Collection

Manual of Digital Earth

Curated on November 24, 2019November 24, 2019 by Stefaan Verhulst

Book by Huadong Guo, Michael F. Goodchild and Alessandro Annoni: “This open access book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing, analysing and mining the rapidly growing volume of global data sets about the Earth.

The main aspects of Digital Earth covered here include: Digital Earth platforms, remote sensing and navigation satellites, processing and visualizing geospatial information, geospatial information infrastructures, big data and cloud computing, transformation and zooming, artificial intelligence, Internet of Things, and social media. Moreover, the book covers in detail the multi-layered/multi-faceted roles of Digital Earth in response to sustainable development goals, climate changes, and mitigating disasters, the applications of Digital Earth (such as digital city and digital heritage), the citizen science in support of Digital Earth, the economic value of Digital Earth, and so on. This book also reviews the regional and national development of Digital Earth around the world, and discusses the role and effect of education and ethics. Lastly, it concludes with a summary of the challenges and forecasts the future trends of Digital Earth.By sharing case studies and a broad range of general and scientific insights into the science and technology of Digital Earth, this book offers an essential introduction for an ever-growing international audience….(More)”.

Unregulated Health Research Using Mobile Devices: Ethical Considerations and Policy Recommendations

Curated on November 24, 2019November 26, 2019 by Stefaan Verhulst

Paper by Mark A. Rothstein et al: “Mobile devices with health apps, direct-to-consumer genetic testing, crowd-sourced information, and other data sources have enabled research by new classes of researchers. Independent researchers, citizen scientists, patient-directed researchers, self-experimenters, and others are not covered by federal research regulations because they are not recipients of federal financial assistance or conducting research in anticipation of a submission to the FDA for approval of a new drug or medical device. This article addresses the difficult policy challenge of promoting the welfare and interests of research participants, as well as the public, in the absence of regulatory requirements and without discouraging independent, innovative scientific inquiry. The article recommends a series of measures, including education, consultation, transparency, self-governance, and regulation to strike the appropriate balance….(More)”.

The Right to Be Seen

Curated on November 24, 2019November 24, 2019 by Stefaan Verhulst

Anne-Marie Slaughter and Yuliya Panfil at Project Syndicate: “While much of the developed world is properly worried about myriad privacy outrages at the hands of Big Tech and demanding – and securing – for individuals a “right to be forgotten,” many around the world are posing a very different question: What about the right to be seen?

Just ask the billion people who are locked out of services we take for granted – things like a bank account, a deed to a house, or even a mobile phone account – because they lack identity documents and thus can’t prove who they are. They are effectively invisible as a result of poor data.

The ability to exercise many of our most basic rights and privileges – such as the right to vote, drive, own property, and travel internationally – is determined by large administrative agencies that rely on standardized information to determine who is eligible for what. For example, to obtain a passport it is typically necessary to present a birth certificate. But what if you do not have a birth certificate? To open a bank account requires proof of address. But what if your house doesn’t have an address?

The inability to provide such basic information is a barrier to stability, prosperity, and opportunity. Invisible people are locked out of the formal economy, unable to vote, travel, or access medical and education benefits. It’s not that they are undeserving or unqualified, it’s that they are data poor.

In this context, the rich digital record provided by our smartphones and other sensors could become a powerful tool for good, so long as the risks are acknowledged. These gadgets, which have become central to our social and economic lives, leave a data trail that for many of us is the raw material that fuels what Harvard’s Shoshana Zuboff calls “surveillance capitalism.” Our Google location history shows exactly where we live and work. Our email activity reveals our social networks. Even the way we hold our smartphone can give away early signs of Parkinson’s.

But what if citizens could harness the power of these data for themselves, to become visible to administrative gatekeepers and access the rights and privileges to which they are entitled? Their virtual trail could then be converted into proof of physical facts.

That is beginning to happen. In India, slum dwellers are using smartphone location data to put themselves on city maps for the first time and register for addresses that they can then use to receive mail and register for government IDs. In Tanzania, citizens are using their mobile payment histories to build their credit scores and access more traditional financial services. And in Europe and the United States, Uber drivers are fighting for their rideshare data to advocate for employment benefits….(More)”.

The Wisdom of the Market: Using Human Factors to Design Prediction Markets for Collective Intelligence

Curated on November 24, 2019November 26, 2019 by Stefaan Verhulst

Paper by Lorenzo Barberis Canonico, Christopher Flathmann, Dr. Nathan McNeese: “There is an ever-growing literature on the power of prediction markets to harness “the wisdom of the crowd” from large groups of people. However, traditional prediction markets are not designed in a human-centered way, often restricting their own potential. This creates the opportunity to implement a cognitive science perspective on how to enhance the collective intelligence of the participants. Thus, we propose a new model for prediction markets that integrates human factors, cognitive science, game theory and machine learning to maximize collective intelligence. We do this by first identifying the connections between prediction markets and collective intelligence, to then use human factors techniques to analyze our design, culminating in the practical ways with which our design enables artificial intelligence to complement human intelligence….(More)”.

“Mind the Five”: Guidelines for Data Privacy and Security in Humanitarian Work With Undocumented Migrants and Other Vulnerable Populations

Curated on November 24, 2019November 24, 2019 by Stefaan Verhulst

Paper by Sara Vannini, Ricardo Gomez and Bryce Clayton Newell: “The forced displacement and transnational migration of millions of people around the world is a growing phenomenon that has been met with increased surveillance and datafication by a variety of actors. Small humanitarian organizations that help irregular migrants in the United States frequently do not have the resources or expertise to fully address the implications of collecting, storing, and using data about the vulnerable populations they serve. As a result, there is a risk that their work could exacerbate the vulnerabilities of the very same migrants they are trying to help. In this study, we propose a conceptual framework for protecting privacy in the context of humanitarian information activities (HIA) with irregular migrants. We draw from a review of the academic literature as well as interviews with individuals affiliated with several US‐based humanitarian organizations, higher education institutions, and nonprofit organizations that provide support to undocumented migrants. We discuss 3 primary issues: (i) HIA present both technological and human risks; (ii) the expectation of privacy self‐management by vulnerable populations is problematic; and (iii) there is a need for robust, actionable, privacy‐related guidelines for HIA. We suggest 5 recommendations to strengthen the privacy protection offered to undocumented migrants and other vulnerable populations….(More)”.

National SDG Review: data challenges and opportunities

Curated on November 23, 2019November 23, 2019 by Stefaan Verhulst

Press Release: “…the Partnership in Statistics for Development in the 21st Century (PARIS21) and Partners for Review launched a landmark new paper that identifies the factors preventing countries from fully exploiting their data ecosystem and proposes solutions to strengthening statistical capacities to achieve the 2030 Agenda for Sustainable Development.

Ninety percent of the data in the world has been created in the past two years, yet many countries with low statistical capacity struggle to produce, analyse and communicate the data necessary to advance sustainable development. At the same time, demand for more and better data and statistics is increasingly massively, with international agreements like the 2030 Agenda placing unprecedented demand on countries to report on more than 230 indicators.

Using PARIS21’s Capacity Development 4.0 (CD 4.0) approach, the paper shows that leveraging data available in the data ecosystem for official reporting requires new capacity in terms of skills and knowledge, management, politics and power. The paper also shows that these capacities need to be developed at both the organisational and systemic level, which involves the various channels and interactions that connect different organisations.

Aimed at national statistics offices, development professionals and others involved in the national data ecosystem, the paper provides a roadmap that can help national statistical systems develop and strengthen the capacities of traditional and new actors in the data ecosystem to improve both the follow-up and review process of the 2030 Agenda as well as the data architecture for sustainable development at the national level…(More)”.

European E-Democracy in Practice

Curated on November 23, 2019November 23, 2019 by Stefaan Verhulst

Book by Hennen, Leonhard (et al.): “This open access book explores how digital tools and social media technologies can contribute to better participation and involvement of EU citizens in European politics. By analyzing selected representative e-participation projects at the local, national and European governmental levels, it identifies the preconditions, best practices and shortcomings of e-participation practices in connection with EU decision-making procedures and institutions. The book features case studies on parliamentary monitoring, e-voting practices, and e-publics, and offers recommendations for improving the integration of e-democracy in European politics and governance. Accordingly, it will appeal to scholars as well as practitioners interested in identifying suitable e-participation tools for European institutions and thus helps to reduce the EU’s current democratic deficit….(More)”.

Why Data Is Not the New Oil

Curated on November 23, 2019November 25, 2019 by Stefaan Verhulst

Blogpost by Alec Stapp: “Data is the new oil,” said Jaron Lanier in a recent op-ed for The New York Times. Lanier’s use of this metaphor is only the latest instance of what has become the dumbest meme in tech policy. As the digital economy becomes more prominent in our lives, it is not unreasonable to seek to understand one of its most important inputs. But this analogy to the physical economy is fundamentally flawed. Worse, introducing regulations premised upon faulty assumptions like this will likely do far more harm than good. Here are seven reasons why “data is the new oil” misses the mark:

1. Oil is rivalrous; data is non-rivalrous

If someone uses a barrel of oil, it can’t be consumed again. But, as Alan McQuinn, a senior policy analyst at the Information Technology and Innovation Foundation, noted, “when consumers ‘pay with data’ to access a website, they still have the same amount of data after the transaction as before. As a result, users have an infinite resource available to them to access free online services.” Imposing restrictions on data collection makes this infinite resource finite.

2. Oil is excludable; data is non-excludable

Oil is highly excludable because, as a physical commodity, it can be stored in ways that prevent use by non-authorized parties. However, as my colleagues pointed out in a recent comment to the FTC: “While databases may be proprietary, the underlying data usually is not.” They go on to argue that this can lead to under-investment in data collection:

[C]ompanies that have acquired a valuable piece of data will struggle both to prevent their rivals from obtaining the same data as well as to derive competitive advantage from the data. For these reasons, it also means that firms may well be more reluctant to invest in data generation than is socially optimal. In fact, to the extent this is true there is arguably more risk of companies under-investing in data generation than of firms over-investing in order to create data troves with which to monopolize a market. This contrasts with oil, where complete excludability is the norm.

3. Oil is fungible; data is non-fungible

Oil is a commodity, so, by definition, one barrel of oil of a given grade is equivalent to any other barrel of that grade. Data, on the other hand, is heterogeneous. Each person’s data is unique and may consist of a practically unlimited number of different attributes that can be collected into a profile. This means that oil will follow the law of one price, while a dataset’s value will be highly contingent on its particular properties and commercialization potential.

4. Oil has positive marginal costs; data has zero marginal costs

There is a significant expense to producing and distributing an additional barrel of oil (as low as $5.49 per barrel in Saudi Arabia; as high as $21.66 in the U.K.). Data is merely encoded information (bits of 1s and 0s), so gathering, storing, and transferring it is nearly costless (though, to be clear, setting up systems for collecting and processing can be a large fixed cost). Under perfect competition, the market clearing price is equal to the marginal cost of production (hence why data is traded for free services and oil still requires cold, hard cash)….(More)”.

Principles alone cannot guarantee ethical AI

Curated on November 23, 2019November 25, 2019 by Stefaan Verhulst

Paper by Brent Mittelstadt: “Artificial intelligence (AI) ethics is now a global topic of discussion in academic and policy circles. At least 84 public–private initiatives have produced statements describing high-level principles, values and other tenets to guide the ethical development, deployment and governance of AI. According to recent meta-analyses, AI ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics. Despite the initial credibility granted to a principled approach to AI ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach for the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement….(More)”.