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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.
Alex Rosenblat is an ethnographer who studies how people experience technology. She also examines the rhetorical claims that shape the stories we tell about the impact of technology on society. Rosenblat is the author of Uberland: How Algorithms Are Rewriting the Rules of Work. A Senior Researcher at Data & Society and a Fellow at the Aspen Institute Tech Policy Hub, 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, the Harvard Business Review, and The Globe & Mail. Her research has received attention worldwide, and has been covered in The New York Times, The Wall Street Journal, New Scientist, and The BBC. Among the scholarly and professional publications in which her prize-winning work has been published are the International Journal of Communication and the Columbia Law Review. Her published research is situated at the intersection of technology and labor, and her upcoming research explores sovereignties, nationalisms, and the fragmentation of shared social facts.
Source: Data & Society Research Institute
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