How Technology Could Revolutionize Refugee Resettlement

Curated on Posted on by Stefaan Verhulst

Krishnadev Calamur in The Atlantic: “… For nearly 70 years, the process of interviewing, allocating, and accepting refugees has gone largely unchanged. In 1951, 145 countries came together in Geneva, Switzerland, to sign the Refugee Convention, the pact that defines who is a refugee, what refugees’ rights are, and what legal obligations states have to protect them.

This process was born of the idealism of the postwar years—an attempt to make certain that those fleeing war or persecution could find safety so that horrific moments in history, such as the Holocaust, didn’t recur. The pact may have been far from perfect, but in successive years, it was a lifeline to Afghans, Bosnians, Kurds, and others displaced by conflict.

The world is a much different place now, though. The rise of populism has brought with it a concomitant hostility toward immigrants in general and refugees in particular. Last October, a gunman who had previously posted anti-Semitic messages online against HIAS killed 11 worshippers in a Pittsburgh synagogue. Many of the policy arguments over resettlement have shifted focus from humanitarian relief to security threats and cost. The Trump administration has drastically cut the number of refugees the United States accepts, and large parts of Europe are following suit.

If it works, Annie could change that dynamic. Developed at Worcester Polytechnic Institute in Massachusetts, Lund University in Sweden, and the University of Oxford in Britain, the software uses what’s known as a matching algorithm to allocate refugees with no ties to the United States to their new homes. (Refugees with ties to the United States are resettled in places where they have family or community support; software isn’t involved in the process.)

Annie’s algorithm is based on a machine learning model in which a computer is fed huge piles of data from past placements, so that the program can refine its future recommendations. The system examines a series of variables—physical ailments, age, levels of education and languages spoken, for example—related to each refugee case. In other words, the software uses previous outcomes and current constraints to recommend where a refugee is most likely to succeed. Every city where HIAS has an office or an affiliate is given a score for each refugee. The higher the score, the better the match.

This is a drastic departure from how refugees are typically resettled. Each week, HIAS and the eight other agencies that allocate refugees in the United States make their decisions based largely on local capacity, with limited emphasis on individual characteristics or needs….(More)”.

How Ireland’s Citizens’ Assembly helped climate action

Curated on Posted on by Stefaan Verhulst

Blog post by Frances Foley: “..In July 2016, the new government – led by Fine Gael, backed by independents – put forward a bill to establish a national-level Citizens’ Assembly to look at the biggest issues of the day. These included the challenges of an ageing population; the role fixed-term parliaments; referendums; the 8th Amendment on abortion; and climate change.

Citizens from every region, every socio-economic background, each ethnicity and age group and from right across the spectrum of political opinion convened over the course of two weekends between September and November 2017. The issue seemed daunting in scale and complexity, but the participants had been well-briefed and had at their disposal a line up of experts, scientists, advocates and other witnesses who would help them make sense of the material. By the end, citizens had produced a radical series of recommendations which went far beyond what any major Irish party was promising, surprising even the initiators of the process….

As expected, the passage for some of the proposals through the Irish party gauntlet has not been smooth. The 8-hour long debate on increasing the carbon tax, for example, suggests that mixing deliberative and representative democracy still produces conflict and confusion. It is certainly clear that parliaments have to adapt and develop if citizens’ assemblies are ever to find their place in our modern democracies.

But the most encouraging move has been the simple acknowledgement that many of the barriers to implementation lie at the level of governance. The new Climate Action Commission, with a mandate to monitor climate action across government, should act as the governmental guarantor of the vision from the Citizens’ Assembly. Citizens’ proposals have themselves stimulated a review of internal government processes to stop their demands getting mired in party wrangling and government bureaucracy. By their very nature, the success of citizens’ assemblies can also provide an alternative vision of how decisions can be made – and in so doing shame political parties and parliaments into improving their decision-making practices.

Does the Irish Citizens’ Assembly constitute a case of rapid transition? In terms of its breadth, scale and vision, the experiment is impressive. But in terms of speed, deliberative processes are often criticised for being slow, unwieldly and costly. The response to this should be to ask what we’re getting: whilst an Assembly is not the most rapid vehicle for change – most serious processes take several months, if not a couple of years – the results, both in specific outcomes and in cultural or political shifts – can be astounding….

In respect to climate change, this harmony between ends and means is particularly significant. The climate crisis is the most severe collective decision-making challenge of our times, one that demands courage, but also careful thought….(More)”.

Whose Commons? Data Protection as a Legal Limit of Open Science

Curated on Posted on by Stefaan Verhulst

Mark Phillips and Bartha M. Knoppers in the Journal of Law, Medicine and Ethics: “Open science has recently gained traction as establishment institutions have come on-side and thrown their weight behind the movement and initiatives aimed at creation of information commons. At the same time, the movement’s traditional insistence on unrestricted dissemination and reuse of all information of scientific value has been challenged by the movement to strengthen protection of personal data. This article assesses tensions between open science and data protection, with a focus on the GDPR.

Powerful institutions across the globe have recently joined the ranks of those making substantive commitments to “open science.” For example, the European Commission and the NIH National Cancer Institute are supporting large-scale collaborations, such as the Cancer Genome Collaboratory, the European Open Science Cloud, and the Genomic Data Commons, with the aim of making giant stores of genomic and other data readily available for analysis by researchers. In the field of neuroscience, the Montreal Neurological Institute is midway through a novel five-year project through which it plans to adopt open science across the full spectrum of its research. The commitment is “to make publicly available all positive and negative data by the date of first publication, to open its biobank to registered researchers and, perhaps most significantly, to withdraw its support of patenting on any direct research outputs.” The resources and influence of these institutions seem to be tipping the scales, transforming open science from a longstanding aspirational ideal into an existing reality.

Although open science lacks any standard, accepted definition, one widely-cited model proposed by the Austria-based advocacy effort openscienceASAP describes it by reference to six principles: open methodology, open source, open data, open access, open peer review, and open educational resources. The overarching principle is “the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process.” This article adopts this principle as a working definition of open science, with a particular emphasis on open sharing of human data.

As noted above, many of the institutions committed to open science use the word “commons” to describe their initiatives, and the two concepts are closely related. “Medical information commons” refers to “a networked environment in which diverse sources of health, medical, and genomic information on large populations become widely shared resources.” Commentators explicitly link the success of information commons and progress in the research and clinical realms to open science-based design principles such as data access and transparent analysis (i.e., sharing of information about methods and other metadata together with medical or health data).

But what legal, as well as ethical and social, factors will ultimately shape the contours of open science? Should all restrictions be fought, or should some be allowed to persist, and if so, in what form? Given that a commons is not a free-for-all, in that its governing rules shape its outcomes, how might we tailor law and policy to channel open science to fulfill its highest aspirations, such as universalizing practical access to scientific knowledge and its benefits, and avoid potential pitfalls? This article primarily concerns research data, although passing reference is also made to the approach to the terms under which academic publications are available, which are subject to similar debates….(More)”.

There Are Better Ways to Do Democracy

Curated on Posted on by Stefaan Verhulst

Article by Peter Coy: “The Brexit disaster has stained the reputation of direct democracy. The United Kingdom’s trauma began in 2016, when then-Prime Minister David Cameron miscalculated that he could strengthen Britain’s attachment to the European Union by calling a referendum on it. The Leave campaign made unkeepable promises about Brexit’s benefits. Voters spent little time studying the facts because there was a vanishingly small chance that any given vote would make the difference by breaking a tie. Leave won—and Google searches for “What is the EU” spiked after the polls closed.

Brexit is only one manifestation of a global problem. Citizens want elected officials to be as responsive as Uber drivers, but they don’t always take their own responsibilities seriously. This problem isn’t new. America’s Founding Fathers worried that democracy would devolve into mob rule; the word “democracy” appears nowhere in the Declaration of Independence or the Constitution.

While fears about democratic dysfunction are understandable, there are ways to make voters into real participants in the democratic process without giving in to mobocracy. Instead of referendums, which often become lightning rods for extremism, political scientists say it’s better to make voters think like jurors, whose decisions affect the lives and fortunes of others.

Guided deliberation, also known as deliberative democracy, is one way to achieve that. Ireland used it in 2016 and 2017 to help decide whether to repeal a constitutional amendment that banned abortion in most cases. A 99-person Citizens’ Assembly was selected to mirror the Irish population. It met over five weekends to evaluate input from lawyers and obstetricians, pro-life and pro-choice groups, and more than 13,000 written submissions from the public, guided by a chairperson from the Irish supreme court. Together they concluded that the legislature should have the power to allow abortion under a broader set of conditions, a recommendation that voters approved in a 2018 referendum; abortion in Ireland became legal in January 2019.

Done right, deliberative democracy brings out the best in citizens. “My experience shows that some of the most polarising issues can be tackled in this manner,” Louise Caldwell, an Irish assembly member, wrote in a column for the Guardian in January. India’s village assemblies, which involve all the adults in local decision-making, are a form of deliberative democracy on a grand scale. A March article in the journal Science says that “evidence from places such as Colombia, Belgium, Northern Ireland, and Bosnia shows that properly structured deliberation can promote recognition, understanding, and learning.” Even French President Emmanuel Macron has used it, convening a three-month “great debate” to solicit the public’s views on some of the issues raised by the sometimes-violent Yellow Vest movement. On April 8, Prime Minister Edouard Philippe presented one key finding: The French have “zero tolerance” for new taxes…(More)”.

Predictive Big Data Analytics using the UK Biobank Data

Curated on Posted on by Stefaan Verhulst

Paper by Ivo D Dinov et al: “The UK Biobank is a rich national health resource that provides enormous opportunities for international researchers to examine, model, and analyze census-like multisource healthcare data. The archive presents several challenges related to aggregation and harmonization of complex data elements, feature heterogeneity and salience, and health analytics. Using 7,614 imaging, clinical, and phenotypic features of 9,914 subjects we performed deep computed phenotyping using unsupervised clustering and derived two distinct sub-cohorts. Using parametric and nonparametric tests, we determined the top 20 most salient features contributing to the cluster separation. Our approach generated decision rules to predict the presence and progression of depression or other mental illnesses by jointly representing and modeling the significant clinical and demographic variables along with the derived salient neuroimaging features. We reported consistency and reliability measures of the derived computed phenotypes and the top salient imaging biomarkers that contributed to the unsupervised clustering. This clinical decision support system identified and utilized holistically the most critical biomarkers for predicting mental health, e.g., depression. External validation of this technique on different populations may lead to reducing healthcare expenses and improving the processes of diagnosis, forecasting, and tracking of normal and pathological aging….(More)”.

Statistics Estonia to coordinate data governance

Curated on Posted on by Stefaan Verhulst

Article by Miriam van der Sangen at CBS: “In 2018, Statistics Estonia launched a new strategy for the period 2018-2022. This strategy addresses the organisation’s aim to produce statistics more quickly while minimising the response burden on both businesses and citizens. Another element in the strategy is addressing the high expectations in Estonian society regarding the use of data. ‘We aim to transform Statistics Estonia into a national data agency,’ says Director General Mägi. ‘This means our role as a producer of official statistics will be enlarged by data governance responsibilities in the public sector. Taking on such responsibilities requires a clear vision of the whole public data ecosystem and also agreement to establish data stewards in most public sector institutions.’…

the Estonian Parliament passed new legislation that effectively expanded the number of official tasks for Statistics Estonia. Mägi elaborates: ‘Most importantly, we shall be responsible for coordinating data governance. The detailed requirements and conditions of data governance will be specified further in the coming period.’ Under the new Act, Statistics Estonia will also have more possibilities to share data with other parties….

Statistics Estonia is fully committed to producing statistics which are based on big data. Mägi explains: ‘At the moment, we are actively working on two big data projects. One project involves the use of smart electricity meters. In this project, we are looking into ways to visualise business and household electricity consumption information. The second project involves web scraping of prices and enterprise characteristics. This project is still in an initial phase, but we can already see that the use of web scraping can improve the efficiency of our production process.’ We are aiming to extend the web scraping project by also identifying e-commerce and innovation activities of enterprises.’

Yet another ambitious goal for Statistics Estonia lies in the field of data science. ‘Similarly to Statistics Netherlands, we established experimental statistics and data mining activities years ago. Last year, we developed a so-called think-tank service, providing insights from data into all aspects of our lives. Think of birth, education, employment, et cetera. Our key clients are the various ministries, municipalities and the private sector. The main aim in the coming years is to speed up service time thanks to visualisations and data lake solutions.’ …(More)”.

Data-driven models of governance across borders

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue of FirstMonday, edited by Payal Arora and Hallam Stevens: “This special issue looks closely at contemporary data systems in diverse global contexts and through this set of papers, highlights the struggles we face as we negotiate efficiency and innovation with universal human rights and social inclusion. The studies presented in these essays are situated in diverse models of policy-making, governance, and/or activism across borders. Attention to big data governance in western contexts has tended to highlight how data increases state and corporate surveillance of citizens, affecting rights to privacy. By moving beyond Euro-American borders — to places such as Africa, India, China, and Singapore — we show here how data regimes are motivated and understood on very different terms….

To establish a kind of baseline, the special issue opens by considering attitudes toward big data in Europe. René König’s essay examines the role of “citizen conferences” in understanding the public’s view of big data in Germany. These “participatory technology assessments” demonstrated that citizens were concerned about the control of big data (should it be under the control of the government or individuals?), about the need for more education about big data technologies, and the need for more government regulation. Participants expressed, in many ways, traditional liberal democratic views and concerns about these technologies centered on individual rights, individual responsibilities, and education. Their proposed solutions too — more education and more government regulation — fit squarely within western liberal democratic traditions.

In contrast to this, Payal Arora’s essay draws us immediately into the vastly different contexts of data governance in India and China. India’s Aadhaar biometric identification system, through tracking its citizens with iris scanning and other measures, promises to root out corruption and provide social services to those most in need. Likewise, China’s emerging “social credit system,” while having immense potential for increasing citizen surveillance, offers ways of increasing social trust and fostering more responsible social behavior online and offline. Although the potential for authoritarian abuses of both systems is high, Arora focuses on how these technologies are locally understood and lived on an everyday basis, which spans from empowering to oppressing their people. From this perspective, the technologies offer modes of “disrupt[ing] systems of inequality and oppression” that should open up new conversations about what democratic participation can and should look like in China and India.

If China and India offer contrasting non-democratic and democratic cases, we turn next to a context that is neither completely western nor completely non-western, neither completely democratic nor completely liberal. Hallam Stevens’ account of government data in Singapore suggests the very different role that data can play in this unique political and social context. Although the island state’s data.gov.sg participates in global discourses of sharing, “open data,” and transparency, much of the data made available by the government is oriented towards the solution of particular economic and social problems. Ultimately, the ways in which data are presented may contribute to entrenching — rather than undermining or transforming — existing forms of governance. The account of data and its meanings that is offered here once again challenges the notion that such data systems can or should be understood in the same ways that similar systems have been understood in the western world.

If systems such as Aadhaar, “social credit,” and data.gov.sg profess to make citizens and governments more visible and legible, Rolien Hoyngexamines what may remain invisible even within highly pervasive data-driven systems. In the world of e-waste, data-driven modes of surveillance and logistics are critical for recycling. But many blind spots remain. Hoyng’s account reminds us that despite the often-supposed all-seeing-ness of big data, we should remain attentive to what escapes the data’s gaze. Here, in midst of datafication, we find “invisibility, uncertainty, and, therewith, uncontrollability.” This points also to the gap between the fantasies of how data-driven systems are supposed to work, and their realization in the world. Such interstices allow individuals — those working with e-waste in Shenzhen or Africa, for example — to find and leverage hidden opportunities. From this perspective, the “blind spots of big data” take on a very different significance.

Big data systems provide opportunities for some, but reduce those for others. Mark Graham and Mohammad Amir Anwar examine what happens when online outsourcing platforms create a “planetary labor market.” Although providing opportunities for many people to make money via their Internet connection, Graham and Anwar’s interviews with workers across sub-Saharan Africa demonstrate how “platform work” alters the balance of power between labor and capital. For many low-wage workers across the globe, the platform- and data-driven planetary labor market means downward pressure on wages, fewer opportunities to collectively organize, less worker agency, and less transparency about the nature of the work itself. Moving beyond bold pronouncements that the “world is flat” and big data as empowering, Graham and Anwar show how data-driven systems of employment can act to reduce opportunities for those residing in the poorest parts of the world. The affordances of data and platforms create a planetary labor market for global capital but tie workers ever-more tightly to their own localities. Once again, the valances of global data systems look very different from this “bottom-up” perspective.

Philippa Metcalfe and Lina Dencik shift this conversation from the global movement of labor to that of people, as they write about the implications of European datafication systems on the governance of refugees entering this region. This work highlights how intrinsic to datafication systems is the classification, coding, and collating of people to legitimize the extent of their belonging in the society they seek to live in. The authors argue that these datafied regimes of power have substantively increased their role in the regulating of human mobility in the guise of national security. These means of data surveillance can foster new forms of containment and entrapment of entire groups of people, creating further divides between “us” and “them.” Through vast interoperable databases, digital registration processes, biometric data collection, and social media identity verification, refugees have become some of the most monitored groups at a global level while at the same time, their struggles remain the most invisible in popular discourse….(More)”.

Nudging the dead: How behavioural psychology inspired Nova Scotia’s organ donation scheme

Curated on Posted on by Stefaan Verhulst

Joseph Brean at National Post: “Nova Scotia’s decision to presume people’s consent to donating their organs after death is not just a North American first. It is also the latest example of how deeply behavioural psychology has changed policy debates.

That is a rare achievement for science. Governments used to appeal to people’s sense of reason, religion, civic duty, or fear of consequences. Today, when they want to change how their citizens behave, they use psychological tricks to hack their minds.

Nudge politics, as it came to be known, has been an intellectual hit among wonks and technocrats ever since Daniel Kahneman won the Nobel Prize in 2002 for destroying the belief people make decisions based on good information and reasonable expectations. Not so, he showed. Not even close. Human decision-making is an organic process, all but immune to reason, but strangely susceptible to simple environmental cues, just waiting to be exploited by a clever policymaker….

Organ donation is a natural fit. Nova Scotia’s experiment aims to solve a policy problem by getting people to do what they always tend to do about government requests — nothing.

The cleverness is evident in the N.S. government’s own words, which play on the meaning of “opportunity”: “Every Nova Scotian will have the opportunity to be an organ and tissue donor unless they opt out.” The policy applies to kidneys, pancreas, heart, liver, lungs, small bowel, cornea, sclera, skin, bones, tendons and heart valves.

It is so clever it aims to make progress as people ignore it. The default position is a positive for the policy. It assumes poor pickup. You can opt out of organ donation if you want. Nova Scotia is simply taking the informed gamble that you probably won’t. That is the goal, and it will make for a revealing case study.

Organ donation is an important question, and chronically low donation rates can reasonably be called a crisis. But most people make their personal choice “thoughtlessly,” as Kahneman wrote in the 2011 book Thinking, Fast and Slow.

He referred to European statistics which showed vast differences in organ donation rights between neighbouring and culturally similar countries, such as Sweden and Denmark, or Germany and Austria. The key difference, he noted, was what he called “framing effects,” or how the question was asked….(More)”.

OECD survey reveals many people unhappy with public services and benefits

Curated on Posted on by Stefaan Verhulst

Report by OECD: “Many people in OECD countries believe public services and social benefits are inadequate and hard to reach. More than half say they do not receive their fair share of benefits given the taxes they pay, and two-thirds believe others get more than they deserve. Nearly three out of four people say they want their government to do more to protect their social and economic security.  

These are among the findings of a new OECD survey, “Risks that Matter”, which asked over 22,000 people aged 18 to 70 years old in 21 countries about their worries and concerns and how well they think their government helps them tackle social and economic risks.

This nationally representative survey finds that falling ill and not being able to make ends meet are often at the top of people’s lists of immediate concerns. Making ends meet is a particularly common worry for those on low incomes and in countries that were hit hard by the financial crisis. Older people are most often worried about their health, while younger people are frequently concerned with securing adequate housing. When asked about the longer-term, across all countries, getting by in old age is the most commonly cited worry.

The survey reveals a dissatisfaction with current social policy. Only a minority are satisfied with access to services like health care, housing, and long-term care. Many believe the government would not be able to provide a proper safety net if they lost their income due to job loss, illness or old age. More than half think they would not be able to easily access public benefits if they needed them.

“This is a wake-up call for policy makers,” said OECD Secretary-General Angel Gurría. “OECD countries have some of the most advanced and generous social protection systems in the world. They spend, on average, more than one-fifth of their GDP on social policies. Yet, too many people feel they cannot count fully on their government when they need help. A better understanding of the factors driving this perception and why people feel they are struggling is essential to making social protection more effective and efficient. We must restore trust and confidence in government, and promote equality of opportunity.”

In every country surveyed except Canada, Denmark, Norway and the Netherlands, most people say that their government does not incorporate the views of people like them when designing social policy. In a number of countries, including Greece, Israel, Lithuania, Portugal and Slovenia, this share rises to more than two-thirds of respondents. This sense of not being part of the policy debate increases at higher levels of education and income, while feelings of injustice are stronger among those from high-income households.

Public perceptions of fairness are worrying. More than half of respondents say they do not receive their fair share of benefits given the taxes they pay, a share that rises to three quarters or more in Chile, Greece, Israel and Mexico. At the same time, people are calling for more help from government. In almost all countries, more than half of respondents say they want the government to do more for their economic and social security. This is especially the case for older respondents and those on low incomes.

Across countries, people are worried about financial security in old age, and most are willing to pay more to support public pension systems… (More)”.

Our data, our society, our health: a vision for inclusive and transparent health data science in the UK and Beyond

Curated on Posted on by Stefaan Verhulst

Paper by Elizabeth Ford et al in Learning Health Systems: “The last six years have seen sustained investment in health data science in the UK and beyond, which should result in a data science community that is inclusive of all stakeholders, working together to use data to benefit society through the improvement of public health and wellbeing.

However, opportunities made possible through the innovative use of data are still not being fully realised, resulting in research inefficiencies and avoidable health harms. In this paper we identify the most important barriers to achieving higher productivity in health data science. We then draw on previous research, domain expertise, and theory, to outline how to go about overcoming these barriers, applying our core values of inclusivity and transparency.

We believe a step-change can be achieved through meaningful stakeholder involvement at every stage of research planning, design and execution; team-based data science; as well as harnessing novel and secure data technologies. Applying these values to health data science will safeguard a social license for health data research, and ensure transparent and secure data usage for public benefit….(More)”.