Platform work and AI in the Global South Flashcards
(41 cards)
Market despotism
Burawoy (1983)
Temporal flexibility trend in all employment, enabling firm flexibility without necessitating firm reliance on contingent workers
Unions are ineffective at compensating for a lack of institutional and structural power
Wood (2016)
Zero-hour contracts favour employers, and very rarely favour employees
Other than those who do not require a fixed number of working hours, which is a minority
Pennycook et al (2013)
Automation will not inevitably replace human labour - it will change how we work, and what work we do
Technology is not neutral and needs to be regulated to ensure that exploitation does not occur
A key development is the digitisation not of management but of decisions concerning workers, leading to arbitrary implementation undermining workers rights
Aloisi & de Stefano (2022) Your Boss is an Algorithm
The governance of crowdsourcing.
Looks at how new practices of work are normalised (rationalities)
Scale of crowdsourcing is difficult to ascertain because it is relatively new and growing repidly
Decentralisation of labour, wageless work and precarisation
Self-governance of crowds is an old and efficient form of governmentality
The institutionalisation of informal work on a global scale
Ettlinger (2016)
CPE approach, looking at the materialities and discourses of gig work development in Japan
The move to gig work further legitimises the flexibilisation of labour markets
Abe government has leveraged specific Japanese discourses - such as overworking - to promote the benefits of gig work - such as flexibility - in response to structural pressures that demand new opportunities for economic growth
Shibata (2020) Discourse of autonomy
Problematises the idea that gig workers have flexibility. Study of Uber’s algorithmic management which finds that the app uses ‘soft control’ to encourage self-responsibilisation so that the decisions made align with firm’s
Workers don’t really get to choose where/when they work
Rosenblat & Stark, 2016
Platform work is starting to become more and more like full-time jobs in China, with a full schedule but none of the traditional job security.
Proposes concept of ‘sticky labour’ to understand management as static.
Identifies the tension between flexibility as a motivation for workers to stay, and flexibility as a mode of regulation benefiting employers
Sun et al (2019)
Flexible work is not generalisable. Flexibility is relational, relative, culture-and-context dependent’
Sun et al (2022)
Across six countries and varied platforms, finds that algorithmic control is central to the operation of online labour platforms.
Most effective form of control was the rating system.
Flexibility myth - workers could not convert purported flexibility into reality, which translated to long working hours and working in isolation
Job quality was determined by individual marketing bargaining power, which prevents worker solidarity by engendering competition. Skills and platform reputation were found to be the most important indicators
Wood et al (2019) Good gig, bad gig
Platforms are not middle men but exploit regulatory loopholes and reproduce workforce precarity
Various forms of nudging (so similar to Rosenblat & Stark, 2016) align worker decisions with company interests
However, workers become familiar with company policies (‘qualculacion’). They tolerate these as long as they align with their own interests - high rates of worker turnover
Shapiro (2018) Between autonomy and flexibility
Fragile art of multi-apping. This is not a collective form of resistance but an individual coping mechanism which further reifies the platform’s power
Other forms of everyday resilience include using shortcuts, postponing orders and upgrading vehicles
Differentiates between resistance, resilience and re-working, and posits the snapping/resilience cycle
Companies still use the same management strategies e.g. a piece-rate pay system (Burawoy, 1983) but new ones as well such as info asymmetry
Demonstrates an exploitative work arrangements which leads to ever-more intensive work regimes
Popan (2024)
Finds that the power of worker agency is constrained by work organisation
Agency is predominantly entrepreneurial - low-level expressions aimed at materially improving individual conditions
In some cases this reinforces capital accumulation - e.g. multi-apping allows platforms to claim workers are independent contractors
Barratt et al (2020) Australian case study of Uber Eats & Deliveroo
Multi-apping is argued to be a form of resistance with subversive potential.
Actually, I think this is a tenuous claim since this only temporarily prevents control of the platform and it actually benefits from it anyway. To be sure, this is an agency that should be acknowledged but I don’t think this is incompatible with also seeing that this agency occurs within fundamentally oppressive wider structures
Tironi & Albornoz, 2022
Studies platform work in Jakarta to propose the driver’s view from within, which is more relational and experiential than the abstract vision of the algorithm
This manifests materially in unpaid labour on the part of drivers, who expend energy on figuring out unanticipated hurdles, shortcuts, shelter, police etc
Worker subversions to make money (e.g. automatically accepting any order) can align with platform goal of maximising income
Spatiotemporal rhythms of the city
Qadri & D’Ignazio (2022)
Women in the gig economy - this gendered dynamic is often unexplored but plays a role in shaping the operation, outcomes and experiences of digital labour platforms.
For example the constraints of motherhood and care (Which are far from novel for feminist scholars) constrain the freedom of remote female workers, despite rhetoric that remote work breaks down gender barriers - e.g. needing to watch the children means you cannot accept more lucrative jobs with tight turnarounds; losing clients while pregnant and having to build up a base again
Digital labour platforms further reinscribe pre-existing gendered labour market inequalities in new ways
James (2022)
Going ‘Karura’ in Kenya - an analysis of Uber drivers, who went on strike in July 2018.
‘Karura’ refers to the forests, which are associated with political resistance against British colonialism and later state development policies. This conjured up the continuity of colonial, political and corporate dynamics of exploitation and demonstrates the politicised nature of the supposedly unbiased digital economy
This forefronts a tension between the ‘subjectification’ from above (where Uber construes workers as independent contractors) and labour subjectivities created from below (how workers actually understand their identity) - the former is closely linked with collective agency, embedded in the Kenyan context
Iazzolino (2023)
An overview of unpaid labour in cloud-work, defined as remotely performed labour mediated by digital labour platforms
Technically geographically untethered labour has geographically contingent outcomes with cloud-work often functioning as an engine of South-North value extraction
Southern workers do more unpaid labour on average than their Northern counterparts
So unpaid labour is a systematic mechanism of how platforms make money + shift risk onto workers + dodge traditional responsibilities in three ways: unpaid wages for done work; unpaid time searching for jobs; unpaid aspirational labour (upskilling)
99 Designs: design tasks are posted as contests and workers must create briefs that may not even be used
Howson et al (2022)
Case study of socio-spatial networks as coping mechanism for lack of state/platform support in migrant drivers, India
Platforms promise better incomes but expose workers to the same precarity as the informal economy
Important to remember that this was the standard beforehand
New ‘digitally organised informality’
Ray (2024)
Platformisation - the introduction of internet apps that consolidate dispersed small-scale producers under the idea of entrepreneurial self-employment
‘The penetration of infrastructures, economic processes and governmental frameworks of digital platforms in spheres of life, and the reorganisation of cultural practices around these platforms’
Driven primarily by US-based companies
Platforms are defined by their digital nature, their mediation between end-users and complementors, and their systematic collection of data and algorithmic processing
Poell et al (2019)
New regime of ‘organised informality’
In the GS, platform apps are a further extension of pre-existing neoliberal forms of economic and labour governance in the GS
Embedded in historical dynamics of social hierarchies - reproducing inequalities of caste, class race and gender in the contemporary labour market
Facilitated by the systematic recruitment of the most deprived to serve in the low-end service economy - although training is formalised (often with state co-operation), terms of employment remain precarious
‘The emotional proletariat’ refers to how employers control not only the physical labour but also the emotions of their workers to develop the right skills and attitude - the affective expression and corporeal embodiment of servility
Gooptu (2013)
March 2024 launch of Platforms and Society journal - showing how recent and ongoing this work on platforms is.
Platform studies are interdisciplinary
Most work is in Global North - so lots of work to be done on the unequal material and spatial repercussions of platformisation, especially re gendered, racialised and (post)colonial trajectories
AI is rapidly turning into another platform industry
Chen et al (2024)
Integrating the digital into global production value networks
GPN is a key framework that has been used to understand the relations between economic production and its actors - but how can it be used to understand growing role of the digital
The digital is not just an infrastructure to be added, but is itself central to the management, make-up and monitoring of global dispersed networks
Foster & Graham (2017)
The micro-work that goes into supporting AI is divided into three parts: AI prep, AI verification and AI impersonation.
There is a gap in the literature on the place of this labour in AI, and the nature of its embeddedness in data companies.
The paper finds that, rather than human labour being an initial form of support that will no longer be needed once technology ‘matures’, it is rather a structural component of production processes because data availability will never reach a steady state - verification will always have to be performed.
This will lead to further marginalisation and precariousness (heteromation) of human workforces - AI sells a techno-utopian vision but is in fact a labour-intensive, poorly paid and low security sector.
Tubaro et al (2019)
