Diane E. Bailey

Diane E. Bailey is Associate Professor in the School of Information at the University of Texas at Austin.

  • Technology Choices

    Technology Choices

    Why Occupations Differ in Their Embrace of New Technology

    Diane E. Bailey and Paul M. Leonardi

    An analysis of the occupational factors that shape the technology choices made by people who perform the same type of work.

    Why do people who perform largely the same type of work make different technology choices in the workplace? An automotive design engineer working in India, for example, finds advanced information and communication technologies essential, allowing him to work with far-flung colleagues; a structural engineer in California relies more on paper-based technologies for her everyday work; and a software engineer in Silicon Valley operates on multiple digital levels simultaneously all day, continuing after hours on a company-supplied home computer and network connection. In Technology Choices, Diane Bailey and Paul Leonardi argue that occupational factors—rather than personal preference or purely technological concerns—strongly shape workers' technology choices.

    Drawing on extensive field work—a decade's worth of observations and interviews in seven engineering firms in eight countries—Bailey and Leonardi challenge the traditional views of technology choices: technological determinism and social constructivism. Their innovative occupational perspective allows them to explore how external forces shape ideas, beliefs, and norms in ways that steer individuals to particular technology choices—albeit in somewhat predictable and generalizable ways. They examine three relationships at the heart of technology choices: human to technology, technology to technology, and human to human. An occupational perspective, they argue, helps us not only to understand past technology choices, but also to predict future ones.

    • Hardcover $35.00 £28.00

Contributor

  • Big Data Is Not a Monolith

    Big Data Is Not a Monolith

    Cassidy R. Sugimoto, Hamid R. Ekbia, and Michael Mattioli

    Perspectives on the varied challenges posed by big data for health, science, law, commerce, and politics.

    Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies.

    The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, “data harm,” and decision making.

    Contributors Ryan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West

    • Hardcover $60.00 £50.00
    • Paperback $30.00 £25.00