Technology and satellite companies open up a world of data

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Gabriel Popkin at Nature: “In the past few years, technology and satellite companies’ offerings to scientists have increased dramatically. Thousands of researchers now use high-resolution data from commercial satellites for their work. Thousands more use cloud-computing resources provided by big Internet companies to crunch data sets that would overwhelm most university computing clusters. Researchers use the new capabilities to track and visualize forest and coral-reef loss; monitor farm crops to boost yields; and predict glacier melt and disease outbreaks. Often, they are analysing much larger areas than has ever been possible — sometimes even encompassing the entire globe. Such studies are landing in leading journals and grabbing media attention.

Commercial data and cloud computing are not panaceas for all research questions. NASA and the European Space Agency carefully calibrate the spectral quality of their imagers and test them with particular types of scientific analysis in mind, whereas the aim of many commercial satellites is to take good-quality, high-resolution pictures for governments and private customers. And no company can compete with Landsat’s free, publicly available, 46-year archive of images of Earth’s surface. For commercial data, scientists must often request images of specific regions taken at specific times, and agree not to publish raw data. Some companies reserve cloud-computing assets for researchers with aligned interests such as artificial intelligence or geospatial-data analysis. And although companies publicly make some funding and other resources available for scientists, getting access to commercial data and resources often requires personal connections. Still, by choosing the right data sources and partners, scientists can explore new approaches to research problems.

Mapping poverty

Joshua Blumenstock, an information scientist at the University of California, Berkeley (UCB), is always on the hunt for data he can use to map wealth and poverty, especially in countries that do not conduct regular censuses. “If you’re trying to design policy or do anything to improve living conditions, you generally need data to figure out where to go, to figure out who to help, even to figure out if the things you’re doing are making a difference.”

In a 2015 study, he used records from mobile-phone companies to map Rwanda’s wealth distribution (J. Blumenstock et al. Science 350, 1073–1076; 2015). But to track wealth distribution worldwide, patching together data-sharing agreements with hundreds of these companies would have been impractical. Another potential information source — high-resolution commercial satellite imagery — could have cost him upwards of US$10,000 for data from just one country….

Use of commercial images can also be restricted. Scientists are free to share or publish most government data or data they have collected themselves. But they are typically limited to publishing only the results of studies of commercial data, and at most a limited number of illustrative images.

Many researchers are moving towards a hybrid approach, combining public and commercial data, and running analyses locally or in the cloud, depending on need. Weiss still uses his tried-and-tested ArcGIS software from Esri for studies of small regions, and jumps to Earth Engine for global analyses.

The new offerings herald a shift from an era when scientists had to spend much of their time gathering and preparing data to one in which they’re thinking about how to use them. “Data isn’t an issue any more,” says Roy. “The next generation is going to be about what kinds of questions are we going to be able to ask?”…(More)”.

Democracy doomsday prophets are missing this critical shift

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Bruno Kaufmann and Joe Mathews in the Washington Post: “The new conventional wisdom seems to be that electoral democracy is in decline. But this ignores another widespread trend: direct democracy at the local and regional level is booming, even as disillusion with representative government at the national level grows.

Today, 113 of the world’s 117 democratic countries offer their citizens legally or constitutionally established rights to bring forward a citizens’ initiative, referendum or both. And since 1980, roughly 80 percent of countries worldwide have had at least one nationwide referendum or popular vote on a legislative or constitutional issue.

Of all the nationwide popular votes in the history of the world, more than half have taken place in the past 30 years. As of May 2018, almost 2,000 nationwide popular votes on substantive issues have taken place, with 1,059 in Europe, 191 in Africa, 189 in Asia, 181 in the Americas and 115 in Oceania, based on our research.

That is just at the national level. Other major democracies — Germany, the United States and India — do not permit popular votes on substantive issues nationally but support robust direct democracy at the local and regional levels. The number of local votes on issues has so far defied all attempts to count them — they run into the tens of thousands.

This robust democratization, at least when it comes to direct legislation, provides a context that’s generally missing when doomsday prophets suggest that democracy is dying by pointing to authoritarian-leaning leaders like Turkish President Recep Tayyip Erdogan, Russian President Vladimir Putin, Hungarian Prime Minister Viktor Orbán, Philippine President Rodrigo Duterte and U.S. President Donald Trump.

Indeed, the two trends — the rise of populist authoritarianism in some nations and the rise of local and direct democracy in some areas — are related. Frustration is growing with democratic systems at national levels, and yes, some people become more attracted to populism. But some of that frustration is channeled into positive energy — into making local democracy more democratic and direct.

Cities from Seoul to San Francisco are hungry for new and innovative tools that bring citizens into processes of deliberation that allow the people themselves to make decisions and feel invested in government actions. We’ve seen local governments embrace participatory budgeting, participatory planning, citizens’ juries and a host of experimental digital tools in service of that desired mix of greater public deliberation and more direct public action….(More).”

Data Governance in the Digital Age

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Centre for International Governance Innovation: “Data is being hailed as “the new oil.” The analogy seems appropriate given the growing amount of data being collected, and the advances made in its gathering, storage, manipulation and use for commercial, social and political purposes.

Big data and its application in artificial intelligence, for example, promises to transform the way we live and work — and will generate considerable wealth in the process. But data’s transformative nature also raises important questions around how the benefits are shared, privacy, public security, openness and democracy, and the institutions that will govern the data revolution.

The delicate interplay between these considerations means that they have to be treated jointly, and at every level of the governance process, from local communities to the international arena. This series of essays by leading scholars and practitioners, which is also published as a special report, will explore topics including the rationale for a data strategy, the role of a data strategy for Canadian industries, and policy considerations for domestic and international data governance…

RATIONALE OF A DATA STRATEGY

THE ROLE OF A DATA STRATEGY FOR CANADIAN INDUSTRIES

BALANCING PRIVACY AND COMMERCIAL VALUES

DOMESTIC POLICY FOR DATA GOVERNANCE

INTERNATIONAL POLICY CONSIDERATIONS

EPILOGUE

Skills for a Lifetime

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Nate Silver’s commencement address at Kenyon College: “….Power has shifted toward people and companies with a lot of proficiency in data science.

I obviously don’t think that’s entirely a bad thing. But it’s by no means entirely a good thing, either. You should still inherently harbor some suspicion of big, powerful institutions and their potentially self-serving and short-sighted motivations. Companies and governments that are capable of using data in powerful ways are also capable of abusing it.

What worries me the most, especially at companies like Facebook and at other Silicon Valley behemoths, is the idea that using data science allows one to remove human judgment from the equation. For instance, in announcing a recent change to Facebook’s News Feed algorithm, Mark Zuckerberg claimed that Facebook was not “comfortable” trying to come up with a way to determine which news organizations were most trustworthy; rather, the “most objective” solution was to have readers vote on trustworthiness instead. Maybe this is a good idea and maybe it isn’t — but what bothered me was in the notion that Facebook could avoid responsibility for its algorithm by outsourcing the judgment to its readers.

I also worry about this attitude when I hear people use terms such as “artificial intelligence” and “machine learning” (instead of simpler terms like “computer program”). Phrases like “machine learning” appeal to people’s notion of a push-button solution — meaning, push a button, and the computer does all your thinking for you, no human judgment required.

But the reality is that working with data requires lots of judgment. First, it requires critical judgment — and experience — when drawing inferences from data. And second, it requires moral judgment in deciding what your goals are and in establishing boundaries for your work.

Let’s talk about that first type of judgment — critical judgment. The more experience you have in working with different data sets, the more you’ll realize that the correct interpretation of the data is rarely obvious, and that the obvious-seeming interpretation isn’t always correct. Sometimes changing a single assumption or a single line of code can radically change your conclusion. In the 2016 U.S. presidential election, for instance, there were a series of models that all used almost exactly the same inputs — but they ranged in giving Trump as high as roughly a one-in-three chance of winning the presidency (that was FiveThirtyEight’s model) to as low as one chance in 100, based on fairly subtle aspects of how each algorithm was designed….(More)”.

Plunging response rates to household surveys worry policymakers

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The Economist: “Response rates to surveys are plummeting all across the rich world. Last year only around 43% of households contacted by the British government responded to the LFS, down from 70% in 2001 (see chart). In America the share of households responding to the Current Population Survey (CPS) has fallen from 94% to 85% over the same period. The rest of Europe and Canada have seen similar trends.

Poor response rates drain budgets, as it takes surveyors more effort to hunt down interviewees. And a growing reluctance to give interviewers information threatens the quality of the data. Politicians often complain about inaccurate election polls. Increasingly misleading economic surveys would be even more disconcerting.

Household surveys derive their power from randomness. Since it is impractical to get every citizen to complete a long questionnaire regularly, statisticians interview what they hope is a representative sample instead. But some types are less likely to respond than others—people who live in flats not houses, for example. A study by Christopher Bollinger of the University of Kentucky and three others matched data from the CPS with social-security records and found that poorer and very rich households were more likely to ignore surveyors than middle-income ones. Survey results will be skewed if the types who do not answer are different from those who do, or if certain types of people are more loth to answer some questions, or more likely to fib….

Statisticians have been experimenting with methods of improving response rates: new ways to ask questions, or shorter questionnaires, for example. Payment raises response rates, and some surveys offer more money for the most reluctant interviewees. But such persistence can have drawbacks. One study found that more frequent attempts to contact interviewees raised the average response rate, but lowered the average quality of answers.

Statisticians have also been exploring supplementary data sources, including administrative data. Such statistics come with two big advantages. One is that administrative data sets can include many more people and observations than is practical in a household survey, giving researchers the statistical power to run more detailed studies. Another is that governments already collect them, so they can offer huge cost savings over household surveys. For instance, Finland’s 2010 census, which was based on administrative records rather than surveys, cost its government just €850,000 ($1.1m) to produce. In contrast, America’s government spent $12.3bn on its 2010 census, roughly 200 times as much on a per-person basis.

Recent advances in computing mean that vast data sets are no longer too unwieldy for use by researchers. However, in many rich countries (those in Scandinavia are exceptions), socioeconomic statistics are collected by several agencies, meaning that researchers who want to combine, say, health records with tax data, face formidable bureaucratic and legal challenges.

Governments in English-speaking countries are especially keen to experiment. In January HMRC, the British tax authority, started publishing real-time tax data as an “experimental statistic” to be compared with labour-market data from household surveys. Two-fifths of Canada’s main statistical agency’s programmes are based at least in part on administrative records. Last year, Britain passed the Digital Economy Act, which will give its Office of National Statistics (ONS) the right to requisition data from other departments and from private sources for statistics-and-research purposes. America is exploring using such data as part of its 2020 census.

Administrative data also have their limitations (see article). They are generally not designed to be used in statistical analyses. A data set on income taxes might be representative of the population receiving benefits or earning wages, but not the population as a whole. Most important, some things are not captured in administrative records, such as well-being, informal employment and religious affiliation….(More)”.

Most Maps of the New Ebola Outbreak Are Wrong

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Ed Kong in The Atlantic: “Almost all the maps of the outbreak zone that have thus far been released contain mistakes of this kind. Different health organizations all seem to use their own maps, most of which contain significant discrepancies. Things are roughly in the right place, but their exact positions can be off by miles, as can the boundaries between different regions.

Sinai, a cartographer at UCLA, has been working with the Ministry of Health to improve the accuracy of the Congo’s maps, and flew over on Saturday at their request. For each health zone within the outbreak region, Sinai compiled a list of the constituent villages, plotted them using the most up-to-date sources of geographical data, and drew boundaries that include these places and no others. The maps at the top of this piece show the before (left) and after (right) images….

Consider Bikoro, the health zone where the outbreak may have originated, and where most cases are found. Sinai took a list of all Bikoro’s villages, plotted them using the most up-to-date sources of geographical data, and drew a boundary that includes these places and no others. This new shape is roughly similar to the one on current maps, but with critical differences. Notably, existing maps have the village of Ikoko Impenge—one of the epicenters of the outbreak—outside the Bikoro health zone, when it actually lies within the zone.

 “These visualizations are important for communicating the reality on the ground to all levels of the health hierarchy, and to international partners who don’t know the country,” says Mathias Mossoko, the head of disease surveillance data in DRC.

“It’s really important for the outbreak response to have real and accurate data,” adds Bernice Selo, who leads the cartographic work from the Ministry of Health’s command center in Kinshasa. “You need to know exactly where the villages are, where the health facilities are, where the transport routes and waterways are. All of this helps you understand where the outbreak is, where it’s moving, how it’s moving. You can see which villages have the highest risk.”

To be clear, there’s no evidence that these problems are hampering the response to the current outbreak. It’s not like doctors are showing up in the middle of the forest, wondering why they’re in the wrong place. “Everyone on the ground knows where the health zones start and end,” says Sinai. “I don’t think this will make or break the response. But you surely want the most accurate data.”

It feels unusual to not have this information readily at hand, especially in an era when digital maps are so omnipresent and so supposedly truthful. If you search for San Francisco on Google Maps, you can be pretty sure that what comes up is actually where San Francisco is. On Google Street View, you can even walk along a beach at the other end of the world….(More)”.

But the Congo is a massive country—a quarter the size of the United States with considerably fewer resources. Until very recently, they haven’t had the resources to get accurate geolocalized data. Instead, the boundaries of the health zones and their constituent “health areas,” as well as the position of specific villages, towns, rivers, hospitals, clinics, and other landmarks, are often based on local knowledge and hand-drawn maps. Here’s an example, which I saw when I visited the National Institute for Biomedical Research in March. It does the job, but it’s clearly not to scale.

Blockchain as a force for good: How this technology could transform the sharing economy

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Aaron Fernando at Shareable: “The volatility in the price of cryptocurrencies doesn’t matter to restaurateur Helena Fabiankovic, who started Baba’s Pierogies in Brooklyn with her partner Robert in 2015. Yet she and her business are already positioned to reap the real-world benefits of the technology that underpins these digital currencies — the blockchain — and they will be at the forefront  of a sustainable, community-based peer-to-peer energy revolution because of it.

So what does a restaurateur have to do with the blockchain and local energy? Fabiankovic is one of the early participants in the Brooklyn Microgrid, a project of the startup LO3 Energy that uses a combination of innovative technologies — blockchain and smart meters — to operate a virtual microgrid in the borough of Brooklyn in New York City, New York. This microgrid enables residents to buy and sell green energy directly to their neighbors at much better rates than if they only interacted with centralized utility providers.

Just as we don’t pay much attention to the critical infrastructure that powers our digital world and exists just out of sight — from the Automated Clearing House (ACH), which undergirds our financial system, to the undersea cables that enable the Internet to be globally useful, blockchain is likely to change our lives in ways that will eventually be invisible. In the sharing economy, we have traditionally just used existing infrastructure and built platforms and services on top of it. Considering that those undersea cables are owned by private companies with their own motives and that the locations of ACH data centers are heavily classified, there is a lot to be desired in terms of transparency, resilience, and independence from self-interested third parties. That’s where open-source, decentralized infrastructure of the blockchain for the sharing economy offers much promise and potential.

In the case of Brooklyn Microgrid, which is part of an emerging model for shared energy use via the blockchain, this decentralized infrastructure would allow residents like Fabiankovic to save money and make sustainable choices. Shared ownership and community financing for green infrastructure like solar panels is part of the model. “Everyone can pay a different amount and you can get a proportional amount of energy that’s put off by the panel, based on how much that you own,” says Scott Kessler, director of business development at LO3. “It’s really just a way of crowdfunding an asset.”

The type of blockchain used by the Brooklyn Microgrid makes it possible to collect and communicate data from smart meters every second, so that the price of electricity can be updated in real time and users will still transact with each other using U.S. dollars. The core idea of the Brooklyn Microgrid is to utilize a tailored blockchain to align energy consumption with energy production, and to do this with rapidly-updated price information that then changes behavior around energy….(More)

CrowdLaw Manifesto

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At the Rockefeller Foundation Bellagio Center this spring, assembled participants  met to discuss CrowdLaw, namely how to use technology to improve the quality and effectiveness of law and policymaking through greater public engagement. We put together and signed 12 principles to promote the use of CrowdLaw by local legislatures and national parliaments, calling for legislatures, technologists and the public to participate in creating more open and participatory lawmaking practices. We invite you to sign the Manifesto using the form below.

Draft dated May 29, 2018

  1. To improve public trust in democratic institutions, we must improve how we govern in the 21st century.
  2. CrowdLaw is any law, policy-making or public decision-making that offers a meaningful opportunity for the public to participate in one or multiples stages of decision-making, including but not limited to the processes of problem identification, solution identification, proposal drafting, ratification, implementation or evaluation.
  3. CrowdLaw draws on innovative processes and technologies and encompasses diverse forms of engagement among elected representatives, public officials, and those they represent.
  4. When designed well, CrowdLaw may help governing institutions obtain more relevant facts and knowledge as well as more diverse perspectives, opinions and ideas to inform governing at each stage and may help the public exercise political will.
  5. When designed well, CrowdLaw may help democratic institutions build trust and the public to play a more active role in their communities and strengthen both active citizenship and democratic culture.
  6. When designed well, CrowdLaw may enable engagement that is thoughtful, inclusive, informed but also efficient, manageable and sustainable.
  7. Therefore, governing institutions at every level should experiment and iterate with CrowdLaw initiatives in order to create formal processes for diverse members of society to participate in order to improve the legitimacy of decision-making, strengthen public trust and produce better outcomes.
  8. Governing institutions at every level should encourage research and learning about CrowdLaw and its impact on individuals, on institutions and on society.
  9. The public also has a responsibility to improve our democracy by demanding and creating opportunities to engage and then actively contributing expertise, experience, data and opinions.
  10. Technologists should work collaboratively across disciplines to develop, evaluate and iterate varied, ethical and secure CrowdLaw platforms and tools, keeping in mind that different participation mechanisms will achieve different goals.
  11. Governing institutions at every level should encourage collaboration across organizations and sectors to test what works and share good practices.
  12. Governing institutions at every level should create the legal and regulatory frameworks necessary to promote CrowdLaw and better forms of public engagement and usher in a new era of more open, participatory and effective governing.

The CrowdLaw Manifesto has been signed by the following individuals and organizations:

Individuals

  • Victoria Alsina, Senior Fellow at The GovLab and Faculty Associate at Harvard Kennedy School, Harvard University
  • Marta Poblet Balcell , Associate Professor, RMIT University
  • Robert Bjarnason — President & Co-founder, Citizens Foundation; Better Reykjavik
  • Pablo Collada — Former Executive Director, Fundación Ciudadano Inteligente
  • Mukelani Dimba — Co-chair, Open Government Partnership
  • Hélène Landemore, Associate Professor of Political Science, Yale University
  • Shu-Yang Lin, re:architect & co-founder, PDIS.tw
  • José Luis Martí , Vice-Rector for Innovation and Professor of Legal Philosophy, Pompeu Fabra University
  • Jessica Musila — Executive Director, Mzalendo
  • Sabine Romon — Chief Smart City Officer — General Secretariat, Paris City Council
  • Cristiano Ferri Faría — Director, Hacker Lab, Brazilian House of Representatives
  • Nicola Forster — President and Founder, Swiss Forum on Foreign Policy
  • Raffaele Lillo — Chief Data Officer, Digital Transformation Team, Government of Italy
  • Tarik Nesh-Nash — CEO & Co-founder, GovRight; Ashoka Fellow
  • Beth Simone Noveck, Director, The GovLab and Professor at New York University Tandon School of Engineering
  • Ehud Shapiro , Professor of Computer Science and Biology, Weizmann Institute of Science

Organizations

  • Citizens Foundation, Iceland
  • Fundación Ciudadano Inteligente, Chile
  • International School for Transparency, South Africa
  • Mzalendo, Kenya
  • Smart Cities, Paris City Council, Paris, France
  • Hacker Lab, Brazilian House of Representatives, Brazil
  • Swiss Forum on Foreign Policy, Switzerland
  • Digital Transformation Team, Government of Italy, Italy
  • The Governance Lab, New York, United States
  • GovRight, Morocco
  • ICT4Dev, Morocco

AI trust and AI fears: A media debate that could divide society

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Article by Vyacheslav Polonski: “Unless you live under a rock, you probably have been inundated with recent news on machine learning and artificial intelligence (AI). With all the recent breakthroughs, it almost seems like AI can already predict the future. Police forces are using it to map when and where crime is likely to occur. Doctors can use it to predict when a patient is most likely to have a heart attack or stroke. Researchers are even trying to give AI imagination so it can plan for unexpected consequences.

Of course, many decisions in our lives require a good forecast, and AI agents are almost always better at forecasting than their human counterparts. Yet for all these technological advances, we still seem to deeply lack confidence in AI predictions. Recent cases show that people don’t like relying on AI and prefer to trust human experts, even if these experts are wrong.

If we want AI to really benefit people, we need to find a way to get people to trust it. To do that, we need to understand why people are so reluctant to trust AI in the first place….

Many people are also simply not familiar with many instances of AI actually working, because it often happens in the background. Instead, they are acutely aware of instances where AI goes terribly wrong:

These unfortunate examples have received a disproportionate amount of media attention, emphasising the message that humans cannot always rely on technology. In the end, it all goes back to the simple truth that machine learning is not foolproof, in part because the humans who design it aren’t….

Fortunately we already have some ideas about how to improve trust in AI — there’s light at the end of the tunnel.

  1. Experience: One solution may be to provide more hands-on experiences with automation apps and other AI applications in everyday situations (like this robot that can get you a beer from the fridge). Thus, instead of presenting the Sony’s new robot dog Aibo as an exclusive product for the upper-class, we’d recommend making these kinds of innovations more accessible to the masses. Simply having previous experience with AI can significantly improve people’s attitudes towards the technology, as we found in our experimental study. And this is especially important for the general public that may not have a very sophisticated understanding of the technology. Similar evidence also suggests the more you use other technologies such as the Internet, the more you trust them.
  2. Insight: Another solution may be to open the “black-box” of machine learning algorithms and be slightly more transparent about how they work. Companies such as Google, Airbnb and Twitter already release transparency reports on a regular basis. These reports provide information about government requests and surveillance disclosures. A similar practice for AI systems could help people have a better understanding of how algorithmic decisions are made. Therefore, providing people with a top-level understanding of machine learning systems could go a long way towards alleviating algorithmic aversion.
  3. Control: Lastly, creating more of a collaborative decision-making process will help build trust and allow the AI to learn from human experience. In our work at Avantgarde Analytics, we have also found that involving people more in the AI decision-making process could improve trust and transparency. In a similar vein, a group of researchers at the University of Pennsylvania recently found that giving people control over algorithms can help create more trust in AI predictions. Volunteers in their study who were given the freedom to slightly modify an algorithm felt more satisfied with it, more likely to believe it was superior and more likely to use in in the future.

These guidelines (experience, insight and control) could help making AI systems more transparent and comprehensible to the individuals affected by their decisions….(More)”.

On Dimensions of Citizenship

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Introduction by Niall Atkinson, Ann Lui, and Mimi Zeiger to a Special Exhibit and dedicated set of Essays: “We begin by defining citizenship as a cluster of rights, responsibilities, and attachments, and by positing their link to the built environment. Of course architectural examples of this affiliation—formal articulations of inclusion and exclusion—can seem limited and rote. The US-Mexico border wall (“The Wall,” to use common parlance) dominates the cultural imagination. As an architecture of estrangement, especially when expressed as monolithic prototypes staked in the San Diego-Tijuana landscape, the border wall privileges the rhetorical security of nationhood above all other definitions of citizenship—over the individuals, ecologies, economies, and communities in the region. And yet, as political theorist Wendy Brown points out, The Wall, like its many counterparts globally, is inherently fraught as both a physical infrastructure and a nationalist myth, ultimately racked by its own contradictions and paradoxes.

Calling border walls across the world “an ad hoc global landscape of flows and barriers,” Brown writes of the paradoxes that riddle any effort to distinguish the nation as a singular, cohesive form: “[O]ne irony of late modern walling is that a structure taken to mark and enforce an inside/outside distinction—a boundary between ‘us’ and ‘them’ and between friend and enemy—appears precisely the opposite when grasped as part of a complex of eroding lines between the police and the military, subject and patria, vigilante and state, law and lawlessness.”1 While 2018 is a moment when ideologies are most vociferously cast in binary rhetoric, the lived experience of citizenship today is rhizomic, overlapping, and distributed. A person may belong and feel rights and responsibilities to a neighborhood, a voting district, remain a part of an immigrant diaspora even after moving away from their home country, or find affiliation on an online platform. In 2017, Blizzard Entertainment, the maker of World of Warcraft, reported a user community of 46 million people across their international server network. Thus, today it is increasingly possible to simultaneously occupy multiple spaces of citizenship independent from the delineation of a formal boundary.

Conflict often makes visible emergent spaces of citizenship, as highlighted by recent acts both legislative and grassroots. Gendered bathrooms act as renewed sites of civil rights debate. Airports illustrate the thresholds of national control enacted by the recent Muslim bans. Such clashes uncover old scar tissue, violent histories and geographies of spaces. The advance of the Keystone XL pipeline across South Dakota, for example, brought the fight for indigenous sovereignty to the fore.

If citizenship itself designates a kind of border and the networks that traverse and ultimately elude such borders, then what kind of architecture might Dimensions of Citizenship offer in lieu of The Wall? What designed object, building, or space might speak to the heart of what and how it means to belong today? The participants in the United States Pavilion offer several of the clear and vital alternatives deemed so necessary by Samuel R. Delany: The Cobblestone. The Space Station. The Watershed.

Dimensions of Citizenship argues that citizenship is indissociable from the built environment, which is exactly why that relationship can be the source for generating or supporting new forms of belonging. These new forms may be more mutable and ephemeral, but no less meaningful and even, perhaps, ultimately more equitable. Through commissioned projects, and through film, video artworks, and responsive texts, Dimensions of Citizenship exhibits the ways that architects, landscape architects, designers, artists, and writers explore the changing form of citizenship: the different dimensions it can assume (legal, social, emotional) and the different dimensions (both actual and virtual) in which citizenship takes place. The works are valuably enigmatic, wide-ranging, even elusive in their interpretations, which is what contemporary conditions seem to demand. More often than not, the spaces of citizenship under investigation here are marked by histories of inequality and the violence imposed on people, non-human actors, ecologies. Our exhibition features spaces and individuals that aim to manifest the democratic ideals of inclusion against the grain of broader systems: new forms of “sharing economy” platforms, the legacies of the Underground Railroad, tenuous cross-national alliances at the border region, or the seemingly Sisyphean task of buttressing coastline topologies against the rising tides….(More)”.