Counting ‘micro-workers’: societal and methodological challenges around new forms of labour

Tubaro, Paola; Ludec, Clément Le; Casilli, Antonio A.

doi:10.13169/workorgalaboglob.14.1.0067

Cited by 20 publications

(10 citation statements)

References 11 publications

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“…Notions of statistical representativeness are difficult to apply to platform settings where the characteristics and boundaries of the user populations are unknown (Tubaro et al, 2020b;Kässi et al, 2021). However, demographic data are broadly in line with what has been reported elsewhere.…”

Section: Methodssupporting

confidence: 60%

Learners in the loop: hidden human skills in machine intelligence

Tubaro¹

2022

Sociologia Del Lavoro

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Today's artificial intelligence, largely based on data-intensive machine learning algorithms, relies heavily on the digital labour of invisibilized and precarized humans-in-the-loop who perform multiple functions of data preparation, verification of results, and even impersonation when algorithms fail. Using original quantitative and qualitative data, the present article shows that these workers are highly educated, engage significant (sometimes advanced) skills in their activity, and earnestly learn alongside machines. However, the loop is one in which human workers are at a disadvantage as they experience systematic misrecognition of the value of their competencies and of their contributions to technology, the economy, and ultimately society. This situation hinders negotiations with companies, shifts power away from workers, and challenges the traditional balancing role of the salary institution.

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Section: Methodssupporting

confidence: 60%

Learners in the loop: hidden human skills in machine intelligence

Tubaro¹

2022

Sociologia Del Lavoro

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“…Workers are familiarly called 'fouleurs' (' crowders') and can register freely on the platform subject to availability (there is now a waiting list). The platform sports 50,000 workers, but we estimate the number of active monthly users to revolve around 7,000 (Tubaro et al, 2020b).…”

Section: Methodsmentioning

confidence: 99%

Hidden inequalities: the gendered labour of women on micro-tasking platforms

Tubaro

Coville

Ludec

et al. 2022

Internet Policy Review

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Around the world, myriad workers perform micro-tasks on online platforms to train and calibrate artificial intelligence solutions. Despite its apparent openness to anyone with basic skills, this form of crowd-work fails to fill gender gaps, and may even exacerbate them. We demonstrate this result in three steps. First, inequalities in both the professional and domestic spheres turn micro-tasking into a 'third shift' that adds to already heavy schedules. Second, the human and social capital of male and female workers differ-leaving women with fewer career prospects within a tech-driven workforce. Third, female micro-work reproduces relegation of women to lower-level computing work observed in the history of science and technology. Issue 1This paper is part of The gender of the platform economy, a special issue of Internet Policy Review guest-edited by Mayo Fuster Morell, Ricard Espelt and David Megias. Introduction: The gendered dimension of work on micro-tasking platformsMicro-tasking platforms are digital infrastructures that fragment large data projects into small bits, and allocate them to masses of anonymous providers, each of them executing remotely a tiny part of the whole and receiving a small compensation for it. Examples of micro-tasks include labelling images, categorising messages, recording short sentences, and transcribing audio snippets. Generally simple and short, they nonetheless serve to meet the data needs of today's fast-growing artificial intelligence industry (Casilli, 2019;Tubaro & Casilli, 2019;Tubaro et al., 2020a).At first glance, these platforms appear ' gender neutral' and largely inclusive.Clients companies target unidentified and uncredited masses, and are typically given very limited access to individual workers' profiles (if at all). Under these conditions, employment discrimination is unlikely to occur -and indeed the nascent literature on digital platforms has mostly taken it as non-existent. Recently,

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“…Additionally, labour market statistics and measures may not capture workers that are using platform work as a secondary income. Establishing this information from company data may also be misleading as work may fall below tax reporting purposes, accounts may be used by more than one person, and there is variability in whether and how companies report this pay data (Tubaro et al, 2020).…”

Section: Employment Trends In the Digital Labour Marketmentioning

confidence: 99%

Measuring the size, characteristics and consequences of digital work

O’Reilly¹,

Verdin²

2022

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This working paper provides a summary assessment of the existing literature and data on digital forms of employment internationally. It illustrates the variability in how it is defined, how it is growing and what kind of risks are associated with these developments. Evaluation of these types of jobs is divided. On one hand, optimists point to the attractions and relative ease in finding employment on digital platforms; on the other hand, more critical perspectives argue that these employment contracts can result in exclusion from social protection systems. The evidence indicates that while overall a relatively small proportion of all employment digital work is growing, both on platforms as well as adoption amongst more traditional companies. The characteristics of digital workers can vary by region and occupation. Overall, they tend to be predominantly younger and more likely male, with a growing number of women albeit in particular occupations. Skills and earnings levels vary but the key issues of disputes is around pay, conditions and employment status. The consequences of this form of work for those with lower skilled digital employment can undermine their social citizenship: they lack comparable employment rights, or when unemployed entitlement to adequate social protection. The potential polarisation effects of digital exclusion and deficits will severely hamper the wider benefits of transparency offered by these technologies. During the pandemic these trends have become more apparent. The imbalance of bargaining power and regulatory governance to bridge gaps in citizenship entitlements undermines the collective potential of policy makers and trade unions to address these challenges. Nevertheless, there is emerging evidence of innovative challenges and contestation of these gaps by both union organisations and national regulators attempts to adapt social protection

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Counting ‘micro-workers’: societal and methodological challenges around new forms of labour

Cited by 20 publications

References 11 publications

Learners in the loop: hidden human skills in machine intelligence

Learners in the loop: hidden human skills in machine intelligence

Hidden inequalities: the gendered labour of women on micro-tasking platforms

Measuring the size, characteristics and consequences of digital work

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