Data Enclaves

data collection, use, and exploitation by Big Tech firms and their conversion of personal data into a private asset that is legible and measurable as a valuable resource, while problematizing the idea that it is the characteristics of the digital technologies themselves that underpins Big Tech's increasing influence.

 

Chapter 3: The Rise of Data Rentiership

 

Thinking of the transformation of personal data into a private asset helps us to understand the emerging forms of data governance pursued by Big Tech. These firms turn our personal data into a private asset in order to extract value from it. This assetization of personal data depends on a range of activities, but firms like Apple, Amazon, Microsoft, Google, and Facebook can capture the most value by creating data monopolies from the network effects and monopolistic strategies enabled by their extension of digital ecosystems comprising platforms, devices, contractual arrangements, users, developers, etc. As a result, digital technologies have ended up configured and shaped by the search for ways to create, extend, and reinforce control over data, creating various forms of rentiership ranging from the buying up of competitors through limiting regulations and competition by lobbying governments to creating self-preferential on their platforms. Data rentiership entails creating a series of data enclaves designed to limit access to personal and user data and to get us to spend as much of our time as creating more data by using our smartphones, computers, or social media. As a result, Big Tech has created a series of walled data gardens that lock-in users, competitors, and policymakers to particular visions of future innovation in which the role of Big Tech seems necessary and inevitable.

 Chapter 4: Emerging Data Enclaves



 

As the collection of our personal data has increased, Big Tech firms have become more dependent on data rentiership as a way to make money. Today, a few Big Tech firms have amassed so much of our personal data that many policymakers, businesspeople, academics, activists, journalists, and others fear these data enclaves will limit the emergence of new digital technology startups to compete with these incumbent firms. This chapter will consider how Big Tech's data enclaves give these firms a problematic first-mover advantage when it comes to developing new digital technologies, especially algorithmic systems and artificial intelligence that need large datasets to 'train' them. This stifling of innovation is just one fear, however, as there are many other concerns about the implications of these data enclaves to our privacy or democracy. The chapter will also outline some of the wider social implications of these data enclaves on artificial intelligence and algorithmic systems in the entrenchment of social prejudices or economic discrimination.

 

Chapter 5: Monopoly, Competition, and Emergent Data

 

Contemporary capitalism is increasingly driven by the pursuit of data enclaves. This transformation is ongoing and has created a tension between those who think that our current laws are able to regulate data-driven economies and those who think that we need to rethink our market rules, especially when it comes to dealing with monopoly and market competition. This chapter will outline the fundamental disruption of contemporary, technoscientific capitalism caused by data enclaves, which makes it such a distinct techno-economic system and, therefore, one that needs a range of new policies and regulatory mechanisms to ensure that the economy does not end up monopolized by a few Big Tech firms. The chapter will examine changes the emergent properties of personal data as a digital asset form; that is, the properties of personal data as an aggregated, political-economic object. These properties entail a totally different approach to competition policy and law. Currently different countries are pursuing different approaches to monopoly and competition policy in response to the emerging problems that data enclaves engender, but these different policymakers do not always understand the implications of 'emergent' data to the functioning of markets.

 

Chapter 6: A New Policy Agenda for Data Governance

 

Rather than a normal conclusion, the book will end by outlining a new policy agenda for data governance in light of the preceding chapters. This new policy agenda focuses specifically on the importance of going beyond privacy and market-based approaches to the governance of personal data. As post hoc and distinct governance approaches, privacy and competition policies are limited in the ways that they can build new social demands into the collection and use of our personal data. Rather, this chapter will discuss how personal data governance and competition policy needs to be built on an aggregate and emergent perspective of personal data - for example, the collection and use of my personal data impacts you, whether you like it or not, and vice versa - and develop 'proactionary' approaches to data governance and competition that: (1) establishes the goals of digital innovation before Big Tech develops new products and services; (2) restricts the capacity of Big Tech to experiment on us with new technologies; and (3) develops a new understanding of contract and contract law with 'modular' contractual articles/principles that users can pick and choose from without losing access to the services or products they need to live their lives.