Challenging exploitation in the gig economy
Over half of the world’s population is now connected to the Internet. Most of these new internet users are from low- and middle-income countries, and many come online looking for jobs.
The rise of gig economy platforms have proved crucial in enabling workers from poor countries to connect with, and earn income from, clients in rich countries. In doing so they have created a potential new army of labour, which could potentially give rise to a planetary-scale labour market.
When we think of the gig economy we usually think of people driving for Uber or dropping off food Deliveroo. But a large component of the gig economy is actually made up of similar platforms but which enable the remote provision of digital services. According to one estimate, there is a $5 billion market for online work that is served by 48 million workers – often located in the global south. But unlike gig economy services which are provided locally (such as Uber and Deliveroo), remote gig work can potentially be carried out by workers anywhere in the world. This remote gig work consists of digital labour, such as transcribing interviews, creating ads, designing logos and programming software.
In our new paper, we investigate the experiences of African and Asian gig workers, who mainly work for clients in the US, Europe and Australia. Despite the varying country contexts and types of work, we find that algorithmic rating-based control is central to the operation of remote gig platforms. Workers with the best scores and the most experience tend to receive more work due to the platforms’ algorithmic ranking of workers within search results. Unsurprisingly, workers stress the importance of maintaining a high rating, as the consequence of a bad ratings is that the platform’s algorithms filter work away from them, thus making continuing on the platform a less viable means of making a living.
These algorithmic management techniques tend to offer workers high levels of flexibility and autonomy compared to the conventional supervision and management of workers. And workers benefit from this autonomy by choosing tasks which offer them variety and complexity. However, these algorithmic mechanisms have a dark side.
In enabling control of a global labour force from anywhere in the world, algorithmic control means that workers face fierce competition which creates a downward pressure on pay. In order to increase their earnings, in this highly competitive environment, workers are often forced to work long hours. Simon*, a Kenyan, carrying out data entry for a client in Canada, explained:
‘A client [is] paying me $3.50 an hour. I’m so broke, this is someone who’s ready to give me the money, so why don’t you want 18 hours in one day.’
Workers also tried to increase their earnings by intensely completing as many tasks as possible and working for numerous clients – all of whom place their own demands on workers. Working for multiple clients also reduces the insecurity of being dependent on a single client who is empowered by the platforms to ‘fire them on the spot.’ As Kevin a transcriptionist from Kenya explained:
‘It’s so insecure… unless you have ten clients; then you can breathe. But then with ten clients it means each client has an expectation of a certain workload for you to do… So you can say, “I’ll get ten clients for security,” but then can you satisfy all those ten clients? You can have three clients, but then when they disappear that’s it.’
Knowing that clients can easily give them a bad rating, which will impact their future ability to make a living from this digital work, workers have to be ready to respond at any time to any demand made by a client. And ensure they meet their clients’ deadlines. These demands could be at any hour of the day or night. This invariably means often working through the night and at other anti-social times. Working these intense, unsocial and irregular hours of work can lead to sleep deprivation and exhaustion. Moses, a Nigerian, working as a virtual assistant for a US client, explained that this was the biggest problem with such work:
‘I find that I’m exhausted… you might find yourself working throughout the night… the biggest challenge when you are working online [is] you can find that you are working for so many hours without rest.’
However, as we show in another recent paper, these workers in the Global South are not just passive victims. Workers are actually coming together, through Facebook groups, WhatsApp groups, and forums, to create self-organized digital communities. This self-organization is despite workers not seeing themselves as traditional employees or workers. Instead, they strongly identify with being ‘freelancers’ and have entrepreneurial aspirations. And as such, these Asian and African workers have little interest in joining a traditional trade union.
These self-organized digital communities are, nevertheless, enabling workers to support and help each other. Freelancers are also trying to use this organization to collectively improve their working conditions. For example, workers warn each other of bad clients, recommend good clients and attempt to influence pay through creating informal norms regarding what to charge clients.
While these workers were relatively uninterested in unions, there were not against collaboratively raising their wages. Seventy one percent of the workers we surveyed expressed interest in doing so against just nine per cent who didn’t.
The greatest influence on both whether the workers in our research had joined a digital work community or not and their willingness to collectively improve their working conditions, is how important the work is for their livelihood, and whether it’s their main occupation or not. This suggests that as the gig economy grows in importance so too will worker self-organization.
If we look to gig workers’ unique lived experiences and identities, there are thus possibilities for forms of trade unionism that build on workers’ willingness to collectively organize and improve working conditions. Therefore, despite fears that workers will be relatively powerless in the growing gig economy, workers need not necessarily be atomized and without collective power. Karl Marx famously argued that as the industrial capitalism of 19th century advanced, worker isolation would be replaced with combination through the formation of worker associations. Our findings suggest this insight remains true for 21st century platform capitalism. The potential for workers to fight for better labour standards remains undimmed.
* All names have been replaced with pseudonyms.
Alex J Wood and Mark Graham have published their paper 'Good Gig, Bad Big: Autonomy and Algorithmic Control in the Global Gig Economy' co-authored with Vili Lehdonvirta, and Isis Hjorth, in the journal Work, Employment and Society. Alex J. Wood is a sociologist of work and employment at the Oxford Internet Institute, University of Oxford. See more of his work at oii.ox.ac.uk/people/alex-j-wood or follow him @tom_swing. Mark Graham is the Professor of Internet Geography at the Oxford Internet Institute, University of Oxford. See more of his work at markgraham.space or follow him @geoplace.
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