Mistrust Issues: How Technology Discourses Quantify, Extract and Legitimize Inequalities

This book explores the relationship between trust and mistrust in the context of data, AI, and technology, and how it is used to legitimize exploitation and increase inequalities. It defines a process of 'trustification' used by governments, corporations, researchers, and the media to extract legitimacy from populations and support the furthering of technology.

Format: Hardback
Length: 186 pages
Publication date: 15 September 2023
Publisher: Bristol University Press

We are frequently compelled to place our faith in technologies and their applications, even when legitimate reasons exist to doubt their reliability. There is no margin for skepticism. This book delves into the intricate relationships between trust and mistrust in the realm of data, artificial intelligence, and technology, as a whole. It establishes a framework called "trustification," which is employed by governments, corporations, researchers, and the media to justify exploitation and exacerbate inequalities. With a focus on social scientists, computer scientists, and public policy, the book effectively uncovers the mechanisms through which trust is operationalized and transformed into a metric, enabling it to be extracted from populations and used to reinforce the legitimacy of technology in governing society.

Introduction:
In today's interconnected world, technologies have become an integral part of our daily lives. From smartphones to social media platforms, we rely on these tools to communicate, work, and access information. However, with the rapid advancement of technology, concerns about trust and mistrust have also emerged. Trust is essential for the successful adoption and implementation of technology, as it determines whether people are willing to share their data and engage with these systems. On the other hand, mistrust can lead to resistance, skepticism, and even rejection of technology.

Trustification:
The concept of "trustification" is central to understanding the dynamics between trust and mistrust in the context of data, AI, and technology. It refers to the process by which governments, corporations, and other stakeholders use various strategies to establish and maintain trust in technologies. Trustification involves the creation of narratives, symbols, and rituals that reinforce the legitimacy and reliability of technology. It also involves the establishment of regulatory frameworks and policies that ensure the responsible use of technology.

Trust and Mistrust in Data:
Data is the foundation of many technologies, including artificial intelligence (AI) and machine learning. However, concerns about data privacy, security, and bias have led to mistrust among individuals. Trustification in data involves the establishment of transparent and accountable data practices, such as data anonymization, encryption, and access controls. It also involves the development of ethical guidelines and standards for data use and management.

Trust and Mistrust in AI:
AI is a rapidly evolving technology that has the potential to transform various industries and improve our lives. However, concerns about AI's ability to make autonomous decisions, its potential for bias, and its impact on employment have led to mistrust among individuals. Trustification in AI involves the development of ethical guidelines and standards for AI development and deployment. It also involves the establishment of regulatory frameworks that ensure the responsible use of AI.

Trust and Mistrust in Technology:
Technology, as a whole, has the potential to bring about significant positive changes in society. However, concerns about its impact on privacy, security, and social inequality have led to mistrust among individuals. Trustification in technology involves the development of transparent and accountable technology practices, such as privacy policies, security measures, and access controls. It also involves the promotion of digital literacy and education to empower individuals to understand and navigate the digital landscape.

Conclusion:
In conclusion, trust and mistrust are complex and multifaceted issues that are intertwined with the development and adoption of data, AI, and technology. Trustification is a critical process that can help establish and maintain trust in these technologies. By adopting transparent and accountable practices, developing ethical guidelines and standards, and promoting digital literacy, we can work towards creating a more trust-based and inclusive digital society.

Dimension: 203 x 127 (mm)
ISBN-13: 9781529230871