Uberland: How Algorithms Are Rewriting the Rules of Work

Uberland: How Algorithms Are Rewriting the Rules of Work

by Alex Rosenblat
Uberland: How Algorithms Are Rewriting the Rules of Work

Uberland: How Algorithms Are Rewriting the Rules of Work

by Alex Rosenblat

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Overview

Silicon Valley technology is transforming the way we work, and Uber is leading the charge. An American startup that promised to deliver entrepreneurship for the masses through its technology, Uber instead built a new template for employment using algorithms and Internet platforms. Upending our understanding of work in the digital age, Uberland paints a future where any of us might be managed by a faceless boss.
 
The neutral language of technology masks the powerful influence algorithms have across the New Economy. Uberland chronicles the stories of drivers in more than twenty-five cities in the United States and Canada over four years, shedding light on their working conditions and providing a window into how they feel behind the wheel. The book also explores Uber’s outsized influence around the world: the billion-dollar company is now influencing everything from debates about sexual harassment and transportation regulations to racial equality campaigns and labor rights initiatives.
 
Based on award-winning technology ethnographer Alex Rosenblat’s firsthand experience of riding over 5,000 miles with Uber drivers, daily visits to online forums, and face-to-face discussions with senior Uber employees, Uberland goes beyond the headlines to reveal the complicated politics of popular technologies that are manipulating both workers and consumers.

Product Details

ISBN-13: 9780520324800
Publisher: University of California Press
Publication date: 10/15/2019
Edition description: First Edition
Pages: 296
Product dimensions: 5.50(w) x 8.60(h) x 0.90(d)

About the Author

Alex Rosenblat is a technology ethnographer. A researcher at the Data & Society Research Institute, she holds an MA in sociology from Queen’s University and a BA in history from McGill University. Rosenblat’s writing has appeared in media outlets such as the New York Times, Harvard Business Review, the Atlantic, Slate, and Fast Company. Her research has received attention worldwide and has been covered in the New York Times, the Wall Street Journal, MIT Technology Review, WIRED, New Scientist, and the Guardian. Many scholarly and professional publications have also published her prizewinning work, including the International Journal of Communication and the Columbia Law Review.


Read an Excerpt

CHAPTER 1

DRIVING AS GLAMOROUS LABOR

How Uber Uses the Myths of the Sharing Economy

In the spring of 2010, Uber launched the first beta version of its now-famous smartphone app. It promised to revolutionize transportation. Uber offered anyone with a car a new way to earn extra income through casual jobs as a driver. Meanwhile, anyone needing a ride could now benefit from an affordable, on-demand chauffeur service to get around. The Uber platform allows users to seamlessly connect passengers and drivers: it calculates the rates, transmits credit card information, and maintains quality ratings for drivers and riders alike.

As a company, Uber has unquestionably changed the way people get around hundreds of cities across the world. It has become a symbol of the New Economy and, for some, the future of work. Uber advertises that its drivers are entrepreneurs who can, with flexible schedules, make middle-class incomes even in an unstable economy. But do these assertions hold up to scrutiny, or is the company playing us with false claims?

THE GREAT RECESSION AND THE SHARING ECONOMY

Before we can understand how Uber treats its drivers, it's necessary to take a step back. Uber's employment model was born in the so-called sharing economy, a social technology movement that capitalized on the economic instability of the Great Recession to sell a narrative. Between 2007 and 2009, the Great Recession and collapse of the subprime mortgage markets ravaged American households with waves of foreclosures. The collapse of financial markets challenged societal confidence in American institutions, like banking and governance, while an exodus of former homeowners shut down neighborhoods and led to urban blight in cities like Detroit and Cleveland. Job losses increased suddenly, and national unemployment climbed to 10 percent in October 2009. This instability sharpened the economic consequences of prolonged joblessness for white-collar workers, who comprised 60 percent of the labor force; by 2009, they accounted for nearly half of the long-term unemployed. Still, the greatest job losses from the Great Recession were concentrated in blue-collar industries among workers under thirty. Although the Great Recession officially ended in June 2009, its impact on unemployment persisted well into the economic recovery.

This context helps explain why sharing-economy companies with roots in Silicon Valley, like Uber, so often frame their technologies as powerful engines of job creation. In the media and in some academic debates, the future of work is framed as the threat of a robot coming for your job. While society may benefit from automated work, the fear is that these benefits will not be distributed equally: jobless futures imply some will get left behind. This threat is not an inherent characteristic of technology but, rather, comes from the current American economic climate. As Philip Alston, a poverty investigator from the United Nations, observed at the end of 2017, "The reality is that the United States now has probably the lowest degree of social mobility among all the rich countries. And if you are born poor, guess where you're going to end up — poor." When technology innovators use "job creation" language, they engage in virtue-signaling: the implication is that not only do they deserve credit for producing large economic gains for society, but also they should be shielded from harsh criticism for their methods because the end result is positive.

The sharing economy promised to save the day for a population shaken by the Great Recession: using technology, millions of people across society would now be able to efficiently pool and share their limited resources. The seeds of Uber took root in a climate of profound economic uncertainty. After the recession hit in 2007, shockwaves of economic downturn rippled across the globe: Greece's government tumbled into insolvency, while in Iceland, bankers were frog-marched to jail for burdening the country with a private banking debt seven times its annual GDP. In the aftermath, the front pages of newspapers regularly featured Middle Eastern and African refugees drowning as they tried to reach Europe, compounding a sense of economic urgency in the United States with global humanitarian concerns arising from geopolitical conflict. The collapse of Wall Street was a reminder that no empire, not even the American kingdom of financiers, is absolute. At the World Bank and the International Monetary Fund, leading economists began to rewrite their theories with a new focus on income equality, replacing earlier ideas that had emphasized growth above all else.

Back in the United States, victims of the Great Recession began to push back against the corporations and practices that had caused the crisis. The City of Baltimore, the State of Illinois, and the Pennsylvania Human Rights Commission, among other, bigger victims of foreclosures, sued the notorious lending institutions whose high-risk lending fueled the Great Recession — institutions like Wells Fargo — and settled for hundreds of millions. Predatory lending practices targeted racial minorities during the subprime boom, highlighting the role of finance in social injustice. Emergent social movements that advocate for social equity, like Occupy Wall Street, organized activists with a common desire to re-center society around a moral economy.

While Occupy Wall Street activists formed a tent city in Zuccotti Park on Wall Street, members of Black Lives Matter were staging protests across the country to advocate a political agenda that could address the root causes of inequality. Soon, more voices joined the chorus, this time from the top. Facebook cofounder and philanthropist Chris Hughes dedicated his intellectual thought leadership to promoting a universal basic income, and Mark Zuckerberg, his former roommate, mentioned it in the commencement speech he gave at Harvard. This quasi-moral solution to income inequality — and to expanding the definition of equality for this generation — finds its strongest American proponents in Silicon Valley. Home to the billion-dollar titans of industry, who form a slightly reluctant political elite in the New Economy, Silicon Valley and the culture of technology radiate influence across the business, political, and media culture of major American cities. And Silicon Valley has a strong stake in national debates over whether automation technology, such as self-driving cars, will take all our jobs. Universal basic income is one form of "automation alimony" that is proposed to relieve the rising inequality often attributed to automation.

It was in this economic and cultural climate that the buzz around "the sharing economy" began. Its promise was seductively simple. The sharing economy was a social technology movement designed to use tech to share resources more efficiently — a true "commonwealth" aimed at remedying some of the insecurity fostered by the Great Recession. The sharing economy was built atop earlier cultural conversations, like those about rental commerce, car-sharing, and cooperative housing. Technology could connect those who possessed underutilized assets, skills, or time with potential consumers, a form of commerce that reduced the costs of ownership and more efficiently distributed goods and services. For struggling millennials displaced by the recession, this new model provided a hopeful new paradigm for earning income. As Robin Chase, cofounder of the car-sharing service Zipcar, wrote in 2015, "In the new collaborative economy, sharing and networking assets, like platforms, car seats and bedrooms, will always deliver more value faster."

Critics, like scholar Nick Srnicek, countered the idea that the sharing economy was anything novel, branding it as a mere reiteration of the platform capitalism of the 1970s. Arguing that platform capitalism will hasten the end of work, Srnicek advocates a future of different possibilities. Meanwhile, culture scholar-activist Trebor Scholz sees platform cooperativism as a viable way of redistributing corporate profits of platforms like Uber to workers. The disparity between billiondollar tech giants and the rest of society makes it easy for critics of capitalism to shout from the rooftops, and by the mid-2010s they weren't alone. The question that academics, policy makers, labor advocates, and others were asking outright, with greater insistence, by the end of 2017 was blunt: Why aren't wages growing in America?

Against this contentious backdrop, ridehailing platforms began promoting themselves as a pathway to the middle class for anyone who wanted to drive. Uber quickly became the poster child for the sharing economy, advertising itself as "a smartphone app that connects riders and drivers at the touch of a button." Founded in March 2009 in San Francisco, the company grew quickly by hiring decentralized staff in each new city or region. These new staff were empowered to establish Uber's operations with lightning speed, like a vast network of start-ups. By the middle of 2017, the company operated in over 630 cities worldwide, and it had provided 5 billion rides to passengers. By March 2018, it had 3 million active drivers worldwide. More importantly though, Uber offered its drivers a job with personal autonomy and a path to a middle-class life, even as that middle class was shrinking. Meanwhile, as early as 2014, Uber announced that the median income of its drivers was a little more than ninety thousand dollars per year in New York City and over seventy-four thousand dollars in San Francisco.

Arguably, the chief accomplishment of technology in the sharing economy has been the creation of robust platforms for serving temporary jobs to a flexible workforce that cycles through a variety of part-time or precarious and temporary jobs to make ends meet. Of course, gig work predates the technological framework that the sharing economy draws on as one of its distinguishing characteristics. Economists Lawrence F. Katz and Alan Krueger argue that the percentage of workers employed in gig work climbed from 10.07 percent in February 2005 to 15.8 percent in late 2015, a decade later. (Although growth in this area is high, the exact measures of the gig economy are unknown: the Bureau of Labor Statistics did make plans to conduct a 2017 survey of contingent workers, though their efforts are still pending as this book goes to press.)

The prevalence of temp, gig, and contingent work is summed up by a Wall Street Journal headline at the end of 2017 announcing, "Some of the World's Largest Employers No Longer Sell Things, They Rent Workers." Highlighting how three out of five of the biggest employers in the United States distribute contract labor, the article describes how they operate like temp agencies. Uber shows us how a company can organize masses of people through technology into discrete units who are available on demand to take passengers from point A to point B — until the drivers opt to log out. That same technology fundamentally alters labor relations as well: drivers are billed as consumers of Uber's connective technology, rather than as workers.

To join the Uber driver workforce, prospective drivers download the Uber driver app onto their mobile smartphones. They then take their Uber-eligible vehicles to local mechanics to be certified as in good working order and upload their driver's license numbers and auto insurance policy numbers to their accounts on Uber's website or through the app (drivers I speak with rarely obtain commercial insurance, unless they are obliged to by regulatory requirements). Then, after consenting to a background check that takes under a week in many places, they're ready to go. In other words, barriers to entry are very few. Part of what makes platforms so valuable is their ability to provide jobs to anyone and everyone in a decentralized workforce. As economic sociologist Vili Lehdonvirta observes:

Piece rates are a substitute for more direct managerial control. Employers who pay hourly rates are pickier about whom they accept into their ranks in the first place, whereas one of the strengths of these platforms is that essentially anyone can sign up and start working right away with minimal hurdles. And workers who are paid on an hourly basis usually cannot take breaks quite as easily as pieceworkers. This low entry barrier and potential for almost minute-by-minute flexibility are genuine features of platform-based piecework, and some workers value them.

Uber's platform manifests a profound tension: the company seeks to standardize work for the masses through algorithmic management while, at the same time, distancing itself from responsibility for workers.

The popularity of Uber among passengers has been central to public support for the sharing economy. Bolstered by popular opinion, tech and labor advocates take to the media to discuss how employment through an app is the future of work, a gangway of progressive opportunity off the sinking ship of the post–Great Recession economy. Perhaps underscoring Uber's shiny prospects as a new player in the labor market, economists have noted that after the job losses of the Great Recession, "recovery job gains came largely from new establishments entering the economy." Sharing-economy employment is often concentrated in the service industry: jobs like delivering passengers, food, or laundry cannot easily be offshored or automated (yet).

With the example of Uber's success, countless other firms began following suit. It seemed that every new company, from domestic cleaning platforms like Handy to the multi-industry temping platform Fiverr, wanted to idolatrously claim their service as the "Uber for X." Many of these imitators went belly-up, including Prim, for on-demand laundry services; HomeJoy, a home-cleaning marketplace; Tutorspree, for tutoring; and SideCar, a direct Uber competitor. Nevertheless, Uber inspired a variety of companies across industries, including nursing, trucking, and others, to think about how technology can be used to create efficient on-demand services by organizing independent providers and consumers through a digital platform. Defining the sharing economy is like trying to nail Jell-O to a wall. It is a haze of converging ideas with popular appeal. Will employers across industries adopt sharing technology to manage their workforces?

The sharing economy grew much more quickly than anyone imagined it would. A Pew Research Center survey published in November 2016 shows that 8 percent of American adults earned money from an online employment platform in the previous year across industries such as ridehailing, online tasks, or cleaning/laundry. Rounds and rounds of venture capital funding bolstered Uber and Airbnb, the two most successful companies to emerge from the sharing-economy period. Both companies became "unicorns," a term for start-ups that reach billion-dollar valuations. In 2016, Uber reached a $68 billion valuation, while Airbnb was valued at $30 billion, less than a decade after their beginnings in 2009 and 2008, respectively. By July 2017, the Oxford Internet Institute's iLabour Project published a report finding that the online sharing economy, which includes clerical and data entry services for jobs posted online, had grown 26 percent in the previous year.

But as the sharing economy has grown, things have gotten complicated. Increasingly, the "sharing economy" has been identified as an intensification of the "gig economy," as people have become suspicious of the way that words like sharing euphemistically describe precarious, part-time, and piecework employment. Scholars, as well as media outlets like the New York Times and Buzzfeed, have moved to rechristen "ridesharing" as "ridehailing" in an attempt to ease the contradiction between altruism and employment. The sharing-economy language has long been both expansive and imprecise, recasting service industry and white-collar jobs alike in the amorphous terms of digital culture and the New Economy.

The sharing economy has also made for odd bedfellows: hopeful, left-leaning advocates of cooperative housing and bike-sharing found themselves allying with industry tech positivists (those who believe that technology will inevitably lead to continual social progress). As sharing technology has taken on a more significant role in society, other civil society actors have chosen to become stakeholders in Uber's future developments. The National Association for the Advancement of Colored People allied with Uber to provide employment for drivers with nonviolent criminal records, and Mothers Against Drunk Driving promoted Uber to reduce drunk driving through ridehailing. (Later, when the working conditions of drivers proved wanting, civil rights advocates were effectively pitted against labor rights advocates through Uber's clever maneuvering, though they might otherwise have found common ground in protecting the rights of vulnerable groups.)

(Continues…)


Excerpted from "Uberland"
by .
Copyright © 2018 Alex Rosenblat.
Excerpted by permission of UNIVERSITY OF CALIFORNIA PRESS.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

Table of Contents

Acknowledgments vii

Introduction: Using an App to Go to Work-Uber as a Symbol of the New Economy 1

1 Driving as Glamorous Labor: How Uber Uses the Myths of the Sharing Economy 21

2 Motivations to Drive: How Uber's System Rewards Full-Time and Recreational Drivers Differently 49

3 The Technology Pitch: How Uber Creates Entrepreneurship for the Masses 73

4 The Shady Middleman: How Uber Manages Money 107

5 Behind the Curtain: How Uber Manages Drivers with Algorithms 138

6 In the Big Leagues: How Uber PLays Ball 167

Conclusion: The New Age of Uber-How Technology Consumption Rewrote the Rules of Work 197

Appendix 1 Methodology: How I Studied Uber 209

Appendix 2 Ridehailing beyond Uber: Meet Lyft, the Younger Twin 217

Notes 221

Index 261

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