Datafication, Identity, and the Reorganization of the Category Individual

Curated on Posted on by Stefaan Verhulst

Paper by Juan Ortiz Freuler: “A combination of political, sociocultural, and technological shifts suggests a change in the way we understand human rights. Undercurrents fueling this process are digitization and datafication. Through this process of change, categories that might have been cornerstones of our past and present might very well become outdated. A key category that is under pressure is that of the individual. Since datafication is typically accompanied by technologies and processes aimed at segmenting and grouping, such groupings become increasingly relevant at the expense of the notion of the individual. This concept might become but another collection of varied characteristics, a unit of analysis that is considered at times too broad—and at other times too narrow—to be considered relevant or useful by the systems driving our key economic, social, and political processes.

This Essay provides a literature review and a set of key definitions linking the processes of digitization, datafication, and the concept of the individual to existing conceptions of individual rights. It then presents a framework to dissect and showcase the ways in which current technological developments are putting pressure on our existing conceptions of the individual and individual rights…(More)”.

What prevents us from reusing medical real-world data in research

Curated on Posted on by Stefaan Verhulst

Paper by Julia Gehrmann, Edit Herczog, Stefan Decker & Oya Beyan: “Recent studies show that Medical Data Science (MDS) carries great potential to improve healthcare. Thereby, considering data from several medical areas and of different types, i.e. using multimodal data, significantly increases the quality of the research results. On the other hand, the inclusion of more features in an MDS analysis means that more medical cases are required to represent the full range of possible feature combinations in a quantity that would be sufficient for a meaningful analysis. Historically, data acquisition in medical research applies prospective data collection, e.g. in clinical studies. However, prospectively collecting the amount of data needed for advanced multimodal data analyses is not feasible for two reasons. Firstly, such a data collection process would cost an enormous amount of money. Secondly, it would take decades to generate enough data for longitudinal analyses, while the results are needed now. A worthwhile alternative is using real-world data (RWD) from clinical systems of e.g. university hospitals. This data is immediately accessible in large quantities, providing full flexibility in the choice of the analyzed research questions. However, when compared to prospectively curated data, medical RWD usually lacks quality due to the specificities of medical RWD outlined in section 2. The reduced quality makes its preparation for analysis more challenging…(More)”.

Data-driven research and healthcare: public trust, data governance and the NHS

Curated on Posted on by Stefaan Verhulst

Paper by Angeliki Kerasidou & Charalampia (Xaroula) Kerasidou: “It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is reported distrust in this domain. Although in the UK, the NHS is one of the most trusted public institutions, public trust does not appear to accompany its data sharing practices for research and innovation, specifically with the private sector, that have been introduced in recent years. In this paper, we examine the question of, what is it about sharing NHS data for research and innovation with for-profit companies that challenges public trust? To address this question, we draw from political theory to provide an account of public trust that helps better understand the relationship between the public and the NHS within a democratic context, as well as, the kind of obligations and expectations that govern this relationship. Then we examine whether the way in which the NHS is managing patient data and its collaboration with the private sector fit under this trust-based relationship. We argue that the datafication of healthcare and the broader ‘health and wealth’ agenda adopted by consecutive UK governments represent a major shift in the institutional character of the NHS, which brings into question the meaning of public good the NHS is expected to provide, challenging public trust. We conclude by suggesting that to address the problem of public trust, a theoretical and empirical examination of the benefits but also the costs associated with this shift needs to take place, as well as an open conversation at public level to determine what values should be promoted by a public institution like the NHS….(More)”.

Setting data free: The politics of open data for food and agriculture

Curated on Posted on by Stefaan Verhulst

Paper by M. Fairbairn, and Z. Kish: “Open data is increasingly being promoted as a route to achieve food security and agricultural development. This article critically examines the promotion of open agri-food data for development through a document-based case study of the Global Open Data for Agriculture and Nutrition (GODAN) initiative as well as through interviews with open data practitioners and participant observation at open data events. While the concept of openness is striking for its ideological flexibility, we argue that GODAN propagates an anti-political, neoliberal vision for how open data can enhance agricultural development. This approach centers values such as private innovation, increased production, efficiency, and individual empowerment, in contrast to more political and collectivist approaches to openness practiced by some agri-food social movements. We further argue that open agri-food data projects, in general, have a tendency to reproduce elements of “data colonialism,” extracting data with minimal consideration for the collective harms that may result, and embedding their own values within universalizing information infrastructures…(More)”.

Digital divides are lower in Smart Cities

Curated on Posted on by Stefaan Verhulst

Paper by Andrea Caragliu and Chiara F. Del Bo: “Ever since the emergence of digital technologies in the early 1990s, the literature has discussed the potential pitfalls of an uneven distribution of e-skills under the umbrella of the digital divide. To provide a definition of the concept, “Lloyd Morrisett coined the term digital divide to mean “a discrepancy in access to technology resources between socioeconomic groups” (Robyler and Doering, 2014, p. 27)”

Despite digital divide being high on the policy agenda, statistics suggest the persisting relevance of this issue. For instance, focusing on Europe, according to EUROSTAT statistics, in 2021 about 90 per cent of people living in Zeeland, a NUTS2 region in the Netherlands, had ordered at least once in their life goods or services over the internet for private use, against a minimum in the EU27 of 15 per cent (in the region of Yugoiztochen, in Bulgaria). In the same year, while basically all (99 per cent) interviewees in the NUTS2 region of Northern and Western Ireland declared using the internet at least once a week, the same statistic drops to two thirds of the sample in the Bulgarian region of Severozapaden. While over time these territorial divides are converging, they can still significantly affect the potential positive impact of the diffusion of digital technologies.

Over the past three years, the digital divide has been made dramatically apparent by the COVID-19 pandemic outbreak. When, during the first waves of full lockdowns enacted in most Countries, tertiary and schooling activities were moved online, many economic outcomes showed significant worsening. Among these, learning outcomes in pupils and service sectors’ productivity were particularly affected.

A simultaneous development in the scientific literature has discussed the attractive features of planning and managing cities ‘smartly’. Smart Cities have been initially identified as urban areas with a tendency to invest and deploy ICTs. More recently, this notion also started to encompass the context characteristics that make a city capable of reaping the benefits of ICTs – social and human capital, soft and hard institutions.

While mounting empirical evidence suggests a superior economic performance of Cities ticking all these boxes, the Smart City movement did not come without critiques. The debate on urban smartness as an instrument for planning and managing more efficient cities has been recently positing that Smart Cities could be raising inequalities. This effect would be due to the role of driver of smart urban transformations played by multinational corporations, who, in a dystopic view, would influence local policymakers’ agendas.

Given these issues, and our own research on Smart Cities, we started asking ourselves whether the risks of increasing inequalities associated with the Smart City model were substantiated. To this end, we focused on empirically verifying whether cities moving forward along the smart city model were facing increases in income and digital inequalities. We answered the first question in Caragliu and Del Bo (2022), and found compelling evidence that smart city characteristics actually decrease income inequalities…(More)”.

A new way to look at data privacy

Curated on Posted on by Stefaan Verhulst

Article by Adam Zewe: “Imagine that a team of scientists has developed a machine-learning model that can predict whether a patient has cancer from lung scan images. They want to share this model with hospitals around the world so clinicians can start using it in diagnosis.

But there’s a problem. To teach their model how to predict cancer, they showed it millions of real lung scan images, a process called training. Those sensitive data, which are now encoded into the inner workings of the model, could potentially be extracted by a malicious agent. The scientists can prevent this by adding noise, or more generic randomness, to the model that makes it harder for an adversary to guess the original data. However, perturbation reduces a model’s accuracy, so the less noise one can add, the better.

MIT researchers have developed a technique that enables the user to potentially add the smallest amount of noise possible, while still ensuring the sensitive data are protected.

The researchers created a new privacy metric, which they call Probably Approximately Correct (PAC) Privacy, and built a framework based on this metric that can automatically determine the minimal amount of noise that needs to be added. Moreover, this framework does not need knowledge of the inner workings of a model or its training process, which makes it easier to use for different types of models and applications.

In several cases, the researchers show that the amount of noise required to protect sensitive data from adversaries is far less with PAC Privacy than with other approaches. This could help engineers create machine-learning models that provably hide training data, while maintaining accuracy in real-world settings…

A fundamental question in data privacy is: How much sensitive data could an adversary recover from a machine-learning model with noise added to it?

Differential Privacy, one popular privacy definition, says privacy is achieved if an adversary who observes the released model cannot infer whether an arbitrary individual’s data is used for the training processing. But provably preventing an adversary from distinguishing data usage often requires large amounts of noise to obscure it. This noise reduces the model’s accuracy.

PAC Privacy looks at the problem a bit differently. It characterizes how hard it would be for an adversary to reconstruct any part of randomly sampled or generated sensitive data after noise has been added, rather than only focusing on the distinguishability problem…(More)”

Questions as a Device for Data Responsibility: Toward a New Science of Questions to Steer and Complement the Use of Data Science for the Public Good in a Polycentric Way

Curated on Posted on by Stefaan Verhulst

Paper by Stefaan G. Verhulst: “We are at an inflection point today in our search to responsibly handle data in order to maximize the public good while limiting both private and public risks. This paper argues that the way we formulate questions should be given more consideration as a device for modern data responsibility. We suggest that designing a polycentric process for co-defining the right questions can play an important role in ensuring that data are used responsibly, and with maximum positive social impact. In making these arguments, we build on two bodies of knowledge—one conceptual and the other more practical. These observations are supplemented by the author’s own experience as founder and lead of “The 100 Questions Initiative.” The 100 Questions Initiative uses a unique participatory methodology to identify the world’s 100 most pressing, high-impact questions across a variety of domains—including migration, gender inequality, air quality, the future of work, disinformation, food sustainability, and governance—that could be answered by unlocking datasets and other resources. This initiative provides valuable practical insights and lessons into building a new “science of questions” and builds on theoretical and practical knowledge to outline a set of benefits of using questions for data responsibility. More generally, this paper argues that, combined with other methods and approaches, questions can help achieve a variety of key data responsibility goals, including data minimization and proportionality, increasing participation, and enhancing accountability…(More)”.

What types of health evidence persuade actors in a complex policy system?

Curated on Posted on by Stefaan Verhulst

Article by Geoff Bates, Sarah Ayres, Andrew Barnfield, and Charles Larkin: “Good quality urban environments can help to prevent non-communicable diseases such as cardiovascular diseases, mental health conditions and diabetes that account for three quarters of deaths globally (World Health Organisation, 2022). More commonly however, poor quality living conditions contribute to poor health and widening inequalities (Adlakha & John, 2022). Consequently, many public health advocates hope to convince and bring together the stakeholders who shape urban development to help create healthier places.

Evidence is one tool that can be used to convince these stakeholders from outside the health sector to think more about health outcomes. Most of the literature on the use of evidence in policy environments has focused on the public sector, such as politicians and civil servants (e.g., Crow & Jones, 2018). However, urban development decision-making processes involve many stakeholders across sectors with different needs and agendas (Black et al., 2021). While government sets policy and regulatory frameworks, private sector organisations such as property developers and investors drive urban development and strongly influence policy agendas.

In our article recently published in Policy & Politics, What types of evidence persuade actors in a complex policy system?, we explore the use of evidence to influence different groups across the urban development system to think more about health outcomes in their decisions…

The key findings of the research were that:

  1. Evidence-based narratives have wide appeal. Narratives based on real-world and lived experiences help stakeholders to form an emotional connection with evidence and are effective for drawing attention to health problems. Powerful outcomes such as child health and mortality data are particularly persuasive. This builds on literature promoting the use of storytelling approaches for public sector actors by demonstrating its applicability within the private and third sectors….(More)”

Design in the Civic Space: Generating Impact in City Government

Curated on Posted on by Stefaan Verhulst

Paper by Stephanie Wade and Jon Freach: “When design in the private sector is used as a catalyst for innovation, it can produce insight into human experience, awareness of equitable and inequitable conditions, and clarity about needs and wants. But when we think of applying design in a government complex, the complicated nature of the civic arena means that public servants need to learn and apply design in ways that are specific to the intricate and expansive ecosystem of long-standing social challenges they face, and learn new mindsets, methods, and ways of working that challenge established practices in a bureaucratic environment. Design offers tools to help navigate the ambiguous boundaries of these complex problems and improve the city’s organizational culture so that it delivers better services to residents and the communities in which they live.

For the new practitioner in government, design can seem exciting, inspiring, hopeful, and fun because over the past decade it has quickly become a popular and novel way to approach city policy and service design. In the early part of the learning process, people often report that using design helps visualize their thoughts, spark meaningful dialogue, and find connections between problems, data, and ideas. But for some, when the going gets tough—when the ambiguity of overlapping and long-standing complex civic problems, a large number of stakeholders, causes, and effects begin to surface—design practices can seem slow and confusing.

In this article we explore the growth and impact of using design in city government and best practices when introducing it into city hall to tackle complex civic sector challenges along with the highs and lows of using design in local government to help cities innovate. The authors, who have worked together to conceive, create, and deliver design training to over 100 global cities, the US federal government, and higher education, share examples from their fieldwork supported by the experiences of city staff members who have applied design methods in their jobs….(More)”.

Just Citation

Curated on Posted on by Stefaan Verhulst

Paper by Amanda Levendowski: “Contemporary citation practices are often unjust. Data cartels, like Google, Westlaw, and Lexis, prioritize profits and efficiency in ways that threaten people’s autonomy, particularly that of pregnant people and immigrants. Women and people of color have been legal scholars for more than a century, yet colleagues consistently under-cite and under-acknowledge their work. Other citations frequently lead to materials that cannot be accessed by disabled people, poor people or the public due to design, paywalls or link rot. Yet scholars and students often understand citation practices as “just” citation and perpetuate these practices unknowingly. This Article is an intervention. Using an intersectional feminist framework for understanding how cyberlaws oppress and liberate oppressed, an emerging movement known as feminist cyberlaw, this Article investigates problems posed by prevailing citation practices and introduces practical methods that bring citation into closer alignment with the feminist values of safety, equity, and accessibility. Escaping data cartels, engaging marginalized scholars, embracing free and public resources, and ensuring that those resources remain easily available represent small, radical shifts that promote just citation. This Article provides powerful, practical tools for pursuing all of them…(More)”.