We Need a New Economic Category


Article by Anne-Marie Slaughter and Hilary Cottam: “Recognizing the true value and potential of care, socially as well as economically, depends on a different understanding of what care actually is: not a service but a relationship that depends on human connection. It is the essence of what Jamie Merisotis, the president of the nonprofit Lumina Foundation, calls “human work”: the “work only people can do.” This makes it all the more essential in an age when workers face the threat of being replaced by machines.

When we use the word in an economic sense, care is a bundle of services: feeding, dressing, bathing, toileting, and assisting. Robots could perform all of those functions; in countries such as Japan, sometimes they already do. But that work is best described as caretaking, comparable to what the caretaker of a property provides by watering a garden or fixing a gate.

What transforms those services into caregiving, the support we want for ourselves and for those we love, is the existence of a relationship between the person providing care and the person being cared for. Not just any relationship, but one that is affectionate, or at least considerate and respectful. Most human beings cannot thrive without connection to others, a point underlined by the depression and declining mental capacities of many seniors who have been isolated during the pandemic….

One of us, Hilary, has worked in Britain to expand caregiving networks. In 2007 she co-designed a program called Circle, which is part social club, part concierge service. Members pay a small monthly fee, and in return get access to fun activities and practical support from members and helpers in the community. More than 10,000 people have participated, and evaluations show that members feel less lonely and more capable. The program has also reduced the money spent on formal services; Circle members are less likely, for example, to be readmitted to the hospital.The mutual-aid societies that mushroomed into existence across the United States during the pandemic reflect the same philosophy. The core of a mutual-aid network is the principle of “solidarity not charity”: a group of community members coming together on an equal basis for the common good. These societies draw on a long tradition of “collective care” developed by African American, Indigenous, and immigrant groups as far back as the 18th century….Care jobs help humans flourish, and, properly understood and compensated, they can power a growing sector of the economy, strengthen our society, and increase our well-being. Goods are things that people buy and own; services are functions that people pay for. Relationships require two people and a connection between them. We don’t really have an economic category for that, but we should….(More)”.

Data Science for Social Good: Philanthropy and Social Impact in a Complex World


Book edited by Ciro Cattuto and Massimo Lapucci: “This book is a collection of insights by thought leaders at first-mover organizations in the emerging field of “Data Science for Social Good”. It examines the application of knowledge from computer science, complex systems, and computational social science to challenges such as humanitarian response, public health, and sustainable development. The book provides an overview of scientific approaches to social impact – identifying a social need, targeting an intervention, measuring impact – and the complementary perspective of funders and philanthropies pushing forward this new sector.

TABLE OF CONTENTS


Introduction; By Massimo Lapucci

The Value of Data and Data Collaboratives for Good: A Roadmap for Philanthropies to Facilitate Systems Change Through Data; By Stefaan G. Verhulst

UN Global Pulse: A UN Innovation Initiative with a Multiplier Effect; By Dr. Paula Hidalgo-Sanchis

Building the Field of Data for Good; By Claudia Juech

When Philanthropy Meets Data Science: A Framework for Governance to Achieve Data-Driven Decision-Making for Public Good; By Nuria Oliver

Data for Good: Unlocking Privately-Held Data to the Benefit of the Many; By Alberto Alemanno

Building a Funding Data Ecosystem: Grantmaking in the UK; By Rachel Rank

A Reflection on the Role of Data for Health: COVID-19 and Beyond; By Stefan E. Germann and Ursula Jasper….(More)”

Why designers should embrace ‘weird data’


Article by Mimi Ọnụọha: “My interest in missing things began with what I could see. For a long time, I have kept a small piece of paper taped to the bottom right corner of my desk. This paper comes and goes, at times becoming wrinkled, discolored by tea stains, or hidden under a stack of books. But it always serves the same purpose: listing the most eccentric datasets that I can find online.

Before the score and lyrics for the hit American musical Hamilton had been released, a group of obsessed fans created a shared document of every word in the show. This dataset made my list. In 2016, a Reddit user published a post with a link to where he had downloaded the metadata of every story ever published on fanfiction.net, a popular site for stories about fandoms. This, too, made the list.

Other things that have graced the list: the daily count of footballs produced by the Wilson Sporting Goods football factory in Ada, Iowa (4,000 as of 2008); an estimation of the number of hot dogs eaten by Americans on the Fourth of July every year (most recently: 150 million); the locations of every public toilet in Australia (of which there are more than 17,000).

Australian academic Mitchell Whitelaw defines data as measurements extracted from the flux of the real. When we typically think of collecting data, we think of big, important things: census information, UN data about health and diseases, data mined by large companies like Google, Amazon, or Facebook….(More)”.

Governing Cross-Border Challenges


OECD Report: “Issues facing governments are increasingly complex and transboundary in nature, making existing governance mechanisms unsuitable for managing them. Governments are leveraging new governance structures and mechanisms to connect and collaborate in order to tackle issues that cut across borders. Governance arrangements with innovative elements can act as enablers of cross-border government collaboration and assist in making it more systemic.

This work has led to the identification of three leading governance approaches and associated case studies, as discussed below….

Theme 1: Building cross-border governance bodies…

Theme 2: Innovative networks tackling cross-border collaboration…

Theme 3: Exploring emerging governance system dynamics…(More)”.

Launch of UN Biodiversity Lab 2.0: Spatial data and the future of our planet


Press Release: “…The UNBL 2.0 is a free, open-source platform that enables governments and others to access state-of-the-art maps and data on nature, climate change, and human development in new ways to generate insight for nature and sustainable development. It is freely available online to governments and other stakeholders as a digital public good…

The UNBL 2.0 release responds to a known global gap in the types of spatial data and tools, providing an invaluable resource to nations around the world to take transformative action. Users can now access over 400 of the world’s best available global spatial data layers; create secure workspaces to incorporate national data alongside global data; use curated data collections to generate insight for action; and more. Without specialized tools or training, decision-makers can leverage the power of spatial data to support priority-setting and the implementation of nature-based solutions. Dynamic metrics and indicators on the state of our planet are also available….(More)”.

False Positivism


Essay by Peter Polack: “During the pandemic, the everyday significance of modeling — data-driven representations of reality designed to inform planning — became inescapable. We viewed our plans, fears, and desires through the lens of statistical aggregates: Infection-rate graphs became representations not only of the virus’s spread but also of shattered plans, anxieties about lockdowns, concern for the fate of our communities. 

But as epidemiological models became more influential, their implications were revealed as anything but absolute. One model, the Recidiviz Covid-19 Model for Incarceration, predicted high infection rates in prisons and consequently overburdened hospitals. While these predictions were used as the basis to release some prisoners early, the model has also been cited by those seeking to incorporate more data-driven surveillance technologies into prison management — a trend new AI startups like Blue Prism and Staqu are eager to get in on. Thus the same model supports both the call to downsize prisons and the demand to expand their operations, even as both can claim a focus on flattening the curve. …

The ethics and effects of interventions depend not only on facts in themselves, but also on how facts are construed — and on what patterns of organization, existing or speculative, they are mobilized to justify. Yet the idea persists that data collection and fact finding should override concerns about surveillance, and not only in the most technocratic circles and policy think tanks. It also has defenders in the world of design theory and political philosophy. Benjamin Bratton, known for his theory of global geopolitics as an arrangement of computational technologies he calls “theStack,” sees in data-driven modeling the only political rationality capable of responding to difficult social and environmental problems like pandemics and climate change. In his latest book, The Revenge of the Real: Politics for a Post-Pandemic World, he argues that expansive models — enabled by what he theorizes as “planetary-scale computation” — can transcend individualistic perspectives and politics and thereby inaugurate a more inclusive and objective regime of governance. Against a politically fragmented world of polarized opinions and subjective beliefs, these models, Bratton claims, would unite politics and logistics under a common representation of the world. In his view, this makes longstanding social concerns about personal privacy and freedom comparatively irrelevant and those who continue to raise them irrational…(More)”.

The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations


Paper by Josh Cowls, Andreas Tsamados, Mariarosaria Taddeo & Luciano Floridi: “In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment….(More)”.

For a heterodox computational social science


Paper by Petter Törnberg and Justus Uitermark: “The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life….(More)”.

Slowed canonical progress in large fields of science


Paper by Johan S. G. Chu and James A. Evans: “The size of scientific fields may impede the rise of new ideas. Examining 1.8 billion citations among 90 million papers across 241 subjects, we find a deluge of papers does not lead to turnover of central ideas in a field, but rather to ossification of canon. Scholars in fields where many papers are published annually face difficulty getting published, read, and cited unless their work references already widely cited articles. New papers containing potentially important contributions cannot garner field-wide attention through gradual processes of diffusion. These findings suggest fundamental progress may be stymied if quantitative growth of scientific endeavors—in number of scientists, institutes, and papers—is not balanced by structures fostering disruptive scholarship and focusing attention on novel ideas…(More)”.

Solutions to Plastic Pollution: A Conceptual Framework to Tackle a Wicked Problem


Chapter by Martin Wagner: “There is a broad willingness to act on global plastic pollution as well as a plethora of available technological, governance, and societal solutions. However, this solution space has not been organized in a larger conceptual framework yet. In this essay, I propose such a framework, place the available solutions in it, and use it to explore the value-laden issues that motivate the diverse problem formulations and the preferences for certain solutions by certain actors. To set the scene, I argue that plastic pollution shares the key features of wicked problems, namely, scientific, political, and societal complexity and uncertainty as well as a diversity in the views of actors. To explore the latter, plastic pollution can be framed as a waste, resource, economic, societal, or systemic problem.

Doing so results in different and sometimes conflicting sets of preferred solutions, including improving waste management; recycling and reuse; implementing levies, taxes, and bans as well as ethical consumerism; raising awareness; and a transition to a circular economy. Deciding which of these solutions is desirable is, again, not a purely rational choice. Accordingly, the social deliberations on these solution sets can be organized across four scales of change. At the geographic and time scales, we need to clarify where and when we want to solve the plastic problem. On the scale of responsibility, we need to clarify who is accountable, has the means to make change, and carries the costs. At the magnitude scale, we need to discuss which level of change we desire on a spectrum of status quo to revolution. All these issues are inherently linked to value judgments and worldviews that must, therefore, be part of an open and inclusive debate to facilitate solving the wicked problem of plastic pollution…(More)”.