Description

Book Synopsis
We are often expected to trust technologies, and how they are used, even if we have good reason not to. There is no room to mistrust. Exploring relations between trust and mistrust in the context of data, AI and technology at large, this book defines a process of ‘trustification’ used by governments, corporations, researchers and the media to legitimize exploitation and increase inequalities. Aimed at social scientists, computer scientists and public policy, the book aptly reveals how trust is operationalized and converted into a metric in order to extract legitimacy from populations and support the furthering of technology to manage society.

Table of Contents
1. Introduction: Trust Issues 2. Trustification: Extracting Legitimacy 3. State: Measuring Authority 4. Corporate: Managing Risk 5. Research: Setting Terms 6. Media: Telling Stories 7. Case Study: COVID-19 Tracing Apps 8. Case Study: Tech for Good 9. Case Study: Trusting Faces 10. Conclusion: False Trade-Offs

Mistrust Issues: How Technology Discourses

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    Order before 4pm today for delivery by Thu 23 Jul 2026.

    A Hardback by Garfield Benjamin

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      Publisher: Bristol University Press
      Publication Date: Publication Date: 15/09/2023
      ISBN13: 9781529230871, 978-1529230871
      ISBN10: 152923087X
      Also in:
      Computing Social and ethical aspects Dictionaries, Reference & Language Communication studies Science & Nature Impact of science and technology on society

      Description

      Book Synopsis
      We are often expected to trust technologies, and how they are used, even if we have good reason not to. There is no room to mistrust. Exploring relations between trust and mistrust in the context of data, AI and technology at large, this book defines a process of ‘trustification’ used by governments, corporations, researchers and the media to legitimize exploitation and increase inequalities. Aimed at social scientists, computer scientists and public policy, the book aptly reveals how trust is operationalized and converted into a metric in order to extract legitimacy from populations and support the furthering of technology to manage society.

      Table of Contents
      1. Introduction: Trust Issues 2. Trustification: Extracting Legitimacy 3. State: Measuring Authority 4. Corporate: Managing Risk 5. Research: Setting Terms 6. Media: Telling Stories 7. Case Study: COVID-19 Tracing Apps 8. Case Study: Tech for Good 9. Case Study: Trusting Faces 10. Conclusion: False Trade-Offs

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