Stefaan Verhulst
Alex Hern at The Guardian: “A transatlantic divide on how to use location data to fight coronavirus risks highlights the lack of safeguards for Americans’ personal data, academics and data scientists have warned.
The US Centers for Disease Control and Prevention (CDC) has turned to data provided by the mobile advertising industry to analyse population movements in the midst of the pandemic.
Owing to a lack of systematic privacy protections in the US, data collected by advertising companies is often extremely detailed: companies with access to GPS location data, such as weather apps or some e-commerce sites, have been known to sell that data on for ad targeting purposes. That data provides much more granular information on the location and movement of individuals than the mobile network data received by the UK government from carriers including O2 and BT.
While both datasets track individuals at the collection level, GPS data is accurate to within five metres, according to Yves-Alexandre de Montjoye, a data scientist at Imperial College, while mobile network data is accurate to 0.1km² in city centres and much less in less dense areas – the difference between locating an individual to their street and to a specific room in their home…
But, warns de Montjoye, such data is never truly anonymous. “The original data is pseudonymised, yet it is quite easy to reidentify someone. Knowing where someone was is enough to reidentify them 95% of the time, using mobile phone data. So there’s the privacy concern: you need to process the pseudonymised data, but the pseudonymised data can be reidentified. Most of the time, if done properly, the aggregates are aggregated, and cannot be de-anonymised.”
The data scientist points to successful attempts to use location data in tracking outbreaks of malaria in Kenya or dengue in Pakistan as proof that location data has use in these situations, but warns that trust will be hurt if data collected for modelling purposes is then “surreptitiously used to crack down on individuals not respecting quarantines or kept and used for unrelated purposes”….(More)”.
Book by Adam Kucharski: “From ideas and infections to financial crises and “fake news,” why the science of outbreaks is the science of modern life.
These days, whenever anything spreads, whether it’s a YouTube fad or a political rumor, we say it went viral. But how does virality actually work? In The Rules of Contagion, epidemiologist Adam Kucharski explores topics including gun violence, online manipulation, and, of course, outbreaks of disease to show how much we get wrong about contagion, and how astonishing the real science is.
Why did the president retweet a Mussolini quote as his own? Why do financial bubbles take off so quickly? Why are disinformation campaigns so effective? And what makes the emergence of new illnesses–such as MERS, SARS, or the coronavirus disease COVID-19–so challenging? By uncovering the crucial factors driving outbreaks, we can see how things really spread — and what we can do about it….(More)”.
Blog post by Stefaan Verhulst: “We live in almost unimaginable times. The spread of COVID-19 is a human tragedy and global crisis that will impact our communities for many years to come. The social and economic costs are huge and mounting, and they are already contributing to a global slowdown. Every day, the emerging pandemic reveals new vulnerabilities in various aspects of our economic, political and social lives. These include our vastly overstretched public health services, our dysfunctional political climate, and our fragile global supply chains and financial markets.
The unfolding crisis is also making shortcomings clear in another area: the way we re-use data responsibly. Although this aspect of the crisis has been less remarked upon than other, more obvious failures, those who work with data—and who have seen its potential to impact the public good—understand that we have failed to create the necessary governance and institutional structures that would allow us to harness data responsibly to halt or at least limit this pandemic. A recent article in Stat, an online journal dedicated to health news, characterized the COVID-19 outbreak as “a once-in-a-century evidence fiasco.” The article continues:
“At a time when everyone needs better information, […] we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.”
It doesn’t have to be this way, and these data challenges are not an excuse for inaction. As we explain in what follows, there is ample evidence that the re-use of data can help mitigate health pandemics. A robust (if somewhat unsystematized) body of knowledge could direct policymakers and others in their efforts. In the second part of this article, we outline eight steps that key stakeholders can and should take to better re-use data in the fight against COVID-19. In particular, we argue that more responsible data stewardship and increased use of data collaboratives are critical….(More)”.
Paper by Nuria Oliver, et al: “This paper describes how mobile phone data can guide government and public health authorities in determining the best course of action to control the COVID-19 pandemic and in assessing the effectiveness of control measures such as physical distancing. It identifies key gaps and reasons why this kind of data is only scarcely used, although their value in similar epidemics has proven in a number of use cases. It presents ways to overcome these gaps and key recommendations for urgent action, most notably the establishment of mixed expert groups on national and regional level, and the inclusion and support of governments and public authorities early on. It is authored by a group of experienced data scientists, epidemiologists, demographers and representatives of mobile network operators who jointly put their work at the service of the global effort to combat the COVID-19 pandemic….(More)”.
GDPR Hub: “The sudden outbreak of cases of COVID-19-afflictions (“Corona-Virus”), which was declared a pandemic by the WHO affects data protection in various ways. Different data protection authorities published guidelines for employers and other parties involved in the processing of data related to the Corona-Virus (read more below).
The Corona-Virus has also given cause to the use of different technologies based on data collection and other data processing activities by the EU/EEA member states and private companies. These processing activities mostly focus on preventing and slowing the further spreading of the Corona-Virus and on monitoring the citizens’ abidance with governmental measures such as quarantine. Some of them are based on anonymous or anonymized data (like for statistics or movement patterns), but some proposals also revolved around personalized tracking.
At the moment, it is not easy to figure out, which processing activities are actually supposed to be conducted and which are only rumors. This page will therefore be adapted once certain processing activities have been confirmed. For now, this article does not assess the lawfulness of particular processing activities, but rather outlines the general conditions for data processing in connection with the Corona-Virus.
It must be noted that several activities – such as monitoring, if citizens comply with quarantine and stay indoors by watching at mobile phone locations – can be done without having to use personal data under Article 4(1) GDPR, if all necessary information can be derived from anonymised data. The GDPR does not apply to activities that only rely on anonymised data….(More)”.
Chapter by Oran Doyle and Rachael Walsh: “Populisms come in different forms, but all involve a political rhetoric that invokes the will of a unitary people to combat perceived constraints, whether economic, legal, or technocratic. In this chapter, our focus is democratic backsliding aided by populist rhetoric. Some have suggested deliberative democracy as a means to combat this form of populism. Deliberative democracy encourages and facilitates both consultation and contestation, emphasizing plurality of voices, the legitimacy of disagreement, and the imperative of reasoned persuasion. Its participatory and inclusive character has the potential to undermine the credibility of populists’ claims to speak for a unitary people. Ireland has been widely referenced in constitutionalism’s deliberative turn, given its recent integration of deliberative mini-publics into the constitutional amendment process.
Reviewing the Irish experience, we suggest that deliberative mini-publics are unlikely to reverse democratic backsliding. Populist rhetoric is fueled by the very measures intended to combat democratic backsliding: enhanced constitutional constraints merely illustrate how the will of the people is being thwarted. The virtues of Ireland’s experiment in deliberative democracy — citizen participation, integration with representative democracy, deliberation, balanced information, expertise — have all been criticized in ways that are at least consistent with populist narratives. The failure of such narratives to take hold in Ireland, we suggest, may be due to a political system that is already resistant to populist rhetoric, as well as a tradition of participatory constitutionalism. The experiment with deliberative mini-publics may have strengthened Ireland’s constitutional culture by reinforcing anti-populist features. But it cannot be assumed that this experience would be replicated in larger countries polarized along political, ethnic, or religious lines….(More)”.
Article by Jeni Tennison: “Studying the past is futile in an unprecedented crisis. Science is the answer – and open-source information is paramount…Data is a necessary ingredient in day-to-day decision-making – but in this rapidly evolving situation, it’s especially vital. Everything has changed, almost overnight. Demands for food, transport, and energy have been overhauled as more people stop travelling and work from home. Jobs have been lost in some sectors, and workers are desperately needed in others. Historic experience can no longer tell us how our society or economy is working. Past models hold little predictive power in an unprecedented situation. To know what is happening right now, we need up-to-date information….
This data is also crucial for scientists, who can use it to replicate and build upon each other’s work. Yet no open data has been published alongside the evidence for the UK government’s coronavirus response. While a model that informed the US government’s response is freely available as a Google spreadsheet, the Imperial College London model that prompted the current lockdown has still not been published as open-source code. Making data open – publishing it on the web, in spreadsheets, without restrictions on access – is the best way to ensure it can be used by the people who need it most.
There is currently no open data available on UK hospitalisation rates; no regional, age or gender breakdown of daily deaths. The more granular breakdown of registered deaths provided by the Office of National Statistics is only published on a weekly basis, and with a delay. It is hard to tell whether this data does not exist or the NHS has prioritised creating dashboards for government decision makers rather than informing the rest of the country. But the UK is making progress with regard to data: potential Covid-19 cases identified through online and call-centre triage are now being published daily by NHS Digital.
Of course, not all data should be open. Singapore has been publishing detailed data about every infected person, including their age, gender, workplace, where they have visited and whether they had contact with other infected people. This can both harm the people who are documented and incentivise others to lie to authorities, undermining the quality of data.
When people are concerned about how data about them is handled, they demand transparency. To retain our trust, governments need to be open about how data is collected and used, how it’s being shared, with whom, and for what purpose. Openness about the use of personal data to help tackle the Covid-19 crisis will become more pressing as governments seek to develop contact tracing apps and immunity passports….(More)”.
Paper by Nora Milotay and Gianluca Sgueo: “Humans are among the many living species capable of collaborative and imaginative thinking. While it is widely agreed among scholars that this capacity has contributed to making humans the dominant species, other crucial questions remain open to debate. Is it possible to encourage large groups of people to engage in collective thinking? Is it possible to coordinate citizens to find solutions to address global challenges? Some scholars claim that large groups of independent, motivated, and well-informed people can, collectively, make better decisions than isolated individuals can – what is known as ‘collective intelligence.’
The social dimension of collective intelligence mainly relates to social aspects of the economy and of innovation. It shows that a holistic approach to innovation – one that includes not only technological but also social aspects – can greatly contribute to the EU’s goal of promoting a just transition for everyone to a sustainable and green economy in the digital age. The EU has been taking concrete action to promote social innovation by supporting the development of its theory and practice. Mainly through funding programmes, it helps to seek new types of partners and build new capacity – and thus shape the future of local and national innovations aimed at societal needs.
The democratic dimension suggests that the power of the collective can be leveraged so as to improve public decision-making systems. Supported by technology, policy-makers can harness the ‘civic surplus’ of citizens – thus providing smarter solutions to regulatory challenges. This is particularly relevant at EU level in view of the planned Conference on the Future of Europe, aimed at engaging communities at large and making EU decision-making more inclusive and participatory.
The current coronavirus crisis is likely to change society and our economy in ways as yet too early to predict, but recovery after the crisis will require new ways of thinking and acting to overcome common challenges, and thus making use of our collective intelligence should be more urgent than ever. In the longer term, in order to mobilise collective intelligence across the EU and to fully exploit its innovative potential, the EU needs to strengthen its education policies and promote a shared understanding of a holistic approach to innovation and of collective intelligence – and thus become a ‘global brain,’ with a solid institutional set-up at the centre of a subsidised experimentation process that meets the challenges imposed by modernday transformations…(More)”.
Paper by Stephane Luchini et al:” The radical uncertainty around the current COVID19 pandemics requires that governments around the world should be able to track in real time not only how the virus spreads but, most importantly, what policies are effective in keeping the spread of the disease under check. To improve the quality of health decision-making, we argue that it is necessary to monitor and compare acceleration/deceleration of confirmed cases over health policy responses, across countries. To do so, we provide a simple mathematical tool to estimate the convexity/concavity of trends in epidemiological surveillance data. Had it been applied at the onset of the crisis, it would have offered more opportunities to measure the impact of the policies undertaken in different Asian countries, and to allow European and North-American governments to draw quicker lessons from these Asian experiences when making policy decisions. Our tool can be especially useful as the epidemic is currently extending to lower-income African and South American countries, some of which have weaker health systems….(More)”.
Article by Jessica Kent: “Clinical data should be treated as a public good when used for research or artificial intelligence algorithm development, so long as patients’ privacy is protected, according to a report from the Radiological Society of North America (RSNA).
As artificial intelligence and machine learning are increasingly applied to medical imaging, bringing the potential for streamlined analysis and faster diagnoses, the industry still lacks a broad consensus on an ethical framework for sharing this data.
“Now that we have electronic access to clinical data and the data processing tools, we can dramatically accelerate our ability to gain understanding and develop new applications that can benefit patients and populations,” said study lead author David B. Larson, MD, MBA, from the Stanford University School of Medicine. “But unsettled questions regarding the ethical use of the data often preclude the sharing of that information.”
To offer solutions around data sharing for AI development, RSNA developed a framework that highlights how to ethically use patient data for secondary purposes.
“Medical data, which are simply recorded observations, are acquired for the purposes of providing patient care,” Larson said….(More)”