Abstract
Afterlives of Data: Life and Debt under Capitalist Surveillance provides a compelling journey into the entangled data economies of health and debt in the United States. Much has been written already on how power relations pervade and drive the data-intensive modern society. Still, Afterlives of Data will not leave the reader unaffected. Like Ebeling’s first book Healthcare and Big Data: Digital Specters and Phantom Objects (2016), the writing style is a masterful combination of narrative storytelling and trenchant critique. This time the focus is on how citizens’ physical and financial health live multiple afterlives, beyond their original use. Afterlives of Data begins and ends with the story of Ana, a tragic example of the fate of many patients suffering not only from a deadly disease but also from the financial strain of medical debt. Ebeling criticizes that patients like Ana often pay twice. First, patients pay (via taxes, insurances, or co-payments) for the healthcare system that collects their data, and second, they pay the costs of the inequitable returns when their health data serve corporate agendas. Among these is the development of proprietary algorithms or new drugs, products that are based on public data but sold back to patients for profit. The book introduces the reader to a hidden data network affecting what lives can be lived. Like invisible strings controlled by puppet masters, we sense the presence of the data affecting us but never get the full picture. Ebeling sets out to expose some of the powerful puppet masters and nodes of the American data economy, unfolding the backbone structure and the lived experience of the datafied “debt society” (Lazzaretto, 2015).
Chapter 1 takes issue with the conception of data as the basis for neutral “facts” by pointing to the possibilities of using data to construct specific truths for specific interests. Chapter 2 documents this through an analysis of the historical roots of mistrust in data and healthcare authorities in the United States, as well as ethnographic encounters with the complex relations between data and trust in the development of a cross-sector data-sharing consortium. Ebeling expresses how public health researchers, data scientists, and social workers attempt to use data to repair the eroded public trust. This is a positive attempt to make data “do good”, by making socioeconomic barriers to health visible through data. But the researchers are also sometimes confronted with their own concerns about trust in data. For example, they cannot get access to information on how their collected data are processed into de-identified “synthetic data” by data vendors they collaborate with. This raises the broader question of what constitutes trustworthy data and data partnerships.
Chapter 3 continues this discussion with a focus on collaborations between nonprofit healthcare organizations and powerful commercial companies like Google, Amazon, and Experian. Ebeling provides unsettling examples of breaches of confidentiality agreements, and how health data are collected for various purposes that individuals are not aware of nor have consented to. Particularly disturbing is how the uncritical reuse of health data often aggravates problems of discrimination hiding in the datasets used to train algorithms. Similarly, Chapters 4 and 5 describe how expanding forms of “alternative data” are used to “score” individuals on their expected treatment compliance or creditworthiness. It is tempting to think that the best option is to avoid making too many data traces visible. However, as discussed in Chapter 6, data visibility impacts the possibilities that are open to individuals. Ebeling illustrates this through experiences of how foreign workers or applicants for US citizenship are considered “untrustworthy” by credit reporting companies if they do not have debt or do not make payments with a credit card. In the society portrayed by Ebeling, humans must increasingly conform to the statistical logic of data, as documented through their health and debt trajectories. The book concludes with the gloomy outlook that there is no escape from data profiling, and “the best that one can do is to hope not to be plucked out of the aggregate by late capital’s vultures and predators” (p.154).
Afterlives of Data takes us important steps further in uncovering the symptoms of the financial toxicity of “surveillance capitalism” (Zuboff, 2019). It is an important read for anyone concerned about the future of healthcare and democracy. The book does, however, miss some opportunities for a more precise diagnosis of the societal disease and a discussion of possible treatment options. While the dystopian storyline of the book beautifully captures the suffering and despair of those exposed to injustices, many examples leave the reader wondering about the concrete motivations and mechanisms behind the specific problems outlined. What mechanisms and business models have made it possible for commercial companies like Amazon and Google to become disruptive healthcare developers? How, concretely, are data used to open or close doors for patients like Ana? Ebeling stresses that mistrust is “baked into” the US regulations and laws for data protection by not allowing the individual to consent to how data are collected and reused (pp.63–64). However, the book leaves it unclear whether individual control over data is the most critically lacking ingredient or the most adequate solution to the problem. Reading the book from the perspective of a European welfare state, informed consent is not always necessary (nor sufficient) for public trust in data sharing. A comparative perspective, spanning both positive and problematic examples of data infrastructures and data uses, might serve as a prism to highlight the main causes of the identified problems. From this perspective, the main target of Ebeling’s critique appears to be the specific entanglement of the data economy and the capitalist structure of the American healthcare system. Acknowledgment of the benefits of data is also important for understanding the impact of “persuasive technologies” by Big Tech. Despite the public scandals, many of us consent to data collection, user profiling, and targeted marketing in return for free access to search and social media platforms. The strings pulled by the data networks are often seamless or can be experienced as empowering as well as disempowering, making the thin line between user benefits and exploitation difficult to see or manage at the individual level. This calls for more explicit discussion of what forms and levels of regulation could mitigate the negative effects of datafied capitalism.
Afterlives of Data is an original and important contribution to the discussion about how the expanding network of data reuses affects our lives. The book is a powerful awakening from the gaslighting technique of corporate justifications that call for “data altruism” while using data in ways that are not in alignment with the interests of citizens. By exposing the power asymmetries and uneven distribution of benefits, this book brings to question the compatibility of political visions to “democratize” health data and the increasing reliance on (and support of) proprietary platforms and algorithms. These questions are relevant not only to readers interested in US politics, but to anyone concerned about how current business models of the global data economy impact democracy, healthcare, and our everyday life.
