Gig Industry and the Issue of Data

The increased use of Big Data in various industries has been embraced by solutionists as “a powerful tool to address various societal ills” (boyd and Crawford 2012, 664). At the same time, many are sceptical about the proliferation of Big Data as they see it as a “manifestation of Big Brother, enabling invasions of privacy, decreased civil freedoms, and increased state and corporate control” (boyd and Crawford 2012, 664). Among those sceptics, are boyd and Crawford, who in 2012 published the article “CRITICAL QUESTIONS FOR BIG DATA”. With this article, they aimed to spark conversations regarding Big Data. With these questions, their focus lied mainly on Big Data in the context of social media. Therefore, as a contribution to this conversation, I turn a critical lens to another sector heavily driven by data, namely the gig economy.

Over the past years, we have witnessed an increase in the number of online platforms offering services from transportation to manual labour (Prassl 2018). Today, for instance, ride-sharing platform Uber offers its services in more than 10.000 cities (Uber 2021). These platforms fall under the gig economy, which Prassl (2018) describes as “evoking the artist’s life in which each concert, or ‘gig’, is but a one-off task or transaction, without further commitments on either side (4).” In the digital gig economy, these gigs are mediated through digital platforms, which not only put workers and consumers in contact with each other but also manage these workers through algorithmic interventions.

This emerging digital gig economy has raised the attention of many scholars. Graham, Hjorth and Lehdonvirta (2017), for instance, highlighted the “risks and costs that unduly affect the livelihoods of digital workers.” Others have studied “the challenge of regulating platform capitalism” (Edward 2020). Seen as the digital gig economy is a heavily data-driven industry, with this article, I add to this work by following boyd and Crawford’s (2012) footsteps and asking “critical questions about what all this data means, who gets access to what data, how data analysis is deployed, and to what ends” (664).

Surveillance

In the digital gig economy, workers are “increasingly managed via online platforms”, subjecting them to “continuous surveillance and monitoring” (Huws 2016). These surveillance practices are justified by the platforms, with the assumption that “workers need to be controlled and disciplined” (Chen and Qui 2019, 11).

Within the digital gig economy, surveillance is practised through extensive data extraction. The ride-hailing platform DiDi, for instance, collects an extensive list of information about its drivers every three seconds. This heavy data extraction raises questions about the privacy of the workers. Is this an ethical form of labour management? And who is regulating the surveillance practices performed by these platforms? The reason DiDi, for instance, is able to perform such invasive surveillance, is because China’s “lax data protection laws” allow for this (Chen and Qui 2019, 11).

In their article, boyd and Crawford (2012), noted how researchers should “reflect on the importance of accountability”. Though they were referring to the extraction of data from social media users, the same can be said about the extraction of data within the gig economy. With the rapid growth of these platforms, there should be more laws and regulations holding those behind the platforms accountable for the way data is extracted from its workers. This is especially important in an industry that is “predicated on an architecture that is primarily staked in, and driven by, economic values and corporate interests,” which often endangers “public values” (Van Dijck, Poell and de Waal 2018, 139).

Dual value production

As stated by Chen and Qui (2019), “the source of power for digital platforms – datafication – depends not only on algorithms, technology, and non-human natural resources but also, more crucially and intensively, on humans themselves (5).”

In the digital gig economy, the workers produce value, not only with the service they offer but also with the data they produce as they offer this service. This process is termed by Van Doorn and Badger (2020) as “dual value production” (1476). The data produced in this process is highly valuable for these platforms, as it is strategically utilized to gain infrastructural power. Airbnb, for instance, leverages data obtained through its platform – such as data that can inform policy decisions – to negotiate with local governments, granting them “increasing control over particular “functional arenas” (Van Doorn 2019, 3). 

This is not exclusive to the gig economy. As addressed by Venturini et al. (2018): “Media companies collect information from us and redistribute it in various configurations and products as part of their business strategy” (4197). Without them necessarily being aware of it, the information users post on various social media channels, is used by the platforms for profit and various other gains (boyd & Crawford 2012, 673). Despite the crucial role they play in the production of this data, users of these platforms, as well as those working in the gig economy are not remunerated for the extra value they produce (Van Doorn and Badger 2021, 124). On the contrary – in the case of the gig economy – data produced by workers is for example used to dynamically adjust prices, decreasing worker fees “based on aggregated market data in order to increase profit margins” (Van Doorn and Badger 2021, 128). So instead of benefitting from the data they produce for the companies, workers are only left in more precarious conditions. 

Conclusion

The mining of data within the digital environment raises critical questions regarding the ethics of these practices. As we have seen these questions stretch beyond the context of social media, as today Big Data is utilized in various sectors. Back in 2012, boyd and Crawford already raised valid concerns which are still relevant today. When looking at the digital gig industry through the framework of boyd and Crawford’s (2012) article, the theme which stands out the most is that of privacy, more specifically how the privacy of those subject to data extraction is utilized and protected. As pointed out by boyd and Crawford (2012), accountability is key. Whether it be from scholars using social media data for research, or platforms within the digital gig industry, when dealing with personal data, one should always tread with care. Ensuring that this is done, effective data protection laws are of great necessity. This has already become clear, as Europe’s General Data Protection Regulation has, for instance, helped gig workers to fight back against platforms such as Uber and Lyft (Clarke 2021). This gives hope for a future where the privacy of gig workers is treated with respect.

References

boyd, danah, and Kate Crawford. 2012. ‘Critical Questions for Big Data’. Information, Communication & Society 15 (5): 662–79. https://doi.org/10.1080/1369118X.2012.678878.

Chen, Julie Yujie, and Jack Linchuan Qiu. 2019. ‘Digital Utility: Datafication, Regulation, Labor, and DiDi’s Platformization of Urban Transport in China’. Chinese Journal of Communication 12 (3): 274–89. https://doi.org/10.1080/17544750.2019.1614964.

Clarke, Laurie. 2021. ‘Data Is the next Frontier in the Fight for Gig Workers’ Rights’. Tech Monitor (blog). 22 March 2021. https://techmonitor.ai/policy/education-and-employment/data-next-frontier-fight-for-gig-workers-rights.

Edward, Webster. 2020. ‘The Uberisation of Work: The Challenge of Regulating Platform Capitalism. A Commentary’. International Review of Applied Economics 34 (4): 512–21. https://doi.org/10.1080/02692171.2020.1773647.

Graham, Mark, Isis Hjorth, and Vili Lehdonvirta. 2017. ‘Digital Labour and Development: Impacts of Global Digital Labour Platforms and the Gig Economy on Worker Livelihoods’. Transfer: European Review of Labour and Research 23 (2): 135–62. https://doi.org/10.1177/1024258916687250.

Prassl, Jeremias. 2018. Humans as a Service: The Promise and Perils of Work in the Gig Economy. Oxford University Press.

Uber. 2021. ‘Zoek een stad | Begin hier je reis te plannen | Uber’. n.d. Accessed 2 October 2021. https://www.uber.com/global/nl/cities/.

Van Dijck, J., Poell, T., & de Waal, M. (2018). The platform society. New York: Oxford University Press.

Van Doorn, Niels, and Adam Badger. 2020. ‘Platform Capitalism’s Hidden Abode: Producing Data Assets in the Gig Economy’. Antipode 52 (5): 1475–95. https://doi.org/10.1111/anti.12641.

Van Doorn, Niels, and Adam Badger. 2021. ‘Dual Value Production as Key to the Gig Economy Puzzle’. Platform Economy Puzzles, August. https://www.elgaronline.com/view/edcoll/9781839100277/9781839100277.00015.xml.