Digest

Christina Alamo, an assistant professor of research of digital economy and society at Louise University, joins the DataFrame podcast to discuss her book "Data Rules: Reinventing the Market Economy" co-authored with Yanis Kalinikus. The book explores the history and sociology of data, examining how data has become central to modern society and organizations. Alamo highlights pivotal moments in the history of data, including the use of clay tokens for recording transactions, the rise of statistics for governing collective behavior, the emergence of modern corporations and their reliance on internal data, and the advent of computers as digital data makers. She emphasizes the importance of understanding data not just as input for large systems but as artifacts of human making, instruments of communication, and tokens through which knowledge is transmitted. Alamo discusses the concept of "datification," the translation of events and episodes of life into data, and the complex ecosystem of actors involved in this process. She explores the implications of AI for data work and surveillance, arguing that AI will accelerate the dynamics of datification and require new approaches to regulation. Alamo emphasizes the need for data literacy, a deeper understanding of data's role in society, and the blurring of boundaries between different spheres of life, such as work and private life, due to the increasing reliance on data. She advocates for a social science of data to address the complex issues arising from the pervasive use of data in our lives.

Outlines

00:00:00

Introduction

This Chapter introduces the topic of the podcast episode, which is the history and sociology of data, and introduces Christina Alamo, the guest speaker and co-author of the book "Data Rules." The episode aims to explore how data has become foundational to modern society and organizations and how previous paradigm shifts can help inform us about future ones.

00:02:14

Motivation for Writing "Data Rules"

This Chapter delves into the motivation behind writing the book "Data Rules." Christina Alamo explains that the book was inspired by the pervasive presence of data in our lives and the need to understand its impact on both everyday life and institutions. She emphasizes the importance of viewing data not just as input for large systems but as artifacts of human making, instruments of communication, and tokens through which knowledge is transmitted.

00:04:59

The History of Data

This Chapter explores the history of data, tracing its evolution from the use of clay tokens for recording transactions to the advent of computers as digital data makers. Christina Alamo identifies pivotal moments in this history, including the rise of statistics for governing collective behavior, the emergence of modern corporations and their reliance on internal data, and the advent of computers as digital data makers. She argues that these historical developments demonstrate the close link between data, institutions, and social cognition.

00:12:52

Data and Generative AI

This Chapter examines the implications of generative AI for data work and society. Christina Alamo argues that generative AI represents a potential new pivotal moment in the history of data, requiring a broader understanding of data beyond its role as input for large systems. She emphasizes the need to consider the cultural, organizational, and societal implications of AI, asking questions about the types of intelligence it proposes, how it infiltrates existing institutions, and the consequences for our ways of working and knowing.

00:19:01

Datification and its Ecosystem

This Chapter delves into the concept of "datification," the translation of events and episodes of life into data. Christina Alamo explains that datification is a complex process involving multiple actors, stages, and links to social reality and the economy. She uses the example of programmatic advertising to illustrate the ecosystem of datification, highlighting the challenges of measuring user attention and the need for proxies and verification systems. She argues that datification is not a straightforward process but involves decision-making, links to existing practices, and the participation of various actors, including regulators and users.

00:29:02

Digital Surveillance and its Implications

This Chapter explores the issue of digital surveillance, offering a nuanced perspective that goes beyond the traditional narrative of large tech companies monitoring user behavior. Christina Alamo argues that surveillance is not simply a means to an end but a byproduct of a complex production process that involves user participation. She emphasizes the need to regulate surveillance practices while protecting user rights and access to services. She suggests that data literacy and the active participation of users, government agencies, and civil society are crucial for addressing the challenges of digital surveillance.

00:37:56

Blurring of Life's Boundaries

This Chapter examines the blurring of boundaries between different spheres of life, such as work and private life, due to the increasing reliance on data. Christina Alamo argues that data has become so central to our lives that social interaction has become a resource for economic value production. She explains that the homogeneity of data representation across different activities, such as buying groceries, studying, and entertaining, has led to the blurring of boundaries between these spheres. She uses the example of TripAdvisor to illustrate how institutions, such as the hospitality industry, are adapting to this blurring of boundaries by leveraging data to offer services that transcend traditional sectoral knowledge.

00:42:37

The Path Forward on Regulation

This Chapter discusses the path forward on regulation in the context of AI and the accelerating dynamics of datification. Christina Alamo emphasizes the need for urgent attention to the regulation of AI, particularly in relation to the use of data without transparency. She advocates for a more nuanced approach to regulation that considers data as complex cognitive artifacts rather than simply inputs for systems. She highlights the importance of addressing the risks posed by AI applications to certain communities and the need to regulate the ecosystems of AI production. She concludes by emphasizing the importance of data literacy and a social science of data to address the complex issues arising from the pervasive use of data in our lives.

Keywords

Q&A

• What motivated Christina Alamo and Yanis Kalinikus to write "Data Rules?"

  They were motivated by the pervasive presence of data in our lives and the need to understand its impact on both everyday life and institutions. They wanted to move beyond a narrow view of data as just input for large systems and explore its role as artifacts of human making, instruments of communication, and tokens through which knowledge is transmitted.

• What are some pivotal moments in the history of data that Christina Alamo highlights?

  She highlights the use of clay tokens for recording transactions, the rise of statistics for governing collective behavior, the emergence of modern corporations and their reliance on internal data, and the advent of computers as digital data makers.

• How does Christina Alamo view the implications of generative AI for data work and society?

  She believes that generative AI represents a potential new pivotal moment in the history of data, requiring a broader understanding of data beyond its role as input for large systems. She emphasizes the need to consider the cultural, organizational, and societal implications of AI, asking questions about the types of intelligence it proposes, how it infiltrates existing institutions, and the consequences for our ways of working and knowing.

• What is "datification" and how does Christina Alamo describe its ecosystem?

  Datification is the translation of events and episodes of life into data. It is a complex process involving multiple actors, stages, and links to social reality and the economy. The ecosystem of datification includes actors who create, process, and use data, as well as those who verify and certify data quality. It is a dynamic and evolving system that is constantly adapting to new technologies and practices.

• How does Christina Alamo approach the issue of digital surveillance?

  She argues that surveillance is not simply a means to an end but a byproduct of a complex production process that involves user participation. She emphasizes the need to regulate surveillance practices while protecting user rights and access to services. She suggests that data literacy and the active participation of users, government agencies, and civil society are crucial for addressing the challenges of digital surveillance.

• What does Christina Alamo mean by the "blurring of life's boundaries"?

  She argues that the increasing reliance on data has led to the erosion of distinctions between different spheres of life, such as work and private life. This blurring of boundaries is driven by the homogeneity of data representation across different activities and the ability to leverage data to create new services and products that transcend traditional sectoral knowledge. It raises questions about the impact on individual autonomy, the nature of work, and the organization of society.

• What are some key aspects of AI regulation that Christina Alamo emphasizes?

  She highlights the need for urgent attention to the regulation of AI, particularly in relation to the use of data without transparency. She advocates for a more nuanced approach to regulation that considers data as complex cognitive artifacts rather than simply inputs for systems. She emphasizes the importance of addressing the risks posed by AI applications to certain communities and the need to regulate the ecosystems of AI production.

• What is the importance of data literacy according to Christina Alamo?

  Data literacy is essential for empowering individuals to participate in discussions about data governance, regulation, and the ethical use of data. It involves understanding the nature of data, its role in society, and its implications for individual lives and institutions.

• What is the role of the "social science of data" in addressing the challenges of data in our lives?

  The social science of data examines the social, cultural, and economic implications of data. It explores the ways in which data shapes our understanding of the world, our interactions with each other, and the organization of society. It is crucial for developing a more nuanced understanding of data's role in our lives and for addressing the challenges and opportunities presented by the increasing reliance on data.

Show Notes