Disrupting D.C. is about Uber’s rise to market dominance, but it’s equally about the material conditions that enabled Uber’s success. What were those conditions?

Some of the conditions are more proximate and can be traced to the last fifteen years of capitalism’s development. Uber’s growth — and the rise of platform-based gig work more generally — can be traced to the specific political-economic conditions that emerged following the Great Recession. Those conditions were favorable for raising the necessary venture capital that underpinned Uber’s growth, as postrecession investors were incentivized to look for Silicon Valley start-ups and “unicorns” in the face of limited investment options.

The Great Recession was also key to producing a workforce among the recently laid-off and those made precarious by the global downturn. Contextualizing Uber’s growth within these processes is key to contesting the idea that tech companies’ urban dominance is simply the result of innovation or progress.

The conditions that gave rise to Uber’s dominance can also be traced to a set of longer-standing trends in cities. Since at least the early 1980s, US cities have faced financial limits brought on by deindustrialization and dwindling tax bases. A key response to these limits has been disinvestment in public services and a broader turn toward neoliberal governance that seeks market-based solutions, increasingly married with technology, to urban issues.

Uber’s political project has shown a keen awareness of the problems facing cities and has succeeded in offering itself as a solution, even if it is a poor solution. Uber presents itself as an alternative to a crumbling public transit system, a poorly regulated taxi industry, increasing precarity for low-wage workers, and even an answer to deep-seated racial inequity. The ground for Uber’s attack on cities was prepared by a four-decade attack on the public sector.

The technology-driven answers to city problems proposed by companies like Uber may seem apolitical, but you argue that’s not the case. Can you explain your argument here? What do you find problematic about Uber’s “solutions”?

One of Silicon Valley’s key successes has been to reframe urban problems as technical ones. The idea that technology offers solutions that are free from politics is not a new one. In fact, one could argue “tech solutionism” has been a key plank of neoliberal governance, but it has reached new heights over the past decade and a half.

Automated vehicles (AVs) are a great case in point. The rise of Uber in the 2010s went hand in hand with a promise that Uber would build the city of the future. The media reported endlessly on the impending transformation of urban life by new technologies. Cities, lacking a different vision, bought into this futuristic vision that promised us smarter cities seamlessly connected by AVs and flying cars. Beyond limited testing, of course, we don’t really see AVs at work in Washington, DC, though there is an increasing scaling up in other cities like San Francisco where they have been fiercely resisted.

We argue that questions around AVs — when they will arrive, how do we prepare for them, and so on — are largely a distraction from more pressing issues. Instead, we should focus on what the idea of AVs does right now to how we think about urban politics. When we hear claims that delivery robots can help eliminate food deserts, we foreclose other, nontechnological means of addressing urban problems. Food deserts don’t exist because we have absentmindedly placed people too far from food. They are a result of structural issues tied up with real estate, uneven urban development, social inequities, and public transport.

Furthermore, there is very little evidence that these technological fixes even work and don’t make cities more unequal. In Washington, DC, for example, we show that many of these technological solutions — delivery and security robots, AVs, and platform technologies like Uber itself — build on and intensify the very problems they purport to solve. Delivery robots and limited AV routes tend to be deployed on college campuses and in DC’s glittering new condo complexes that mark the front line of the city’s rapidly gentrifying landscape. They are not catchall solutions; rather, they feed on and intensify the yawning gaps in the city’s landscape.

The solutions to urban problems are political in nature. They involve deep discussions and struggles that ask what kind of city we want to live in and who should be able to live in it. We already have the technologies we need to begin to address them; what we lack is the political will. Uber’s promises are narrow and technocratic, inhibiting our ability to pursue democratic solutions that center normative ideals and public goods like public transport.

One way Uber cultivated friendly relations with local politicians early on was by promising to share its data with city governments. City officials argue that this data is valuable because it will help them solve issues like traffic congestion and transit deserts. You object to this idea.

First, the question of data production and ownership is important. Drivers produce the data that Uber commodifies and turns into big data. Uber can then use this data to do a wide range of things, from perfecting its algorithms and surveilling drivers to attracting capital and negotiating with city governments.

The relationship with data is, however, asymmetrical. Uber has the data and cities want it. As we argue in the book, the lure of data is both real and understandable for cities. For urban planners, for example, data appears to be an unqualified good. They can use data to get a better picture of congestion, road usage, parking management, among many other things.

At the same time, a single-minded focus on data is misplaced. The idea that city officials can sit down and look at screens that show the city working in real time is a popular one. Neoliberal and technocratic ideologies seek to convince us that everything from your daily routine to cities can be hacked.

This ideal doesn’t reflect the reality of data. When a city like Washington, DC, receives data from Uber, it is not in real time. The data must be cleaned and shaped into a usable form. That process takes time, money, and expertise that cities often lack.

Even if we could make that data usable, what might it tell us that we don’t already know about life in cities? This deification of quantitative data is a political strategy that seeks to advance technological solutions at the expense of democratic ones. Data can be very helpful, but it is not prescriptive.

You cite the challenges that gig work poses to workers’ organizing, such as atomizing workplace conditions: Uber makes it very difficult for its drivers to ever meet and talk with one another.

However, your interviews with Uber drivers seem to show that most Uber drivers do not see themselves as workers — many see themselves as smarter than the average driver and think of Ubering as a side gig rather than a main career. This would seem to be an additional obstacle to organizing. How do you think these sorts of attitudes can be changed or overcome?

The platform workplace, like many workplaces, is made up of strangers. But the platform workplace is unique in the extent to which it keeps workers strangers and creates barriers to them interacting with each other.

The atomized and flexible nature of the work, including workers’ employment status as independent contractors, has limited expressions of worker solidarity. Uber’s claims that it employs independent contractors and the gamification of the app means that workers increasingly see themselves as not just trying to outsmart that app, but as pitted against one another in competition. The individualized and competitive nature of this work is difficult to overcome.

The lack of physical space, like a shop floor or dispatch office, in which platform workers meet or congregate creates another material barrier to the possibility for notions of collective worker consciousness to emerge. There is no obvious place where you can turn a stranger — someone unknown and not one’s own — into someone for whom you do the hard work of caring, trusting, and maintaining relationships.

These relationships may not simply emerge from drivers being in the same place. There are also class and racial divisions among drivers. Some middle-class drivers we spoke to were embarrassed that they had to resort to Uber to make ends meet and feared the day someone they knew would get in their car. Others pointed out that they were aware of Uber’s exploitative nature, but they had figured out how to make it profitable for them by outsmarting the app and other drivers.

Despite these challenges, workers have succeeded in organizing. One example of this we show was at Washington, DC’s airport, where the ride-hailing parking lot put drivers in contact with each other and saw them able to strategize and organize, resulting in a moderately successful strike. Uber managed to successfully defeat this movement, but these processes of resistance are in their infancy and will hopefully grow as the nature of platform exploitation becomes more obvious.

When workers see each other, talk with each other, and start to care about each other, the seeds of meaningful solidarity are sown. Without that collectivity, which requires physical proximity and place to be together, it feels hard to imagine that the attitudes common to workers in the gig economy will be overcome.

One of the central claims of your book is that Uber has been so successful because citizens have lowered their expectations of the government. As a result, citizens (and politicians) have looked to corporations instead of the government for solutions to structural problems.

You argue that to combat this, confidence in the public realm needs to be restored. How might this be achieved?

Few of the people we interviewed for Disrupting D.C. saw Uber as a perfect solution for the problems that so often define cities like DC. Yet one of our major findings was that even fewer saw such solutions coming from either city government or through the work of “politics proper.”

In short, Uber’s success emerged in the context of the very low expectations we have that our political system can offer the kinds of solutions we need. The question of how to restore confidence in the possibility of politics is a difficult but crucial one.

We don’t offer any prescriptive answers to this question in the book. Instead we point to all the different groups that are already building a new common sense not defined by Uber’s narrow worldview. We can pursue this achievement by collectively resisting Uber’s politics and by pursuing alternatives — like that of the Green New Deal, for instance.