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)”.
Analyzing Big Data on a Shoestring Budget
Article by Toshiko Kaneda and Lori S. Ashford: “Big data has opened a new world for demographers and public health scientists to explore, to gain insights into social and health phenomena using the myriad digital traces we leave behind in our daily lives. But is analyzing big data practical and affordable? Researchers and organizations who have not made the leap might wonder: Do we need a lot more funding? Supercomputers? Armies of data scientists?
Three studies, presented recently in a PRB Demography Talk, show the feasibility of conducting research on a proverbial shoestring—using big data that are publicly, freely available to anyone with a personal computer and Wi-Fi connection.
Study 1: Can Google data help measure health care access more accurately?
The first study, presented by Luis Gabriel Cuervo of the Universitat Autònoma de Barcelona and the AMORE project, used Google mobility data to assess the effect of traffic congestion on people’s ability to access health services in Cali, Colombia, a city of 2.3 million. The study aimed to improve how health care accessibility is measured and communicated, to inform urban and health services planning.
Cuervo assembled a multidisciplinary research team, including mobility experts, to examine travel times from where people live to urgent and frequently used health services. The team used Google’s Distance Matrix API, which provides travel times and distance between origins and destinations, accounting for changing traffic conditions. The data are generated from Google Maps on people’s cell phones.
Combining this information with census and health services data, the study measured travel times repeatedly and revealed significant inequality by sociodemographic characteristics. On typical days, 60% of the city’s population lived more than 15 minutes by car from emergency care, with those in the poorest neighborhoods facing the longest travel times and a greater impact from traffic congestion.
Studies 2 and 3: Can Google data help predict changes in birth rates and examine excess deaths from COVID-19 related shutdowns?
In another study, Joshua Wilde from the Max Planck Institute for Demographic Research (MPIDR) and Portland State University asked, can Google search data predict whether COVID-related shutdowns will lead to a baby boom or bust? In 2020, early in the pandemic, Wilde and team constructed a forecasting model based on volumes of Google searches with keywords related to conception, pregnancy, childbirth, and economic stability. Their thinking was that if searches increased sharply for keywords such as “pregnancy test” and “missed period,” one might expect higher birth rates seven to nine months later. On the other hand, prior research had associated unemployment with lower birth rates—so if unemployment-related searches climbed, one might expect a baby bust….(More)”.
Policy Guide on Social Impact Measurement for the Social and Solidarity Economy
OECD Report: “As social and solidarity economy (SSE) entities are increasingly requested to demonstrate their positive contribution to society, social impact measurement can help them understand the additional, net value generated by their activities, in the pursuit of their mission and beyond. Policy plays an important role to facilitate a conducive environment to unlock the uptake of social impact measurement among SSE actors. Drawing on a mapping exercise and good practice examples from over 33 countries, this international policy guide navigates how policy makers can support social impact measurement for the social and solidarity economy by: (i) improving the policy framework, (ii) delivering guidance, (iii) building evidence and (iv) supporting capacity. Building on the earlier publication Social Impact Measurement for the Social and Solidarity Economy released in 2021 the guide is published under the framework of the OECD Global Action “Promoting Social and Solidarity Economy Ecosystems”, funded by the European Union’s Foreign Partnership Instrument…(More)”.
An agenda for advancing trusted data collaboration in cities
Report by Hannah Chafetz, Sampriti Saxena, Adrienne Schmoeker, Stefaan G. Verhulst, & Andrew J. Zahuranec: “… Joined by experts across several domains including smart cities, the law, and data ecosystem, this effort was focused on developing solutions that could improve the design of Data Sharing Agreements…we assessed what is needed to implement each aspect of our Contractual Wheel of Data Collaboration–a tool developed as a part of the Contracts for Data Collaborations initiative that seeks to capture the elements involved in data collaborations and Data Sharing Agreements.
In what follows, we provide key suggestions from this Action Lab…
- The Elements of Principled Negotiations: Those seeking to develop a Data Sharing Agreement often struggle to work with collaborators or agree to common ends. There is a need for a common resource that Data Stewards can use to initiate a principled negotiation process. To address this need, we would identify the principles to inform negotiations and the elements that could help achieve those principles. For example, participants voiced a need for fairness, transparency, and reciprocity principles. These principles could be supported by having a shared language or outlining the minimum legal documents required for each party. The final product would be a checklist or visualization of principles and their associated elements.
- Data Responsibility Principles by Design: …
- Readiness Matrix: …
- A Decision Provenance Approach for Data Collaboration: ..
- The Contractual Wheel of Data Collaboration 2.0…
- A Repository of Legal Drafting Technologies:…(More)”.
Building Trust in AI: A Landscape Analysis of Government AI Programs
Paper by Susan Ariel Aaronson: “As countries around the world expand their use of artificial intelligence (AI), the Organisation for Economic Co-operation and Development (OECD) has developed the most comprehensive website on AI policy, the OECD.AI Policy Observatory. Although the website covers public policies on AI, the author of this paper found that many governments failed to evaluate or report on their AI initiatives. This lack of reporting is a missed opportunity for policy makers to learn from their programs (the author found that less than one percent of the programs listed on the OECD.AI website had been evaluated). In addition, the author found discrepancies between what governments said they were doing on the OECD.AI website and what they reported on their own websites. In some cases, there was no evidence of government actions; in other cases, links to government sites did not work. Evaluations of AI policies are important because they help governments demonstrate how they are building trust in both AI and AI governance and that policy makers are accountable to their fellow citizens…(More)”.
To harness telecom data for good, there are six challenges to overcome
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)”.
The Right To Be Free From Automation
Essay by Ziyaad Bhorat: “Is it possible to free ourselves from automation? The idea sounds fanciful, if not outright absurd. Industrial and technological development have reached a planetary level, and automation, as the general substitution or augmentation of human work with artificial tools capable of completing tasks on their own, is the bedrock of all the technologies designed to save, assist and connect us.
From industrial lathes to OpenAI’s ChatGPT, automation is one of the most groundbreaking achievements in the history of humanity. As a consequence of the human ingenuity and imagination involved in automating our tools, the sky is quite literally no longer a limit.
But in thinking about our relationship to automation in contemporary life, my unease has grown. And I’m not alone — America’s Blueprint for an AI Bill of Rights and the European Union’s GDPR both express skepticism of automated tools and systems: The “use of technology, data and automated systems in ways that threaten the rights of the American public”; the “right not to be subject to a decision based solely on automated processing.”
If we look a little deeper, we find this uneasy language in other places where people have been guarding three important abilities against automated technologies. Historically, we have found these abilities so important that we now include them in various contemporary rights frameworks: the right to work, the right to know and understand the source of the things we consume, and the right to make our own decisions. Whether we like it or not, therefore, communities and individuals are already asserting the importance of protecting people from the ubiquity of automated tools and systems.
Consider the case of one of South Africa’s largest retailers, Pick n Pay, which in 2016 tried to introduce self-checkout technology in its retail stores. In post-Apartheid South Africa, trade unions are immensely powerful and unemployment persistently high, so any retail firm that wants to introduce technology that might affect the demand for labor faces huge challenges. After the country’s largest union federation threatened to boycott the new Pick n Pay machines, the company scrapped its pilot.
As the sociologist Christopher Andrews writes in “The Overworked Consumer,” self-checkout technology is by no means a universally good thing. Firms that introduce it need to deal with new forms of theft, maintenance and bottleneck, while customers end up doing more work themselves. These issues are in addition to the ill fortunes of displaced workers…(More)”.
The Government of Chance: Sortition and Democracy from Athens to the Present
Book by Yves Sintomer: “Electoral democracies are struggling. Sintomer, in this instructive book, argues for democratic innovations. One such innovation is using random selection to create citizen bodies with advisory or decisional political power. ‘Sortition’ has a long political history. Coupled with elections, it has represented an important yet often neglected dimension of Republican and democratic government, and has been reintroduced in the Global North, China and Mexico. The Government of Chance explores why sortation is returning, how it is coupled with deliberation, and why randomly selected ‘minipublics’ and citizens’ assemblies are flourishing. Relying on a growing international and interdisciplinary literature, Sintomer provides the first systematic and theoretical reconstruction of the government of chance from Athens to the present. At what conditions can it be rational? What lessons can be drawn from history? The Government of Chance therefore clarifies the democratic imaginaries at stake: deliberative, antipolitical, and radical, making a plaidoyer for the latter….(More)”.
Reclaiming Participatory Governance
Book edited by Adrian Bua and Sonia Bussu: “…offers empirical and theoretical perspectives on how the relationship between social movements and state institutions is emerging and developing through new modes of participatory governance.
One of the most interesting political developments of the past decade has been the adoption by social movements of strategies seeking to change political institutions through participatory governance. These strategies have flourished in a variety of contexts, from anti-austerity and pro-social justice protests in Spain, to movements demanding climate transition and race equality in the UK and the USA, to constitutional reforms in Belgium and Iceland. The chief ambition and challenge of these new forms of participatory governance is to institutionalise the prefigurative politics and social justice values that inspired them in the first place, by mobilising the bureaucracy to respond to their claims for reforms and rights. The authors of this volume assess how participatory governance is being transformed and explore the impact of such changes, providing timely critical reflections on: the constraints imposed by cultural, economic and political power relations on these new empowered participatory spaces; the potential of this new “wave” of participatory democracy to reimagine the relationship between citizens and traditional institutions towards more radical democratic renewal; where and how these new democratisation efforts sit within the representative state; and how tensions between the different demands of lay citizens, organised civil society and public officials are being managed….(More)”.
Your Data Is Diminishing Your Freedom
Interview by David Marchese: “It’s no secret — even if it hasn’t yet been clearly or widely articulated — that our lives and our data are increasingly intertwined, almost indistinguishable. To be able to function in modern society is to submit to demands for ID numbers, for financial information, for filling out digital fields and drop-down boxes with our demographic details. Such submission, in all senses of the word, can push our lives in very particular and often troubling directions. It’s only recently, though, that I’ve seen someone try to work through the deeper implications of what happens when our data — and the formats it’s required to fit — become an inextricable part of our existence, like a new limb or organ to which we must adapt. ‘‘I don’t want to claim we are only data and nothing but data,’’ says Colin Koopman, chairman of the philosophy department at the University of Oregon and the author of ‘‘How We Became Our Data.’’ ‘‘My claim is you are your data, too.’’ Which at the very least means we should be thinking about this transformation beyond the most obvious data-security concerns. ‘‘We’re strikingly lackadaisical,’’ says Koopman, who is working on a follow-up book, tentatively titled ‘‘Data Equals,’’ ‘‘about how much attention we give to: What are these data showing? What assumptions are built into configuring data in a given way? What inequalities are baked into these data systems? We need to be doing more work on this.’’
Can you explain more what it means to say that we have become our data? Because a natural reaction to that might be, well, no, I’m my mind, I’m my body, I’m not numbers in a database — even if I understand that those numbers in that database have real bearing on my life. The claim that we are data can also be taken as a claim that we live our lives through our data in addition to living our lives through our bodies, through our minds, through whatever else. I like to take a historical perspective on this. If you wind the clock back a couple hundred years or go to certain communities, the pushback wouldn’t be, ‘‘I’m my body,’’ the pushback would be, ‘‘I’m my soul.’’ We have these evolving perceptions of our self. I don’t want to deny anybody that, yeah, you are your soul. My claim is that your data has become something that is increasingly inescapable and certainly inescapable in the sense of being obligatory for your average person living out their life. There’s so much of our lives that are woven through or made possible by various data points that we accumulate around ourselves — and that’s interesting and concerning. It now becomes possible to say: ‘‘These data points are essential to who I am. I need to tend to them, and I feel overwhelmed by them. I feel like it’s being manipulated beyond my control.’’ A lot of people have that relationship to their credit score, for example. It’s both very important to them and very mysterious…(More)”.