Phones but no Papers

This originally appeared in Points, in a series of other great pieces responding to a Pew Research report on Gig Work, Online Selling, and Home Sharing.

Phones, but No Papers

New Vulnerabilities in On-demand Work

Emerging forms of on-demand low-wage work done through online labor platforms like Uber, Postmates, and Amazon Mechanical Turk have raised questions about new kinds of risks faced by low-wage workers in the US. However, while we focus on these emerging forms of contingent work and what they bode for the future, for many workers the characteristics of the gig economy — flexibility, precarity, instability — have been central to their experiences of work for generations. Contingent work has always been prevalent in communities where workers have been historically excluded from secure jobs, from union membership, and even from wider public forms of social welfare through systemic forms of discrimination. For these workers, there was no “golden era” of plentiful stable work and a strong social safety net.

Despite these long-standing trends, emerging forms of on-demand labor, and the data-driven technologies that workers interact with, can deepen the vulnerabilities of certain populations of workers.

What kinds of risks, for example, is an undocumented immigrant taking by giving up their data to a gig economy platform in exchange for work opportunities? What avenues for visibility into these populations are potentially being opened up for companies, government, or law enforcement?

Image by Alexandra Mateescu

Image by Alexandra Mateescu

A new Pew Report that examines workers in the “gig” or “on-demand” economy has found that Hispanic workers are overrepresented by 6 percentage points within the population of workers who earn income through online gig labor platforms like Uber. While this report doesn’t disaggregate this population based on their immigration status, given that this population tends to share other demographic similarities with other segments of on-demand laborers that are also overrepresented in other groups — for example, those without high school educations, and who make less than $30,000 a year — undocumented workers could potentially be overrepresented within the on-demand workforce. If this is indeed the case, it shouldn’t be too surprising. While undocumented immigrants only make up 5% of the total US workforce, foreign-born workers are overall more likely than native-born workers to be working in service occupations across the economy.

Given the number of undocumented workers that could be doing this work, this may seem to be a small issue. However, focusing on the vulnerabilities of this small population of on-demand workers isn’t only important to understand in order to get a better idea of who’s doing this work. It also has serious implications for the ways the companies they work for gather data about them. The ways that companies across the on-demand labor economy collect, use, and even share the data generated about these workers has the potential to exacerbate vulnerabilities of undocumented workers. Outside of the context of work, these issues are usually thought of under the rubric of privacy. For example, when Google uses your browsing data to show you creepily accurate advertisements or show women fewer ads for high paying jobs than they show men — we start to worry about the rules that govern how Google can share the data generated by our normal daily activities. The same is true for workers — except unlike you and your internet browser, workers don’t have a choice to simply use a different search engine, or mess around with their privacy settings to protect themselves. In order to find and coordinate the work that’s increasingly central to their livelihood (56% of gig economy workers say the money they make is “essential” or “important” to their overall finances), they must use platforms that they can’t tinker with to control the ways their data are collected and shared.

But, what are the stakes of companies having data like this about their workers? One way we can anticipate some of the consequences of this for undocumented workers is to look for other instances within the on-demand economy where rules about sharing data have come under pressure. As current disputes between Airbnb and the cities of San Francisco and NYC illustrate, the rules about how companies share data about the people who use their platforms are subject to change based on the political climate. Airbnb hosts in these cities have relied upon a certain level of invisibility and slack in the overlapping systems between their landlords, local housing regulations and law enforcement, and Airbnb’s data about them in order to rent their extra rooms and avoid fines. However, in the face of legislation in NYC that would impose steep fines on Airbnb hosts, the company has shown a willingness to share their data about hosts with the government to make enforcement more efficient, and to close the gaps in information between these powerful institutions.

Undocumented workers could face a similar (albeit more life-altering) set of risks when they engage in work through on-demand labor platforms. If the information these companies gather on their workers — from personal information, like photos of their faces, to information generated in the process of their work, ranging from GPS–tracking data to payroll information –is collected and shared, it could make them visible to institutions that pose huge risks to their safety and livelihoods.

These emerging forms of work, with their data-intensive forms of tracking and surveillance, raise new questions for workers who’ve traditionally relied on a level of obscurity and invisibility in order to navigate the daily insecurities they face as undocumented residents and workers. In our current political climate, with rising anxieties surrounding the future of immigration enforcement in the U.S., the data that these companies have may be of increasing interest to powerful government institutions, and they may soon face difficult choices about their obligations to their workers.