Imagery: A better “picture” of the city


Daniel Arribas-Bel at Catapult: ‘When trying to understand something as complex as the city, every bit of data helps create a better picture. Researchers, practitioners and policymakers gather as much information as they can to represent every aspect of their city – from noise levels captured by open-source sensors and the study of social isolation using tweets to where the latest hipster coffee shop has opened – exploration and creativity seem to have no limits.

But what about imagery?

You might well ask, what type of images? How do you analyse them? What’s the point anyway?

Let’s start with the why. Images contain visual cues that encode a host of socio-economic information. Imagine a picture of a street with potholes outside a derelict house next to a burnt out car. It may be easy to make some fairly sweeping assumptions about the average income of its resident population. Or the image of a street with a trendy barber-shop next door to a coffee-shop with bare concrete feature walls on one side, and an independent record shop on the other. Again, it may be possible to describe the character of this area.

These are just some of the many kinds of signals embedded in image data. In fact, there is entire literature in geography and sociology that document these associations (see, for example, Cityscapes by Daniel Aaron Silver and Terry Nichols Clark for a sociology approach and The Predictive Postcode by Richard Webber and Roger Burrows for a geography perspective). Imagine if we could figure out ways to condense such information into formal descriptors of cities that help us measure aspects that traditional datasets can’t, or to update them more frequently than standard sources currently allow…(More)”.

The cultural foundations of modern democracies


Damian J. Ruck, Luke J. Matthews, Thanos Kyritsis, Quentin D. Atkinson & R. Alexander Bentley at Nature Human Behavior: “National democracy is a rare thing in human history and its stability has long been tied to the cultural values of citizens. Yet it has not been established whether changing cultural values made modern democracy possible or whether those values were a response to democratic institutions. Here we combine longitudinal data and cohort information of nearly 500,000 individuals from 109 nations to track the co-evolution of democratic values and institutions over the last century.

We find that cultural values of openness towards diversity predict a shift towards democracy and that nations with low institutional confidence are prone to political instability. In addition, the presence of democratic institutions did not predict any substantive changes in the measured cultural values. These results hold accounting for other factors, including gross domestic product per capita and non-independence between nations due to shared cultural ancestry. Cultural values lead to, rather than follow, the emergence of democracy. This indicates that current stable democracies will be under threat, should cultural values of openness to diversity and institutional confidence substantially decline… (More).”

Redesigning Organizations: Concepts for the Connected Society


Book by Denise Feldner: “This book offers readers a deeper understanding of the Cyberspace, of how institutions and industries are reinventing themselves, helping them excel in the transition to a fully digitally connected global economy. Though technology plays a key part in this regard, societal acceptance is the most important underlying condition, as it poses pressing challenges that cut across companies, developers, governments and workers.

The book explores the challenges and opportunities involved, current and potential future concepts, critical reflections and best practices. It addresses connected societies, new opportunities for governments, the role of trust in digital networks, and future education networks. In turn, a number of representative case studies demonstrate the current state of development in practice….(More)”.

Between Truth and Power The Legal Constructions of Informational Capitalism


Book by Julie Cohen: “Our current legal system is to a great extent the product of an earlier period of social and economic transformation. From the late nineteenth century through the mid-twentieth century, as accountability for industrial-age harms became a pervasive source of conflict, the U.S. legal system underwent profound, tectonic shifts. Today, ownership of information-age resources and accountability for information-age harms have become pervasive sources of conflict, and different kinds of change are emerging.

In Between Truth and Power, Julie E. Cohen explores the relationships between legal institutions and political and economic transformation. Systematically examining struggles over the conditions of information flow and the design of information architectures and business models, she argues that as law is enlisted to help produce the profound economic and socio-technical shifts that have accompanied the emergence of the informational economy, it is too is transforming in fundamental ways. Drawing on elements from legal theory, science and technology studies, information studies, communication studies and organization studies to develop a complex theory of institutional change, Cohen develops an account of the gradual emergence of legal institutions adapted to the information age and of the power relationships that such institutions reflect and reproduce….(More)”.

Data Protection in the Humanitarian Sector – A Blockchain Approach


Report by Andrej Verity and Irene Solaiman: “Data collection and storage are becoming increasingly digital. In the humanitarian sector, data motivates action, informing organizations who then determine priorities and resource allocation in crises.

“Humanitarians are dependent on technology and on the Internet. When life-saving aid isn’t delivered on time and to the right beneficiaries, people can die.” -Brookings

In the age of information and cyber warfare, humanitarian organizations must take measures to protect civilians, especially those in critical and vulnerable positions.

“Data privacy and ensuring protection from harm, including the provision of data security, are therefore fundamentally linked—and neither can be realized without the other.” -The Signal Code

Information in the wrong hands can risk lives or even force aid organizations to shut down. For example, in 2009, Sudan expelled over a dozen international nongovernmental organizations (NGOs) that were deemed key to maintaining a lifeline to 4.7 million people in western Darfur. The expulsion occurred after the Sudanese Government collected Internet-accessible information that made leadership fear international criminal charges. Responsible data protection is a crucial component of cybersecurity. As technology develops, so do threats and data vulnerabilities. Emerging technologies such as blockchain provide further security to sensitive information and overall data storage. Still, with new technologies come considerations for implementation…(More)”.

Quadratic Payments: A Primer


Blogpost by Vitalik Buterin: “If you follow applied mechanism design or decentralized governance at all, you may have recently heard one of a few buzzwords: quadratic votingquadratic funding and quadratic attention purchase. These ideas have been gaining popularity rapidly over the last few years, and small-scale tests have already been deployed: the Taiwanese presidential hackathon used quadratic voting to vote on winning projects, Gitcoin Grants used quadratic funding to fund public goods in the Ethereum ecosystem, and the Colorado Democratic party also experimented with quadratic voting to determine their party platform.

To the proponents of these voting schemes, this is not just another slight improvement to what exists. Rather, it’s an initial foray into a fundamentally new class of social technology which, has the potential to overturn how we make many public decisions, large and small. The ultimate effect of these schemes rolled out in their full form could be as deeply transformative as the industrial-era advent of mostly-free markets and constitutional democracy. But now, you may be thinking: “These are large promises. What do these new governance technologies have that justifies such claims?”…(More)”.

Collective Intelligence: A Taxonomy and Survey


Paper by Feijuan He et al: “Collective intelligence (CI) refers to the intelligence that emerges at the macro-level of a collection and transcends that of the individuals. CI is a continuously popular research topic that is studied by researchers in different areas, such as sociology, economics, biology, and artificial intelligence. In this survey, we summarize the works of CI in various fields. First, according to the existence of interactions between individuals and the feedback mechanism in the aggregation process, we establish CI taxonomy that includes three paradigms: isolation, collaboration and feedback. We then conduct statistical literature analysis to explain the differences among three paradigms and their development in recent years. Second, we elaborate the types of CI under each paradigm and discuss the generation mechanism or theoretical basis of the different types of CI. Third, we describe certain CI-related applications in 2019, which can be appropriately categorized by our proposed taxonomy. Finally, we summarize the future research directions of CI under each paradigm. We hope that this survey helps researchers understand the current conditions of CI and clears the directions of future research….(More)”

The Crowd and the Cosmos: Adventures in the Zooniverse


Book by Chris Lintott: “The world of science has been transformed. Where once astronomers sat at the controls of giant telescopes in remote locations, praying for clear skies, now they have no need to budge from their desks, as data arrives in their inbox. And what they receive is overwhelming; projects now being built provide more data in a few nights than in the whole of humanity’s history of observing the Universe. It’s not just astronomy either – dealing with this deluge of data is the major challenge for scientists at CERN, and for biologists who use automated cameras to spy on animals in their natural habitats. Artificial intelligence is one part of the solution – but will it spell the end of human involvement in scientific discovery?

No, argues Chris Lintott. We humans still have unique capabilities to bring to bear – our curiosity, our capacity for wonder, and, most importantly, our capacity for surprise. It seems that humans and computers working together do better than computers can on their own. But with so much scientific data, you need a lot of scientists – a crowd, in fact. Lintott found such a crowd in the Zooniverse, the web-based project that allows hundreds of thousands of enthusiastic volunteers to contribute to science.

In this book, Lintott describes the exciting discoveries that people all over the world have made, from galaxies to pulsars, exoplanets to moons, and from penguin behavior to old ship’s logs. This approach builds on a long history of so-called “citizen science,” given new power by fast internet and distributed data. Discovery is no longer the remit only of scientists in specialist labs or academics in ivory towers. It’s something we can all take part in. As Lintott shows, it’s a wonderful way to engage with science, yielding new insights daily. You, too, can help explore the Universe in your lunch hour…(More)”.

Defining concepts of the digital society


A special section of Internet Policy Review edited by Christian Katzenbach and Thomas Christian Bächle: “With this new special section Defining concepts of the digital society in Internet Policy Review, we seek to foster a platform that provides and validates exactly these overarching frameworks and theories. Based on the latest research, yet broad in scope, the contributions offer effective tools to analyse the digital society. Their authors offer concise articles that portray and critically discuss individual concepts with an interdisciplinary mindset. Each article contextualises their origin and academic traditions, analyses their contemporary usage in different research approaches and discusses their social, political, cultural, ethical or economic relevance and impact as well as their analytical value. With this, the authors are building bridges between the disciplines, between research and practice as well as between innovative explanations and their conceptual heritage….(More)”

Algorithmic governance
Christian Katzenbach, Alexander von Humboldt Institute for Internet and Society
Lena Ulbricht, Berlin Social Science Center

Datafication
Ulises A. Mejias, State University of New York at Oswego
Nick Couldry, London School of Economics & Political Science

Filter bubble
Axel Bruns, Queensland University of Technology

Platformisation
Thomas Poell, University of Amsterdam
David Nieborg, University of Toronto
José van Dijck, Utrecht University

Privacy
Tobias Matzner, University of Paderborn
Carsten Ochs, University of Kassel

Causal Inference: What If


Book by Miguel A. Hernán, James M. Robins: “Causal Inference is an admittedly pretentious title for a book. Causal inference is a complex scientific task that relies on triangulating evidence from multiple sources and on the application of a variety of methodological approaches. No book can possibly provide a comprehensive description of methodologies for causal inference across the sciences. The authors of any Causal Inference book will have to choose which aspects of causal inference methodology they want to emphasize.

The title of this introduction reflects our own choices: a book that helps scientists–especially health and social scientists–generate and analyze data to make causal inferences that are explicit about both the causal question and the assumptions underlying the data analysis. Unfortunately, the scientific literature is plagued by studies in which the causal question is not explicitly stated and the investigators’ unverifiable assumptions are not declared. This casual attitude towards causal inference has led to a great deal of confusion. For example, it is not uncommon to find studies in which the effect estimates are hard to interpret because the data analysis methods cannot appropriately answer the causal question (were it explicitly stated) under the investigators’ assumptions (were they declared).

In this book, we stress the need to take the causal question seriously enough to articulate it, and to delineate the separate roles of data and assumptions for causal inference. Once these foundations are in place, causal inferences become necessarily less casual, which helps prevent confusion. The book describes various data analysis approaches that can be used to estimate the causal effect of interest under a particular set of assumptions when data are collected on each individual in a population. A key message of the book is that causal inference cannot be reduced to a collection of recipes for data analysis.

The book is divided in three parts of increasing difficulty: Part I is about causal inference without models (i.e., nonparametric identification of causal effects), Part II is about causal inference with models (i.e., estimation of causal effects with parametric models), and Part III is about causal inference from complex longitudinal data (i.e., estimation of causal effects of time-varying treatments)….(More) (Additional Material)”.