law is mainly a national competence, and the perennial cleavage of opinion about when and whether to regulate any economic activity. It is, however, the subject of data in relation to working conditions in the gig economy, and specifically to labour platforms, which is principally addressed in this paper. Labour platforms do not provide the entitlements generally expected for their workers because they do not accept that they are employees. There is little if any corroborated, independent data, however, on how much they are paid, the hours they work, discrimination of any kind, the transparency of rating systems and opportunities for worker training and representation. We do not know much about their conditions except anecdotally and what platforms are willing to tell us through the medium of a few privileged researchers. By contrast, independent survey data presents a per country aggregate of demographics, people’s motivations and total hours worked on platforms. Except in one case that I have found (Balaram, Warden and Wallace-Stephens 2017) they do not reveal data on conditions on specific platforms. Nor, why should the latter reveal them for competitive or any other reasons? Since their workers are generally treated as self-employed, even though they may be largely or even wholly dependent upon a single platform, their conditions presently do not fall under national labour law regulations, for example, the minimum national wage (or minimum living wage in the United Kingdom) or transposed EU legislation in the case, for example, of the Working Time or Written Statement directives. Extending benefits to workers on labour platforms in the gig economy will require changes in public policy which is a political decision. In an exceptional case, a tribunal (Employment Tribunals 2016; Employment Appeal Tribunal 2017) has ruled in favour of the claim by some London-based drivers of Uber, a ride-sharing service, to limited entitlements. The decision, however, does not have universal effect in the United Kingdom (UK). Both in the formulation and implementation of new rules or the extension of existing ones, data will need to be accessible from platform operators. Generally no such data are shared directly by them with any national authority with the very recent exception of France in the case of payment of taxes. If new rules apply, does that mean that, for compliance, platforms will be mandated to supply certain data? They are unlikely to do so on a voluntary basis. And how might this be achieved without revealing commercially sensitive data or failing to protect the privacy of personal data as required by the General Data Protection Regulation which became effective throughout the EU in May 2018? In the first half of this paper I start with a definition of what is meant by the catch-all term of A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 7 the 'gig' economy and the part described as 'labour platforms' with which this paper is concerned. There follows an overview of the literatures of organisation and management, paradigms of political economy and cultural responses towards rapid technological change that may have some explanatory value for the rise of the phenomenon and also differing attitudes towards it. These differences, I show, are being played out in an EU context as well as a national one. The second half of the paper is devoted to how data might be acquired and put to work systemically to improve the conditions of gig workers. I start with a brief review of the data from surveys and studies carried out in Europe and the United States. If there is a change in public policy, the “elephant in the room” however, will be data compliance by platforms, an issue which looks as though it will present formidable obstacles and one on which little research has been done with the notable exception of Arun Sundararajan (2017). I sketch out his approach generally known as 'shared regulation' and the few others with the similar objective. Since labour law and social policy are mainly national competences I consider the EU's use of soft power to achieve its objectives in this field. Specifically I look for a pathway between access to data on working conditions and legal certainty in establishing minimum standards for workers. Finally, I conclude by suggesting further areas of research for a deeper evaluation of opportunities for change in this field following the recommendations and principles of the recently proclaimed European Pillar of Social Rights (EC 2017). 2. Defining the ‘gig economy’ There is no precise definition in the literature which contributes to the difficulty in measuring it. The EU still refers to it by the loose, catch-all term 'collaborative economy' which could include both for-profit and not for-profit models and those where only the expenses of providing the service are recovered plus a small percentage (e.g. Blablacar, a car-sharing service in France). It is clear, however that the European Commission (EC) is referring mainly to the for-profit model in its Agenda for the Collaborative Economy (EC 2016) and this is the one to which I refer in this paper. The literature, particularly when the collaborative economy first started to attract attention, referred to 'peer-to-peer' to signify individuals exploiting their under-used cars, bicycles, spare rooms, tools, time and know-how, to provide services to other individuals for a little extra money on an occasional basis. From this the term 'gigs' came to be adopted. This peer-to-peer model, however, has proved not to be the case with Uber and other labour platforms in the driving and delivering sectors. Many of its drivers in Europe are engaged in the so-called UberX model (superseding the earlier UberPop version) and are licenced professionals (sometimes with financial support from the platform for vehicle purchase or lease). A similar development is true of Airbnb, an accommodation-sharing service, where a large proportion of properties have been bought solely for renting out. 'Gigs', however, is more widely understood as referring to activities where labour is performed rather than the exploitation of A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 8 assets such as accommodation. 'Gigs or 'gig work' therefore best describes services performed by individual workers dependent upon platform intermediaries, sometimes several, to which they are connected by a smartphone or computer app, typically poorly paid (sometimes less than the national minimum wage), capable of being 'deactivated' at any time, without a collective voice, and lacking in either any of the work-related entitlements enjoyed by workers classified as 'employees' or full access to statutory state benefits when they need them. By contrast, surveys show that the flexibility to work when and where they want is liked by gig workers. Equally, however, many say have little other choice. Work in the gig economy can be online 'mind' services ranging from simple, repetitive tasks (as in Clickworker) to those requiring higher skill levels (as in Upwork) or offline physical services (such as ride-hailing or delivering). It is with the offline labour platform model with which this paper is concerned and how it fits into the interlocking circles of the overall 'collaborative economy' is shown in Figure1. Figure 1. The interlocking circles of Collaborative Economy. 'Gigs' are very often neither 'peer-to-peer' as has been said nor in the case of Uber occasional. According to the European Court (ECJ 2017:§47) 'it has become apparent that most trips are carried out by drivers for whom Uber is their only or main professional activity'. Although I am chiefly concerned with the physical rather than mind services, the social dimension of poorly paid, precarious work without entitlements or benefits can equally apply to both. A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 9 3. Literature and theory The gig economy is a recent development brought to popular attention under the title ‘collaborative consumption’ by Botsman and Roo (2010) followed by Rifkin (2014) whose theme was ‘the collaborative commons’. It has since become the object of wider scholarly research. Bardhi and Eckhardt (2012), for example, found that a car-sharing model (Zipcar) set up primarily for access rather than profit (costs of operation covered) with benefits for sustainability failed to gain brand recognition loyalty. Martin (2016) has drawn attention to the co-option of the ‘sharing’ ideal by ‘the market’, Rosenblat and Stark (2015, 2016) have studied how Uber exercises ‘continuous soft surveillance’ and ‘remote control’ (2015:6) over its drivers. Raval and Dourish (2016) drawing on the concept of ‘Body Work and Affective Labor’ (2016: 99, 101) have surveyed ways in which its drivers are obliged to ‘earn’ their ratings under a reputation system to which most of them object, including, having also to perform 'emotional labour' for example, tolerating rude behaviour and providing (at their own expense) small comforts for passengers or having them sit in the front passenger seat. A plethora of reports have emerged from the EU institutions, national governments and independent research centres. 3.1 Organisational aspects - bad for workers, good for consumers (and potentially investors) The rise of the gig economy can be situated within the context of the information society described by Nye (2014) and Nagirnaya (2014) while its salient organisational characteristics are identified as information asymmetry (Rosenblat and Stark 2015:2016), ruthless, flexible and evasive entrepreneurialism (Mejia 2016; Sennett 2006; Elert and Henrekson 2016). Traits such as disruptiveness and lack of corporate social responsibility are pre-figured in earlier texts by Christensen (1997), Christensen, Raynor and McDonald (2015) and Crouch (2006), while it remains unclear whether Schumpeter's (1934, 1939, 1942) theory of creative destruction is applicable as I have found no data which confirms that there has been a net increase in new jobs. In terms of wages, evidence is of the opposite. Consumers, however, may benefit from lower costs and greater convenience. 3.2 Management aspects - back to the 19th Century Management is about how workers are treated and the organisational model described above represents, I contend, a regression from the human resources (HR) school of management to earlier forms inspired by F.W Taylor and H. Fayol's theories of scientific management, if not to even earlier forms of the division of labour inherent in the first industrial revolution and the experience of the Tolpuddle Martyrs. Gone is the employee-centric orientation of the HR school A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 10 and the practices of Human Resource management foreshadowed by Durkheim, Mary Parker Follet and Chester Barnard and pioneered by Elton Mayo and the Hawthorne Studies. Uber, for example, shares the principle of scientific management with its algorithmic control and panoptic surveillance of every task undertaken by its workers. Its aim is the same - to achieve the greatest possible return for the minimum outlay using new developments in technology and in this respect and others it goes well beyond Taylor. In his theory maximum output by workers equated with highest wages and self-satisfaction, for which management was responsible for providing all the resources and skills training required. Labour platforms such as Uber or Deliveroo, a goods-delivery service, treat their workers as instrumental, merely a commodity, a factor of production to be acquired (and disposed of) at the lowest possible cost in terms of wages, entitlements and representation, exemplifying Marx's conception of 'the reserve army of unemployed labour' (Braverman 1974 [1998]:265-276) which is made available for low paid, unskilled service jobs first by mechanisation, then automation, and now (latterly) digitalisation. By contrast, the peer-to-peer nature of gig work has been portrayed by platforms as a democratisation of labour by eliminating the traditional hierarchies of both Taylorism and the HR school and fostering flexible work, wherever and whenever desired. Offline labour platforms, however, have substituted an often mythic peer-to-peer claim for bogus self-employment. Moreover, There is evidence (Boston Consulting Group in Uber, 2016; Reuters, 2017; Codagnone and Martens, 2016:18) that net rates of pay quoted by Uber and other platforms are dubious and very long hours (virtually limitless) are required to make a living or top-up another source of income. The data deficit, however, means that there are few empirical studies of the impact of this type of work, notably within the EU. A more truly peer-to-peer relationship could only be established by offline labour platforms operating as cooperatives but so far these have not made headway in Europe. A de-centralised system such as blockchain promises its complete fulfilment if it were to materialise. 4. Paradigms of political economy and cultural attitudes Opinion on the extent to which the gig economy should be regulated varies throughout the EU and within the EU institutions themselves. The broadest division which animates policy makers and is already evident in current regulation is between pro-laissez faire, pro-choice ('leaving it to the market') and pro-social justice ('pro-values'). There are also those who do not unreservedly accept the application of new digital technology seeing it as 'the tyranny of rational choice solutions, alienated from concrete social practices' (Strong and Sposito 1995: 268) or 'the discrepancy between the growth of technically exploitable knowledge, on the one hand, and the absence of any worthwhile form of social life, on the other' (Adorno and Horkheimer quoted in Finlayson 2005: 67). Are the technologies exploited by Uber leading towards a dystopia of contingent employees permanently on call and winner-takes-all monopolists, or economies of scale permitting cooperative enterprises? (Adler 2016). Habermas (2001:46) has warned us of A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 11 alienation resulting from the monetization of 'value orientations, binding norms and processes of understanding’, while we should not ignore Weber's 'iron cage' (Weber [1904/5], 1930: 123, 128) in which individuals are trapped by teleological efficiency, rational calculation and control - the bureaucratisation of social order, the 'disenchantment' of the world (Greisman and Ritzer 1981:35). Michael Sandel (2012) draws attention to the 'market society' in which we now live rather than simply the 'market economy', and in which non-market values are 'crowded out'. 4.1 A European dimension These cleavages manifests themselves in several ways. Firstly, they align closely with a Varieties of Capitalism typology, where Uber, for example, and its drivers, are free to operate in the liberal market economies of UK, Ireland, Poland, Estonia and Lithuania, subject to relatively light touch conditions. By contrast, in most of the other member states of the EU which follow, in various ways, the social market model, it is either banned or its drivers are subject to considerably more onerous licencing requirement. Secondly, they are reflected in the stance taken by lawmakers for example in the European Parliament (EP), where an analysis which I conducted of parliamentary questions on the subject between November 2014 and May 2017 revealed that Members of the EP were divided almost equally between those who called for further regulation at EU level and those who either did not or whose view was that it was expressly a matter for member states. Thirdly they are demonstrated in the communications of the European Commission which show that priority in policy making with regard to the gig economy has been placed more on the economic aspects - namely growth and competitiveness - than with social aspects. It is noteworthy that the Commission has consistently declined to bring forward any new legislation on the gig economy since publication of its set of non-binding guidelines contained in its Agenda for the collaborative economy (EC2016). The stance of the Commission is seen by some, principally by trade unionists and others on the Left, as consistent with its liberalising, deregulatory, pro-business tendency. By contrast, there is a push back by industry and market economists who hold it responsible for largely perverse effects on business of social measures such as the Working Time Directive (WTD) and others relating to agency, temporary and part time workers, the prevention of discrimination against minority groups and health and safety. None of these, however, materially affect the conditions of gig workers because they only apply to employees. The proclamation of the European Pillar of Social Rights (EPSR) can be seen as an acknowledgement that 'social Europe' has been somewhat neglected, particularly during the period of recovery from the great recession following the banking collapse of 2007 and 2008. President Junker has said as much with his call for a 'Social Triple A for Europe' (EC 2017a). Like the Agenda, referred to above, the EPSR's twenty principles are non-binding. Among them are explicit references to the elimination of precariousness, abusive contracts and in-work poverty and making statutory work-related entitlements, social welfare benefits and collective bargaining available to all A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 12 workers regardless of the type and duration of the employment relationship. The EPSR concretely addresses social policy, and in particular, labour aspects of the gig economy, in a way that the Agenda does not but it is still, essentially, an instrument of the EU's soft power. For the first time it treats decent wages and work-life balance as rights but the question is how these might gain a legal basis when labour law is, for the most part, a national competence and the Commission does not intend to bring forward new legislation except for a proposal for a new directive on contracts (Written Statement Directive) and clarification of the existing Working Time Directive, both of which were already 'in the pipeline'. This is where access to data on working conditions has a critical role to play in shaping public policy and how this might be approached is discussed in the second half of this paper. 5. The data deficit The lack of empirical data is widely acknowledged (Codagnone and Martens 2016; Huws, Spencer and Joyce 2016; OECD 2016; Taylor 2017; CIPD 2017; German Federal Ministry for Labour and Social Affairs 2017; EC 2018). It would be more accurate and constructive, however, to talk about a lack of access as never before has so much data been collected as it has by platforms (Codagnone, Biagi and Abadie 2016;60,61). A review I conducted of the relatively small number of independent surveys that have been carried out in Europe reveals a focus on overall numbers, motivations and demographics of both service providers and consumers using offline labour platforms but very little data on specific working conditions and employment status of the former. Further investigation is required into these, notably pay, leave, health and safety, working hours, tax, insurance, collective bargaining and quality of working life (Huws et al. 2016:51). More detail has come from surveys commissioned by, or facilitated in the United States and Europe by Uber, but they have not been independently corroborated. The most noteworthy of these are the analyses by Hall and Krueger (2015, 2016). These have attracted criticism in the press and among other researchers being described as 'mostly descriptive and inconclusive' and whose findings on earnings as 'an utter misrepresentation of the reality' (Codagnone and Martens 2016:17,18). The operative data that would make a difference in formulating public policy, however, is not from surveys, whatever their credibility. The data, in the era of Big Data are already there. They are collected by platforms twenty four hours a day, justified in some cased for security reasons. Uber, for example, collects licence, insurance and background checks (medical and criminal records) on each of it drivers as well as credit card details and mobile phone numbers for every rider. In effect it 'holds the key to the digital identities of its millions of contractors and customers' (Lashinsky (2017:140). The task is making it available to those who legitimately need it (and not, by oversight, to those who do not as has recently been reported), namely policy makers, regulators and tax authorities. This raises questions of commercial sensitivity and data privacy protection. Several approaches will be considered in the next section. A.J. Hawley / European Journal of Government and Economics 7(1), 5-23. 19 and 'social,' to which the EU aspires and which bears heavily on the integration project. References Adler, P.S. (2016) 'Alternative Economic Futures: A Research Agenda for Progressive Management Scholarship', Academy of Management Perspective, 30(2): 123-128. https://journals.aom.org/toc/amp/30/2 Balaram, B., Warden, J.R. and Wallace-Stephens, F. 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