Data Brokers Are a Threat to Democracy


Justin Sherman at Wired: “Enter the data brokerage industry, the multibillion dollar economy of selling consumers’ and citizens’ intimate details. Much of the privacy discourse has rightly pointed fingers at Facebook, Twitter, YouTube, and TikTok, which collect users’ information directly. But a far broader ecosystem of buying up, licensing, selling, and sharing data exists around those platforms. Data brokerage firms are middlemen of surveillance capitalism—purchasing, aggregating, and repackaging data from a variety of other companies, all with the aim of selling or further distributing it.

Data brokerage is a threat to democracy. Without robust national privacy safeguards, entire databases of citizen information are ready for purchase, whether to predatory loan companies, law enforcement agencies, or even malicious foreign actors. Federal privacy bills that don’t give sufficient attention to data brokerage will therefore fail to tackle an enormous portion of the data surveillance economy, and will leave civil rights, national security, and public-private boundaries vulnerable in the process.

Large data brokers—like Acxiom, CoreLogic, and Epsilon—tout the detail of their data on millions or even billions of people. CoreLogic, for instance, advertises its real estate and property information on 99.9 percent of the US population. Acxiom promotes 11,000-plus “data attributes,” from auto loan information to travel preferences, on 2.5 billion people (all to help brands connect with people “ethically,” it adds). This level of data collection and aggregation enables remarkably specific profiling.

Need to run ads targeting poor families in rural areas? Check out one data broker’s “Rural and Barely Making It” data set. Or how about racially profiling financial vulnerability? Buy another company’s “Ethnic Second-City Strugglers” data set. These are just some of the disturbing titles captured in a 2013 Senate report on the industry’s data products, which have only expanded since. Many other brokers advertise their ability to identify subgroups upon subgroups of individuals through criteria like race, gender, marital status, and income level, all sensitive characteristics that citizens likely didn’t know would end up in a database—let alone up for sale….(More)”.

Undoing Optimization: Civic Action in Smart Cities


Book by Alison B. Powell: “City life has been reconfigured by our use—and our expectations—of communication, data, and sensing technologies. This book examines the civic use, regulation, and politics of these technologies, looking at how governments, planners, citizens, and activists expect them to enhance life in the city. Alison Powell argues that the de facto forms of citizenship that emerge in relation to these technologies represent sites of contention over how governance and civic power should operate. These become more significant in an increasingly urbanized and polarized world facing new struggles over local participation and engagement. The author moves past the usual discussion of top-down versus bottom-up civic action and instead explains how citizenship shifts in response to technological change and particularly in response to issues related to pervasive sensing, big data, and surveillance in “smart cities.”…(More)”.

Advancing data literacy in the post-pandemic world


Paper by Archita Misra (PARIS21): “The COVID-19 crisis presents a monumental opportunity to engender a widespread data culture in our societies. Since early 2020, the emergence of popular data sites like Worldometer2 have promoted interest and attention in data-driven tracking of the pandemic. “R values”, “flattening the curve” and “exponential increase” have seeped into everyday lexicon. Social media and news outlets have filled the public consciousness with trends, rankings and graphs throughout multiple waves of COVID-19.

Yet, the crisis also reveals a critical lack of data literacy amongst citizens in many parts of the world. The lack of a data literate culture predates the pandemic. The supply of statistics and information has significantly outpaced the ability of lay citizens to make informed choices about their lives in the digital data age.

Today’s fragmented datafied information landscape is also susceptible to the pitfalls of misinformation, post-truth politics and societal polarisation – all of which demand a critical thinking lens towards data. There is an urgent need to develop data literacy at the level of citizens, organisations and society – such that all actors are empowered to navigate the complexity of modern data ecosystems.

The paper identifies three key take-aways. It is crucial to

  • forge a common language around data literacy
  • adopt a demand-driven approach and participatory approach to doing data literacy
  • move from ad-hoc programming towards sustained policy, investment and impact…(More)”.

Socially Responsible Data Labeling


Blog By Hamed Alemohammad at Radiant Earth Foundation: “Labeling satellite imagery is the process of applying tags to scenes to provide context or confirm information. These labeled training datasets form the basis for machine learning (ML) algorithms. The labeling undertaking (in many cases) requires humans to meticulously and manually assign captions to the data, allowing the model to learn patterns and estimate them for other observations.

For a wide range of Earth observation applications, training data labels can be generated by annotating satellite imagery. Images can be classified to identify the entire image as a class (e.g., water body) or for specific objects within the satellite image. However, annotation tasks can only identify features observable in the imagery. For example, with Sentinel-2 imagery at the 10-meter spatial resolution, one cannot detect the more detailed features of interest, such as crop types but would be able to distinguish large croplands from other land cover classes.

Human error in labeling is inevitable and results in uncertainties and errors in the final label. As a result, it’s best practice to examine images multiple times and then assign a majority or consensus label. In general, significant human resources and financial investment is needed to annotate imagery at large scales.

In 2018, we identified the need for a geographically diverse land cover classification training dataset that required human annotation and validation of labels. We proposed to Schmidt Futures a project to generate such a dataset to advance land cover classification globally. In this blog post, we discuss what we’ve learned developing LandCoverNet, including the keys to generating good quality labels in a socially responsible manner….(More)”.

How we mapped billions of trees in West Africa using satellites, supercomputers and AI


Martin Brandt and Kjeld Rasmussen in The Conversation: “The possibility that vegetation cover in semi-arid and arid areas was retreating has long been an issue of international concern. In the 1930s it was first theorized that the Sahara was expanding and woody vegetation was on the retreat. In the 1970s, spurred by the “Sahel drought”, focus was on the threat of “desertification”, caused by human overuse and/or climate change. In recent decades, the potential impact of climate change on the vegetation has been the main concern, along with the feedback of vegetation on the climate, associated with the role of the vegetation in the global carbon cycle.

Using high-resolution satellite data and machine-learning techniques at supercomputing facilities, we have now been able to map billions of individual trees and shrubs in West Africa. The goal is to better understand the real state of vegetation coverage and evolution in arid and semi-arid areas.

Finding a shrub in the desert – from space

Since the 1970s, satellite data have been used extensively to map and monitor vegetation in semi-arid areas worldwide. Images are available in “high” spatial resolution (with NASA’s satellites Landsat MSS and TM, and ESA’s satellites Spot and Sentinel) and “medium or low” spatial resolution (NOAA AVHRR and MODIS).

To accurately analyse vegetation cover at continental or global scale, it is necessary to use the highest-resolution images available – with a resolution of 1 metre or less – and up until now the costs of acquiring and analysing the data have been prohibitive. Consequently, most studies have relied on moderate- to low-resolution data. This has not allowed for the identification of individual trees, and therefore these studies only yield aggregate estimates of vegetation cover and productivity, mixing herbaceous and woody vegetation.

In a new study covering a large part of the semi-arid Sahara-Sahel-Sudanian zone of West Africa, published in Nature in October 2020, an international group of researchers was able to overcome these limitations. By combining an immense amount of high-resolution satellite data, advanced computing capacities, machine-learning techniques and extensive field data gathered over decades, we were able to identify individual trees and shrubs with a crown area of more than 3 m2 with great accuracy. The result is a database of 1.8 billion trees in the region studied, available to all interested….(More)”

Supercomputing, machine learning, satellite data and field assessments allow to map billions of individual trees in West Africa. Martin Brandt, Author provided

Why Trust Matters: An Economist’s Guide to the Ties That Bind Us


Book by Benjamin Ho: “Have economists neglected trust? The economy is fundamentally a network of relationships built on mutual expectations. More than that, trust is the glue that holds civilization together. Every time we interact with another person—to make a purchase, work on a project, or share a living space—we rely on trust. Institutions and relationships function because people place confidence in them. Retailers seek to become trusted brands; employers put their trust in their employees; and democracy works only when we trust our government.

Benjamin Ho reveals the surprising importance of trust to how we understand our day-to-day economic lives. Starting with the earliest societies and proceeding through the evolution of the modern economy, he explores its role across an astonishing range of institutions and practices. From contracts and banking to blockchain and the sharing economy to health care and climate change, Ho shows how trust shapes the workings of the world. He provides an accessible account of how economists have applied the mathematical tools of game theory and the experimental methods of behavioral economics to bring rigor to understanding trust. Bringing together insights from decades of research in an approachable format, Why Trust Matters shows how a concept that we rarely associate with the discipline of economics is central to the social systems that govern our lives….(More)”.

A Resurgence of Democracy in 2040?


Blog by Steven Aftergood: “The world will be “increasingly out of balance and contested at every level” over the next twenty years due to the pressures of demographic, environmental, economic and technological change, a new forecast from the National Intelligence Council called Global Trends 2040 said last week.

But among the mostly grim possible futures that can be plausibly anticipated — international chaos, political paralysis, resource depletion, mounting poverty — one optimistic scenario stands out: “In 2040, the world is in the midst of a resurgence of open democracies led by the United States and its allies.”

How could such a global renaissance of democracy possibly come about?

The report posits that between now and 2040 technological innovation in open societies will lead to economic growth, which will enable solutions to domestic problems, build public confidence, reduce vulnerabilities and establish an attractive model for emulation by others. Transparency is both a precondition and a consequence of this process.

“Open, democratic systems proved better able to foster scientific research and technological innovation, catalyzing an economic boom. Strong economic growth, in turn, enabled democracies to meet many domestic needs, address global challenges, and counter rivals,” the report assessed in this potential scenario.

“With greater resources and improving services, these democracies launched initiatives to crack down on corruption, increase transparency, and improve accountability worldwide, boosting public trust. These efforts helped to reverse years of social fragmentation and to restore a sense of civic nationalism.”

“The combination of rapid innovation, a stronger economy, and greater societal cohesion enabled steady progress on climate and other challenges. Democratic societies became more resilient to disinformation because of greater public awareness and education initiatives and new technologies that quickly identify and debunk erroneous information. This environment restored a culture of vigorous but civil debate over values, goals, and policies.”

“Strong differences in public preferences and beliefs remained but these were worked out democratically.”

In this hopeful future, openness provided practical advantages that left closed authoritarian societies lagging behind.

“In contrast to the culture of collaboration prevailing in open societies, Russia and China failed to cultivate the high-tech talent, investment, and environment necessary to sustain continuous innovation.”

“By the mid-2030s, the United States and its allies in Europe and Asia were the established global leaders in several technologies, including AI, robotics, the Internet of Things, biotech, energy storage, and additive manufacturing.”

The success of open societies in problem solving, along with their economic and social improvements, inspired other countries to adopt the democratic model.

“Technological success fostered a widely perceived view among emerging and developing countries that democracies were more adaptable and resilient and better able to cope with growing global challenges.”…(More)”.

Regulating Personal Data : Data Models and Digital Services Trade


Report by Martina Francesca Ferracane and Erik van der Marel: “While regulations on personal data diverge widely between countries, it is nonetheless possible to identify three main models based on their distinctive features: one model based on open transfers and processing of data, a second model based on conditional transfers and processing, and third a model based on limited transfers and processing. These three data models have become a reference for many other countries when defining their rules on the cross-border transfer and domestic processing of personal data.

The study reviews their main characteristics and systematically identifies for 116 countries worldwide to which model they adhere for the two components of data regulation (i.e. cross-border transfers and domestic processing of data). In a second step, using gravity analysis, the study estimates whether countries sharing the same data model exhibit higher or lower digital services trade compared to countries with different regulatory data models. The results show that sharing the open data model for cross-border data transfers is positively associated with trade in digital services, while sharing the conditional model for domestic data processing is also positively correlated with trade in digital services. Country-pairs sharing the limited model, instead, exhibit a double whammy: they show negative trade correlations throughout the two components of data regulation. Robustness checks control for restrictions in digital services, the quality of digital infrastructure, as well as for the use of alternative data sources….(More)”.

The Case for Local Data Sharing Ordinances


Paper by Beatriz Botero Arcila: “Cities in the US have started to enact data-sharing rules and programs to access some of the data that technology companies operating under their jurisdiction – like short-term rental or ride hailing companies – collect. This information allows cities to adapt too to the challenges and benefits of the digital information economy. It allows them to understand what their impact is on congestion, the housing market, the local job market and even the use of public spaces. It also empowers them to act accordingly by, for example, setting vehicle caps or mandating a tailored minimum pay for gig-workers. These companies, however, sometimes argue that sharing this information attempts against their users’ privacy rights and their privacy rights, because this information is theirs; it’s part of their business records. The question is thus what those rights are, and whether it should and could be possible for local governments to access that information to advance equity and sustainability, without harming the legitimate privacy interests of both individuals and companies. This Article argues that within current Fourth Amendment doctrine and privacy law there is space for data-sharing programs. Privacy law, however, is being mobilized to alter the distribution of power and welfare between local governments, companies, and citizens within current digital information capitalism to extend those rights beyond their fair share and preempt permissible data-sharing requests. The Article warns that if the companies succeed in their challenges, privacy law will have helped shield corporate power from regulatory oversight, while still leaving individuals largely unprotected and submitting local governments further to corporate interests….(More)”.

The Locus Charter


Press Release: “A coalition of location data practitioners has developed an ethics charter to promote responsible use of location technology. The Locus Charter, facilitated by The Benchmark Initiative and EthicalGEO, is a proposed set of common international principles that can guide responsible practice when using location data, including through safeguarding privacy, protecting the vulnerable, and addressing any harmful impacts of bias in data.

The Benchmark Initiative and EthicalGEO are inviting individuals, businesses, and government agencies from around the world to join The Locus Charter community and help to shape equitable and sustainable practice around the use of location data. Member organisations include the American Geographical Society and Britain’s mapping agency, Ordnance Survey.

Location data is currently at the heart of the debate around digital privacy. Tech giants Apple and Facebook are in conflict over how much apps should be able to track users. Recent research shows personal information can be inferred from location data collected from smartphones, and that anonymisation can often be reversed to reveal people’s identities. The New York Times has unveiled a largely hidden trade in location data about individual people, collected from smartphones. As phones and other devices generate more detailed location data, these challenges grow…

The Locus Charter aims to restore public trust in location technology, in order to enable its transformative power to, improve public health, enhance our response to the Covid-19 pandemic, fight climate change, protect the environment and more….(More)”.