Shuang Frost

The rise in economic inequality associated with technological displacement is one of the defining issues of our time. Last year the White House reported that recent advances in AI will result in the obsolescence of millions of low and medium-skill jobs and the depression of wages for ordinary workers. This prediction echoes an emerging consensus in social scientific literature: that the trend of widening inequality will only accelerate as more firms move to achieve cost advantages by replacing labor with capital. To glimpse a future of dire technological inequality, one need look no further than the San Francisco Bay Area, one of the wealthiest regions of America with the highest rates of eviction and homelessness. As Russel Hancock, president of Joint Venture Silicon Valley, recently explained in an interview with MIT Technology Review, “When we used to have booms in the tech sector, it would lift all boats. That not how it works anymore.”

So what is driving this hollowing out of jobs at the bottom and middle of society? Is it simply the case that increasingly intelligent and efficient machines are outmoding their human counterparts in all but a narrow set of economic activities? Certainly this is not the whole story. The tech industry’s reshaping of society has been driven not only by technological factors, but also deeply social ones. In the past two decades, tech firms have engaged in a dialectical process of emphasizing the superiority of technologies and simultaneously devaluing human labor.

As machine capability expands into new realms of human activity, it inevitably replaces some of the human skills and knowledge needed to get jobs done. This in turn is thought to cause a deskilling of workers (think for example of the secretarial profession after the advent of the personal computer). But there is also a concurrent process of enskillment which takes place. Social scientists have shown that with the advent of any new technology, workers must acquire new skills and apply their embodied knowledge in order to make the technology useful. As Cristina Graseni argued in her book, Skilled Vision, “there is no fixed algebra of skill and machine by which an increase of technology means a decrease of skill.” This is because human workers are not just the users of technologies, but also their active re-inventors.

Take for example the transportation industry. In the past five years, the spread of ride-sharing platforms has led to a fundamental reconfiguration of urban transportation and a supposed deskilling of the transportation industry. The remarkable growth of these technologies and the rise of the world’s most valuable start-ups— Uber ($68billion) and Didi ($50 billion) — has been predicated on a business model of substituting professionalized, monopolistic service providers (i.e. traditional taxi companies) with decentralized low-cost labor. Reports show that in some American cities, the hourly income of Uber drivers after expenses falls below minimum wage. In China where fares are much lower still, many drivers claim that they can barely cover costs.

This radical reduction in wages has justified by claims that transportation is a deskilled profession and that service providers are merely acting as extensions of technologies (such as GPS navigation and customer-driver pairing algorithms). However, I found in my research of ride-sharing industry in China that such characterizations are misleading. Firstly, ride-sharing services depend upon the knowledge, skills, and social relations of drivers. After joining the platform, drivers learn which smartphones work best with the app and which telecommunication networks offer the most reliable service in the areas that they operate. They develop strategies for making customers happy and boosting their user ratings. The drivers form online communities to share tacit knowledge about things like earning subsidies and promotions and avoiding getting caught by the police in places where the app is still illicit. Though these processes of enskillment, knowledge-making, and socialization often go unacknowledged by ride-sharing firms, they constitute an indispensable human infrastructure that enables the smooth functioning of technological platforms.

Secondly, on ride-sharing platforms a significant percentage of drivers are full-time professionals. Both in America and in China, Uber rolled out subsidy structures that encourage individuals to make driving for Uber their full-time jobs. Drivers are rewarded with “bonus” fares if they stay on call for a certain number of hours per day or complete a specified number of trips within a given week. As a result, many Uber drivers work roughly the same hours as their traditional taxi-driving counterparts. In China, many drivers claim that they rely on bonuses to make ends meet. One man joked that being a part-time driver is like being Lei Feng: you do it only out of a selfless commitment to society. Nevertheless, Uber has consistently refused to categorize drivers as employees. By instead categorizing them as “independent contractors,” the company avoids paying employee benefits, thus keeping the cost of labor artificially low.

Social tensions caused by technological displacement show no signs of abating. According to a recent study, in the next 10 to 20 years, 57 percent of jobs in OECD countries and 77 percent of jobs in China are at risk of being displaced by automating technologies. The transportation industry will be one of the sectors most affected. Autonomous driving cars and semi-trucks alone could displace the 12-15 percent of the world’s workforce.

This newest wave of displacement is not necessarily a bad thing. Like technological innovations of the past, advances in AI have the potential to free us humans from certain repetitive tasks and enable us to focus on more creative work. However, it is important to consider how the benefits of technologies are distributed and to recognize the value of the knowledge and skills that ordinary workers bring to this socio-technological transition.

Shuang Frost is a Ph.D. candidate of anthropology at Harvard University, with a secondary field in Science, Technology, and Society. Her dissertation looks at the economic, political, and social impacts of the ride-sharing industry in contemporary urban China. Her broader research interests include digital technology, moral economy, and corporate governance.