China Data Flows and Power in the Era of Chinese Big Tech

Curated on Posted on by Stefaan Verhulst

Paper by W. Gregory Voss and Emmanuel Pernot-Leplay: “Personal data have great economic interest today and their possession and control are the object of geopolitics, leading to their regulation by means that vary dependent on the strategic objectives of the jurisdiction considered. This study fills a gap in the literature in this area by analyzing holistically the regulation of personal data flows both into and from China, the world’s second largest economy. In doing so, it focuses on laws and regulations of three major power blocs: the United States, the European Union, and China, seen within the framework of geopolitics, and considering the rise of Chinese big tech.

First, this study analyzes ways that the United States—the champion of the free-flow of data that has helped feed the success of the Silicon Valley system—has in specific cases prevented data flows to China on grounds of individual data protection and national security. The danger of this approach and alternate protection through potential U.S. federal data privacy legislation are evoked. Second, the cross-border data flow restriction of the European Union’s General Data Protection Regulation (GDPR) is studied in the context of data exports to China, including where the data transit via the United States prior to their transfer to China. Next, after review of the conditions for a European Commission adequacy determination and an examination of recent data privacy legislation in China, the authors provide a preliminary negative assessment of the potential for such a determination for China, where government access is an important part of the picture. Difficult points are highlighted for investigation by data exporters to China, when relying on EU transfer mechanisms, following the Schrems II jurisprudence.

Finally, recent Chinese regulations establishing requirements for the export of data are studied. In this exercise, light is shed on compliance requirements for companies under Chinese law, provisions of Chinese data transfer regulations that are similar to the those of the GDPR, and aspects that show China’s own approach to restrictions on data transfers, such as an emphasis on national security protection. This study concludes with the observation that restrictions for data flows both into and out of China will continue and potentially be amplified, and economic actors will need to prepare themselves to navigate the relevant regulations examined in this study….(More)”.

The pandemic veneer: COVID-19 research as a mobilisation of collective intelligence by the global research community

Curated on Posted on by Stefaan Verhulst

Paper by Daniel W Hook and James R Wilsdon: “The global research community responded with speed and at scale to the emergence of COVID-19, with around 4.6% of all research outputs in 2020 related to the pandemic. That share almost doubled through 2021, to reach 8.6% of research outputs. This reflects a dramatic mobilisation of global collective intelligence in the face of a crisis. It also raises fundamental questions about the funding, organisation and operation of research. In this Perspective article, we present data that suggests that COVID-19 research reflects the characteristics of the underlying networks from which it emerged, and on which it built. The infrastructures on which COVID-19 research has relied – including highly skilled, flexible research capacity and collaborative networks – predated the pandemic, and are the product of sustained, long-term investment. As such, we argue that COVID-19 research should not be viewed as a distinct field, or one-off response to a specific crisis, but as a ‘pandemic veneer’ layered on top of longstanding interdisciplinary networks, capabilities and structures. These infrastructures of collective intelligence need to be better understood, valued and sustained as crucial elements of future pandemic or crisis response…(More)”.

A shift in paradigm? Collaborative public administration in the context of national digitalization strategies

Curated on Posted on by Stefaan Verhulst

Paper by Gerhard Hammerschmid, Enora Palaric, Maike Rackwitz, and Kai Wegrich: “Despite claims of a paradigmatic shift toward the increased role of networks and partnerships as a form of governance—driven and enabled by digital technologies—the relation of “Networked Governance” with the pre-existing paradigms of “Traditional Weberian Public Administration” and “New Public Management” remains relatively unexplored. This research aims at collecting systematic evidence on the dominant paradigms in digitalization reforms in Europe by comparing the doctrines employed in the initial and most recent digitalization strategies across eight European countries: Estonia, France, Germany, Italy, The Netherlands, Norway, Spain, and the United Kingdom. We challenge the claim that Networked Governance is emerging as the dominant paradigm in the context of the digitalization of the public sector. The findings confirm earlier studies indicating that information and communication technologies tend to reinforce some traditional features of administration and the recentralization of power. Furthermore, we find evidence of the continued importance of key features of “New Public Management” in the digital era…(More)”.

To harness telecom data for good, there are six challenges to overcome

Curated on Posted on by Stefaan Verhulst

Blog by Anat Lewin and Sveta Milusheva: “The global use of mobile phones generates a vast amount of data. What good can be done with these data? During the COVID-19 pandemic, we saw that aggregated data from mobile phones can tell us where groups of humans are going, how many of them are there, and how they are behaving as a cluster. When used effectively and responsibly, mobile phone data can be immensely helpful for development work and emergency response — particularly in resource-constrained countries.  For example, an African country that had, in recent years, experienced a cholera outbreak was ahead of the game. Since the legal and practical agreements were already in place to safely share aggregated mobile data, accessing newer information to support epidemiological modeling for COVID-19 was a straightforward exercise. The resulting datasets were used to produce insightful analyses that could better inform health, lockdown, and preventive policy measures in the country.

To better understand such challenges and opportunities, we led an effort to access and use anonymized, aggregated mobile phone data across 41 countries. During this process, we identified several recurring roadblocks and replicable successes, which we summarized in a paper along with our lessons learned. …(More)”.

Professional expertise in Policy Advisory Systems: How administrators and consultants built Behavioral Insights in Danish public agencies

Curated on Posted on by Stefaan Verhulst

Paper by Jakob Laage-Thomsen: “Recent work on consultants and academics in public policy has highlighted their transformational role. The paper traces how, in the absence of an explicit government strategy, external advisors establish different organizational arrangements to build Behavioral Insights in public agencies as a new form of administrative expertise. This variation shows the importance of the politico-administrative context within which external advisors exert influence. The focus on professional expertise adds to existing understandings of ideational compatibility in contemporary Policy Advisory Systems. Inspired by the Sociology of Professions, expertise is conceptualized as professionally constructed sets of diagnosis, inference, and treatment. The paper compares four Danish governmental agencies since 2010, revealing the central roles external advisors play in facilitating new policy ideas and diffusing new forms of expertise. This has implications for how we think of administrative expertise in contemporary bureaucracies, and the role of external advisors in fostering new forms of expertise….(More)”.

The Law of AI for Good

Curated on Posted on by Stefaan Verhulst

Paper by Orly Lobel: “Legal policy and scholarship are increasingly focused on regulating technology to safeguard against risks and harms, neglecting the ways in which the law should direct the use of new technology, and in particular artificial intelligence (AI), for positive purposes. This article pivots the debates about automation, finding that the focus on AI wrongs is descriptively inaccurate, undermining a balanced analysis of the benefits, potential, and risks involved in digital technology. Further, the focus on AI wrongs is normatively and prescriptively flawed, narrowing and distorting the law reforms currently dominating tech policy debates. The law-of-AI-wrongs focuses on reactive and defensive solutions to potential problems while obscuring the need to proactively direct and govern increasingly automated and datafied markets and societies. Analyzing a new Federal Trade Commission (FTC) report, the Biden administration’s 2022 AI Bill of Rights and American and European legislative reform efforts, including the Algorithmic Accountability Act of 2022, the Data Privacy and Protection Act of 2022, the European General Data Protection Regulation (GDPR) and the new draft EU AI Act, the article finds that governments are developing regulatory strategies that almost exclusively address the risks of AI while paying short shrift to its benefits. The policy focus on risks of digital technology is pervaded by logical fallacies and faulty assumptions, failing to evaluate AI in comparison to human decision-making and the status quo. The article presents a shift from the prevailing absolutist approach to one of comparative cost-benefit. The role of public policy should be to oversee digital advancements, verify capabilities, and scale and build public trust in the most promising technologies.

A more balanced regulatory approach to AI also illuminates tensions between current AI policies. Because AI requires better, more representative data, the right to privacy can conflict with the right to fair, unbiased, and accurate algorithmic decision-making. This article argues that the dominant policy frameworks regulating AI risks—emphasizing the right to human decision-making (human-in-the-loop) and the right to privacy (data minimization)—must be complemented with new corollary rights and duties: a right to automated decision-making (human-out-of-the-loop) and a right to complete and connected datasets (data maximization). Moreover, a shift to proactive governance of AI reveals the necessity for behavioral research on how to establish not only trustworthy AI, but also human rationality and trust in AI. Ironically, many of the legal protections currently proposed conflict with existing behavioral insights on human-machine trust. The article presents a blueprint for policymakers to engage in the deliberate study of how irrational aversion to automation can be mitigated through education, private-public governance, and smart policy design…(More)”

Contextualizing Datafication in Peru: Insights from a Citizen Data Literacy Project

Curated on Posted on by Stefaan Verhulst

Paper by Katherine Reilly and Marieliv Flores: The pilot data literacy project Son Mis Datos showed volunteers how to leverage Peru’s national data protection law to request access to personal data held by Peruvian companies, and then it showed them how to audit corporate data use based on the results. While this intervention had a positive impact on data literacy, by basing it on a universalist conception of datafication, our work inadvertently reproduced the dominant data paradigm we hoped to challenge. This paper offers a retrospective analysis of Son Mis Datos, and explores the gap between van Dijck’s widely cited theory of datafication, and the reality of our participants’ experiences with datafication and digital transformation on the ground in Peru. On this basis, we suggest an alternative definition of datafication more appropriate to critical scholarship as the transformation of social relations around the uptake of personal data in the coordination of transactions, and propose an alternative approach to data literacy interventions that begins with the experiences of data subjects…(More)”.

How Data Happened: A History from the Age of Reason to the Age of Algorithms

Curated on Posted on by Stefaan Verhulst

Book by Chris Wiggins and Matthew L Jones: “From facial recognition—capable of checking people into flights or identifying undocumented residents—to automated decision systems that inform who gets loans and who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn’t just appear: they are part of a history that goes back centuries, from the census enshrined in the US Constitution to the birth of eugenics in Victorian Britain to the development of Google search.

Expanding on the popular course they created at Columbia University, Chris Wiggins and Matthew L. Jones illuminate the ways in which data has long been used as a tool and a weapon in arguing for what is true, as well as a means of rearranging or defending power. They explore how data was created and curated, as well as how new mathematical and computational techniques developed to contend with that data serve to shape people, ideas, society, military operations, and economies. Although technology and mathematics are at its heart, the story of data ultimately concerns an unstable game among states, corporations, and people. How were new technical and scientific capabilities developed; who supported, advanced, or funded these capabilities or transitions; and how did they change who could do what, from what, and to whom?

Wiggins and Jones focus on these questions as they trace data’s historical arc, and look to the future. By understanding the trajectory of data—where it has been and where it might yet go—Wiggins and Jones argue that we can understand how to bend it to ends that we collectively choose, with intentionality and purpose…(More)”.

Exploring data journalism practices in Africa: data politics, media ecosystems and newsroom infrastructures

Curated on Posted on by Stefaan Verhulst

Paper by Sarah Chiumbu and Allen Munoriyarwa: “Extant research on data journalism in Africa has focused on newsroom factors and the predilections of individual journalists as determinants of the uptake of data journalism on the continent. This article diverts from this literature by examining the slow uptake of data journalism in sub- Saharan Africa through the prisms of non-newsroom factors. Drawing on in-depth interviews with prominent investigative journalists sampled from several African countries, we argue that to understand the slow uptake of data journalism on the continent; there is a need to critique the role of data politics, which encompasses state, market and existing media ecosystems across the continent. Therefore, it is necessary to move beyond newsroom-centric factors that have dominated the contemporary understanding of data journalism practices. A broader, non-newsroom conceptualisation beyond individual journalistic predilections and newsroom resources provides productive clarity on data journalism’s slow uptake on the continent. These arguments are made through the conceptual prisms of materiality, performativity and reflexivity…(More)”.

Ten (not so) simple rules for clinical trial data-sharing

Curated on Posted on by Stefaan Verhulst

Paper by Claude Pellen et al: “Clinical trial data-sharing is seen as an imperative for research integrity and is becoming increasingly encouraged or even required by funders, journals, and other stakeholders. However, early experiences with data-sharing have been disappointing because they are not always conducted properly. Health data is indeed sensitive and not always easy to share in a responsible way. We propose 10 rules for researchers wishing to share their data. These rules cover the majority of elements to be considered in order to start the commendable process of clinical trial data-sharing:

  • Rule 1: Abide by local legal and regulatory data protection requirements
  • Rule 2: Anticipate the possibility of clinical trial data-sharing before obtaining funding
  • Rule 3: Declare your intent to share data in the registration step
  • Rule 4: Involve research participants
  • Rule 5: Determine the method of data access
  • Rule 6: Remember there are several other elements to share
  • Rule 7: Do not proceed alone
  • Rule 8: Deploy optimal data management to ensure that the data shared is useful
  • Rule 9: Minimize risks
  • Rule 10: Strive for excellence…(More)”