Abstract
The social media giant Twitter was acquired this past October by one of Silicon Valley's quintessential business magnates, Elon Musk, who began charging exorbitant monthly fees to use its application programming interface (API), a mechanism to make platform data accessible. With a free API, programmers could readily design open-access tools for the public good—for instance, identifying political misinformation during the 2020 U.S. elections or saving lives during the February 6th earthquake in Turkey. Researchers also made novel findings in social movements, network science, and public health (Ledford 2023). In response, some Twitter users moved to Mastodon. This nonprofit, decentralized platform stores data across a network of independent servers to ensure transparency, longevity, access, and user autonomy in opposition to data commodification and surveillance. However, Meta, which owns Facebook and Instagram, recently developed "Threads" as a Twitter alternative. With cross-platform integrations using data that Meta already has and well-designed algorithms, Threads is now the most rapidly downloaded app on record (Isaac 2023).
This recent example of Twitter’s paywall, its impacts on innovation and democratic participation, and Meta’s success in developing an alternative aligns perfectly with the arguments outlined in Access Rules: Freeing Data from Big Tech for a Better Future. In this book, Thomas Ramge, a prolific journalist in innovation and technologies, and Viktor Mayer-Schönberger, Professor of Internet Governance and Regulation at Oxford University, argue that tech monopolies restrict data access to construct asymmetries in information, restructuring the global economy while stymieing innovation and democratic participation in the process.
To set the stage for their argument, Chapter One begins with an illustrative story of Benjamin Franklin’s advocacy for information access as vital to democratic participation in response to British Colonial America’s uneven distribution of publications. Drawing parallels to this history, the authors recount how Google and Apple’s refusal to provide data for COVID-19 contact tracing to public health authorities negatively affected efforts to control its spread. On the other hand, open biomedical data-sharing allowed companies and governments to develop a COVID-19 vaccine rapidly.
As they explain in Chapter Two, data is a strategic investment rather than a commodity, and exclusive access allows for a competitive edge. For instance, Google’s self-driving cars overshadow competitors as they use proprietary data from Google’s StreetView cars to accelerate development, building self-perpetuating algorithms that improve themselves with the data they produce. Google’s practices contrast with their roots in 1990s Silicon Valley culture that fostered innovation with values that promoted knowledge-sharing, as sociologist AnnaLee Saxenian’s pivotal work has shown and is outlined in Chapter Four. Eventually, tech monopolies emerged here with venture capital investments and bought competing start-ups.
In Chapter Three, the authors build on but also critique early twentieth-century economist Joseph Schumpeter’s arguments that market overregulation, along with monopolistic dominance, will lead to capitalist decline as markets require innovation to thrive. This dominance is built through "data capitalism," elaborated in Chapter Four, where powerful institutions extract user data for capital. Policymakers have acknowledged this digital authoritarianism and the harms of corporate surveillance, with Europe establishing GDPR (General Data Protection Regulation) based on European values such as consent and privacy. As a result, companies have altered their practices to maintain a presence in the European market, inadvertently rejecting cyberpunk roots and benefiting from this mandate to retain data.
In Chapter Five, Mayer-Schönberger and Ramge discuss global tech policy, as the United States and China are engaged in a "Tech Cold War" of data capitalism. In China, digital superpowers like Baidu, Alibaba, and Tencent have dominated markets with government support and protectionist policies. In the United States, the Biden administration has taken a more confrontational approach to limit Big Tech. The authors argue that companies in both the United States and China practice a new form of colonialism called "data colonialism," where digital click-workers in the global South make only $1 to $3 an hour. Instead of land grabs, they argue, data is the new resource ripe for extraction.
In response to exploitative data extraction and obfuscation, the authors outline recommendations for a data access mandate that treats data as a shared resource for the public good. Furthermore, the authors recommend a data access coalition to disrupt the hegemony of U.S. and Chinese companies and decentralize informational power. Keeping confidentiality and privacy in mind, they argue that a data access mandate could require companies to provide access to depersonalized data, preventing abuse and imposing severe penalties for misuse. Decentralized infrastructures could enable these measures and help distribute information more widely to "democratize data."
While their argument is compelling, Mayer-Schönberger and Ramge's focus on data practices without considering inherent harms limits the scope of data democratization. As they celebrate technological innovation, they bypass how algorithms can perpetuate inequality—for instance, self-driving cars that cannot readily detect Black individuals, as the cars are trained on white bodies, or mortgage lending systems that reproduce neighborhood segregation (Noble 2018). While they encourage capitalist entrepreneurship, I would assert that truly democratic data involves not-for-profit digital infrastructures built by communities, much like Mastodon.
Another significant gap in this book is the need for more underrepresented voices, which is noticeable after paging through the references. While Mayer-Schönberger and Ramge mention the European FAIR (Findable, Accessible, Interoperable, Reusable) principles for data, they do not mention CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) that has arisen with the unmentioned Indigenous Data Sovereignty movement. These voices, for instance, are left out of their celebration of the Human Genome Project (HGP) as one that exemplifies the open sharing of data for accelerating health care innovation. The authors do not mention how such a project reinforces notions of Indigeneity based on European and North American conceptions of DNA that undermine Indigenous self-determination and the global anti-colonial movement (TallBear 2013). "Data colonialism" rings hollow without these critiques in mind.
While this book was a pleasurable read with an accessible writing style, I would caution the reader to acknowledge its context and approach it with a critical perspective. The argument for Data Access mandates and concrete recommendations based on historical and contemporary anecdotes may appeal to the broad audience of academics, individuals working in tech, and policymakers to whom this book caters. However, I hope this does not lead to more technocratic measures that leave out the perspectives of those who have experienced data harm.